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Acknowledgement First and foremost thanks to ALLAH

I would like to express my sincere appreciation and gratitude to Prof.

Dr.Ibrahim Mohammady Ibrahim, Professor of Physiology, and former

Head of Physiology department, faculty of Medicine, Cairo University,

for his unlimited encouragement, kind supervision and productive

guidance.

I am greatly thankful and grateful to Prof. Dr.Iman Abd el Salam

Sood Professor of Pediatric and former Head of Pediatric department,

faculty of Medicine, Cairo University, for her keen supervision, kind

help and valuable instructions.

I would like to thank Dr. Nermeen Ahmed Al Desouky, Assistant

professor of Clinical Pathology, faculty of Medicine, Cairo University,

who offered me great help throughout this work.

I would like to express my special thanks and gratitude to Prof Dr.

Hassan Mohamed Eissa, Head of Physiology department, faculty of

Medicine, Cairo University.

Shaimaa Nasr Amin

Abstract

Diabetes mellitus with pregnancy causes increased mortality and morbidity to

both the mother and her offspring .The aim of this study is to investigate the

effect of maternal diabetes on some hematological and biochemical parameters

of their newborn infants. The study population consisted of 60 neonates divided

into 3 groups (each consists of 20 neonates); group I (control group), group II

(Infants of diabetic mothers with pregestational diabetes) and group III (Infants

of diabetic mothers with gestational diabetes).

Routine investigations were performed for these neonates in the form of

measuring serum glucose, calcium, total and direct bilirubin levels, complete

blood count and arterial blood gas analysis; measurements were performed once

for control group just after birth and twice for infants of diabetic mothers

(IDMs) on admission and just before discharge from neonatal intensive care

unit (NICU).

Some of the measured variables are affected in IDMs while others showed no

significant difference as compared to control, and the reversibility of the

affected variables to normal level were not the same on discharge from NICU.

Keywords:

Infants of diabetic mothers, gestational diabetes, pregestational diabetes, hematological changes, biochemical changes.

LIST OF CONTENTS Page

• Introduction and Aim of the work 1

• Review of literature

Chapter 1: Diabetes and Pregnancy 3

Chapter 2: Infants of Diabetic Mothers 32

• Subjects and Methods 64

• Results 71

• Discussion 110

• Summary 126

• References 131

• Arabic summary

List of Abbreviations

i

1, 25(OH)2 D 1, 25 dihydroxy vitamin D AA Autoantibodies ABG Arterial Blood Gases

ACOG American College of Obstetricians and Gynecologists

ADIPS Australian Diabetes in Pregnancy Society AGA Appropriate for gestational age

Akt serine/ threonine kinase AMPK AMP-activated protein kinase ANOVA Analysis of variance aPKC Activated protein kinase C ASP Acylation stimulating protein BM Basal plasma membrane BMI Body Mass Index C.O Cardiac output CaO2 Blood oxygen content CaR Calcium-sensing receptor CGRP Calcitonin gene related peptide CBC Complete blood count CE Cholesterol esters CETP Cholesterol ester transfer protein CO Carbon monoxide CT Calcitonin CTR CT receptors DAG Diacylglycerol DO2 Oxygen delivery DSB Direct Serum Bilirubin EFA Essential fatty acid ELBW Extremely low birth weight EPO Erythropoietin ER Endoplasmic reticulum FFA Free Fatty Acid GA Gestational age


ii

GAD65A Glutamic acid decarboxylase -directed against the 65 K isoform of glutamic acid

GDM Gestational diabetes mellitus GI Glycemic Index GLUTs Glucose transporters Gs stimulating G protein GSIS Glucose stimulated insulin secretion HAPO Hyperglycemia and Adverse Pregnancy Outcome Hb Hemoglobin HbA Adult haemoglobin HbA1c Glycosylated hemoglobin HbF Fetal haemoglobin Hct Hematocrit HDL High density lipoprotein HIF Hypoxia-inducible factor HL Hepatic lipase HLA Human leukocyte antigen HR Heart rate HNF1A Hepatocyte nuclear factor-1alpha hPL Human placental lactogen IA-2A Insulinoma associated antigens iCa Ionized Ca ICAs Islet cell cytoplasm IDMs Infants of diabetic mothers IGF-1 Insulin like growth factor 1 IGFR Insulin growth factor receptor IGFBP-1 Insulin like growth factor binding protein-1 IGT Impaired Glucose Tolerence INDMs Infants of non diabetic mothers

IR Insulin receptor IRS-1 Insulin receptor substrate-1 IRTK Insulin receptor tyrosine kinase IUGR Intrauterine growth restriction KBs Ketone Bodies


iii

KCNJ11

Potassium inwardly rectifying channel subfamily J, Member 11

LADA latent autoimmune diabetes of the adult LCPUFA Long-chain polyunsaturated fatty acid LDL Low density lipoprotein LGA Large for gestational age LPL Lipoprotein lipase MAPK Mitogen activated protein kinase MCH Mean Corpuscular Hemoglobin MCHC Mean Corpuscular Hemoglobin Concentration MCV Mean corpuscular volume MODY Maturity onset diabetes of the young MR Mitral regurge NBS New Ballard score NEFA Non-esterified fatty acids NF-κB Nuclear factor-κB NGT Normal Glucose Tolerance NICU Neonatal Intensive Care Unit NZSSD New Zealand Society for the Study of Diabetes ox-LDL Oxidised low-density lipoprotein P Phosphorus PC-1 Plasma cell membrane glycoprotein-1 PCOS Polycystic ovary syndrome PGDM Pregestational diabetes mellitus PIP3 Phosphatidylinositol (3, 4, 5)-trisphosphate PKC Protein kinasesC PMNL Polymorphonuclear Leukocytes PNA Postnatal age PPAR-α Peroxisome proliferator-activated receptor -alpha PR Pulmonary regurge PTH Parathyroid hormone PTHrP PTH-related protein Ptcco2 Transcutaneous measurement of Pco2


iv

PVH Pathologic ventricular hypertrophy RDS Respiratory Distress Syndrome RDW RedCell Distribution Width SaO2 Hemoglobin saturation SD Standard Deviation SGA Small for gestational age SOD Superoxide dismutase Spo2 Pulse oximetry oxygen saturation SPSS Statistical Package for the Social Science STfR Serum transferrin receptors SV Stroke volume TAS Total antioxidant status tCa Total Ca concentrations TCR T-cell receptor TfR-F index Transferrin receptors to ferritin ratio TG Triglyceride TK Tyrosine kinase TLC Total Leukocytic Count TNF-α Tumour necrosis factor-alpha TR Tricuspid regurge

TSB Total Serum Bilirubin

TReg T regulatory cells TTN Transient Tachypnea of the Newborn UCP Uncoupling protein UDPGT Uridine diphosphoglucuronosyl transferase

UGT Uridine diphosphoglucuronate Glucuronosyltransferase

UGT1A1 a specific enzyme A1 isoform of UGT VEGF Vascular endothelial growth factor VLDL Very low density lipoprotein WHO World Health Organization

List of Tables

v

Tables of Review of literature Table No.

Title Page

1 Priscilla White’s last classification for diabetes in

pregnancy modified by Pedersen

8

2 Recommended values for the diagnosis of gestational

diabetes

29

3 Normal Hemoglobin levels in neonates 56

Tables of the Results Table No.

Title Page

1 Shows mean ±standard deviation (SD) of the measured variables among studied groups

71-72

2 Paired Sample test for serum glucose and calcium at

admission and before discharge (Group II)

73

3 Paired Sample test for Arterial blood gas analysis

components at admission and before discharge (Group II)

74

4 Paired Sample test for total and direct bilirubin at admission

and before discharge (Group II)

74

5 Paired Sample test for complete Blood Count among at

admission and before discharge (Group II)

75

6 Paired Sample test for serum glucose and calcium at

admission and before discharge (Group III)

76

7

Paired Sample test for Arterial blood gas analysis

components at


77

8 Paired Sample test for total and direct bilirubin at admission 77

List of Tables

vi

and before discharge (Group III)

9 Paired Sample test for Complete Blood Count among at


78

10 Comparison of serum glucose and calcium in group II, group

III on admission and control group.

79

11 Comparison of Arterial Blood Gas analysis in group II,

group III on admission and control group.

80

12 Comparison of total and direct serum bilirubin in group II,

group III on admission and control group

81

13 Comparison of Complete Blood Count in control, group II

on admission and group III on admission

82

14 Comparison of serum glucose and calcium in, group II,

group III before discharge and control group.

83

15 Comparison of Arterial Blood Gas analysis in group II,


84

16 Comparison of total and direct serum bilirubin in group II ,

group III before discharge and control group

84

17 Comparison of Complete Blood Count in, group II, group III

before discharge and control group

86

18 No significant correlation between serum glucose levels TSB in control group (group I)

95

19 A significant positive correlation between serum glucose level and total serum bilirubin in group II on admission

96

20 No significant correlation between serum glucose (mg/dl) levels and TSB (mg/dl) in groupIII on admission (groupIII a)

97

21 No significant correlation between gestational age and total leucocytic count in control group (group I)

98

List of Tables

vii

22 No significant correlation between gestational age and total leucocytic count group II on admission (group IIa)

99

23 No significant correlation between gestational age and total leucocytic count in groupIII on admission (group IIIa)

100

24 No significant correlation between staff count and gestational age in control group (group I)

101

25 No significant correlation between staff count and gestational age in group II on admission (group IIa)

102

26 No significant correlation between staff count and gestational age in groupIII on admission (group IIIa)

103

27 No significant correlation between reticulocytic index and gestational age in control group (group I)

104

28 A significant positive correlation between reticulocytic index and gestational age in group II on admission (group IIa)

105

29 No significant correlation between reticulocytic index and gestational age in groupIII on admission (group IIIa)

106

30 No significant correlation between total serum bilirubin and gestational age in control group (group I)

107

31 No significant correlation between total serum bilirubin and gestational age in group II on admission (group IIa)

108

32 No significant correlation between total serum bilirubin and gestational age in groupIII on admission (group IIIa)

109

List of Figures

viii

Figures of Review of literature Figure

No. Title Page

1 Overview of maternal /fetal nutrient transport and

availability

3

2 Relationship of adipose tissue lipolytic activity with

lipoprotein

7

3 Intermediary metabolism in non-pregnant ,normal

pregnancy and gestational diabetes

16

4 Summary of Potential Mechanisms of insulin resistance in

skeletal muscle during late pregnancy in human gestational

diabetes

19

5 Scheme depicting the putative sequence of events that may

take place in women with autoimmune gestational diabetes

mellitus (GDM)

23

6 Problems found in IDMs 32

7 Obesity and impaired glucose tolerance in offspring of

diabetic mothers

37

8 Hemoglobin switching 55

9 chemical structure of naturally occurring unconjugated

bilirubin

59

Figures of Subjects and Methods Figure

No. Title Page

1 New Ballard Score 66

List of Figures

ix

Figures of the Results Figure

No. Title Page

1 Comparison of plasma glucose level (mg/dl) among the

studied groups

87

2 Comparison of plasma calcium level (mg/dl) among the studied groups

87

3 Comparison of serum total bilirubin (mg/dl) level among the studied groups

88

4 Comparison of serum level of direct bilirubin (mg/dl) among the studied group

88

5 Comparison of hemoglobin level among the studied group

89

6 Comparison of packed cell volume (%) among the studied group

89

7 Comparison of total leucocytic count among the studied group

90

8 Comparison of staff. Count among the studied group 90 9 Comparison of platelets counts among the studied group

91

10 Comparison of red cell distribution width among the studied group

91

11 Comparison of oxygen tension (mm Hg) among the studied group

92

12 Comparison of carbon dioxide tension among the studied group

92

13 Comparison of bicarbonate level among the studied group

93

14 Comparison of pH among the studied group

93

List of Figures

x

15 Comparison of base deficit/excess among the studied group 94 16 No significant correlation between serum glucose level TSB

in control group (group I)

95

17 A significant positive correlation between serum glucose level and total serum bilirubin in group II on admission

96

18 No significant correlation between serum glucose (mg/dl) levels and TSB (mg/dl) in groupIII on admission (group IIIa)

97

19 No significant correlation between gestational age and total leucocytic count in control group (Group I)

98

20 No significant correlation between gestational age and total leucocytic count in group II on admission (group IIa)

99

21 No significant correlation between gestational age and total leucocytic count in groupIII on admission (group IIIa)

100

22 No significant correlation between staff count and gestational age in control group (group I)

101

23 No significant correlation between staff count and gestational age in group II on admission (group IIa)

102

24 No significant correlation between staff count and gestational age in groupIII on admission (group IIIa)

103

25 No significant correlation between reticulocytic index and gestational age in control group (group I)

104

26 A significant positive correlation between Reticulocytic index and gestational age in group II on admission (group IIa)

105

27 No significant correlation between reticulocytic index and gestational age in groupIII on admission (group IIIa)

106

List of Figures

xi

28 No significant correlation between total serum bilirubin and gestational age in control group (group I)

107

29 No significant correlation between total serum bilirubin and gestational age in group II on admission (group IIa)

108

30 No significant correlation between total serum bilirubin and gestational age in groupIII on admission (group IIIa)

109

Introduction and aim of the work

1

Introduction

Diabetes mellitus during pregnancy increases fetal and maternal

morbidity and mortality (Walkinshaw, 2005). Gestational diabetes mellitus

(GDM) represents approximately 90% of these cases and affects from 2 to more

than 10% of all pregnancies, and sometimes much higher, depending on the

population being tested and the diagnostic criteria used (Moses and Cheung,

2009) and varies in direct proportion to typeII diabetes mellitus in the

background population (Ben-Haroush et al., 2004).

Metabolic changes occur in normal pregnancy in response to the increase

in nutrient needs of the fetus and the mother. There are two main changes that

occur during pregnancy, the first is progressive insulin resistance that begins

near midpregnancy and progresses through the third trimester to the level that

approximates the insulin resistance seen in individuals with type II diabetes

mellitus (Lain and Catalano, 2007).The insulin resistance appears to result

from a combination of increased maternal adiposity and the placental secretion

of anti-insulin hormones (Stuebe et al., 2009).

The second change is the compensatory increase in insulin secretion by

the pancreatic beta-cells to overcome the insulin resistance of pregnancy. As a

result, circulating glucose levels are kept within normal (Stuebe et al., 2009). If

there is maternal defect in insulin secretion and in glucose utilization, GDM will

occur as the diabetogenic hormones rise to their peak levels (Negrato et al.,

2009). Abnormal concentrations of maternal glucose, lipids, and amino acids

may influence fetal development, leading to changes in metabolism, weight, and

behaviour. Congenital anomalies are more frequent in infants of diabetic

mothers. Increased glucose metabolism in embryo cells increases oxidative

stress through hexosamine biosynthetic pathway (Horal et al., 2004) or hypoxia

(Li et al., 2005). Fetal organogenesis is completed by seven weeks

Introduction and aim of the work

2

postconception and there is an increased prevalence of congenital anomalies and

spontaneous abortions in diabetic women with poor glycaemic control during

this period (Eriksson, 2009).

If the mother has hyperglycaemia, the fetus will be exposed to either

sustained or intermittent hyperglycaemia. Before 20 weeks’ an acute

hyperglycaemic stimulus in the human fetus stimulates fetal insulin release only

in diabetic pregnancy. After 20 weeks' gestation, the fetus responds to

hyperglycemia with pancreatic beta-cell hyperplasia and increased insulin levels

(Ericsson et al., 2007).

The fetus may have cardiac arrhythmia due to decreased potassium level

with elevated insulin and glucose levels (De Leon and Stanley, 2007). Chronic

fetal hyperglycemia and hyperinsulinemia increase the fetal basal metabolic rate

and oxygen consumption, leading to a relative hypoxic state. The fetus increases

oxygen-carrying capacity through increased erythropoietin production, and

polycythemia (Georgieff, 2006).

Infants born to mothers with glucose intolerance are at an increased risk

of morbidity and mortality related to the respiratory distress, growth

abnormalities, hyperviscosity secondary to polycythemia, hyperbilirubinemia ,

hypoglycaemia, adverse neurodevelopment outcomes, congenital anomalies,

hypocalcaemia, hypomagnesaemia, and iron abnormalities, cardiovascular

malformations(Alam et al., 2006; Barnes-Powell ,2007).

-Aim of the work:

The aim of this study is to investigate the effect of maternal diabetes on

some hematological and biochemical parameters of their offspring.

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Chapter I Review of Literature

4

-Carbohydrate metabolism

Glucose is the primary energy source of fetoplacental tissues. During

early pregnancy, basal plasma glucose, insulin and hepatic gluconeogenesis are

unchanged. However, during late pregnancy; the mother develops

hypoglycemia, which is especially manifest under fasting conditions, when the

rate of gluconeogenesis from different substrates is enhanced. The development

of maternal hypoglycemia despite the enhanced gluconeogenesis and the

reduced consumption of glucose by maternal tissues in presence of insulin

resistance is due to the high rate of placental transfer of glucose (von Versen-

Hoeynck and Powers, 2007). The use of different substrates for

gluconeogenesis using glycerol rather than other gluconeogenetic substrates is

intense (Hadden and McLaughlin, 2009).

Glucose transfer is carried out by facilitated diffusion according to

concentration-dependent kinetics in presence of a high number of glucose

transporters (GLUTs), particularly GLUT1. GLUT4 is an insulin-responsive

glucose transporter, and is present in placental stroma. GLUT8 is expressed by

the placenta at term, but may be of less importance in early pregnancy

(Limesand et al., 2004). At term, GLUT12 is found predominantly in villous

vessel smooth muscle cells and villous stromal cells (Gude et al., 2005).

The fetus does not synthesize glucose but uses it as its main oxidative

substrate. This causes fetal glycemia to be normally lower than that of its

mother allowing a positive maternal–fetal glucose gradient, which facilitates its

placental transfer (Limesand et al., 2004).

When the fetus is deprived of glucose by placental insufficiency or

maternal hypoglycemia, fetal weight-specific glucose utilization rate is not very

much different from normal rates. This occurs by increasing concentrations,

activity and plasma membrane localization of glucose transporters that increase

insulin signal transduction (Wallace et al., 2005). Chronic hyperglycemia


5

down-regulates glucose tolerance and insulin sensitivity with decreased

expression of skeletal muscle and hepatic Glut 1 and 4 glucose transporters

(Hay, 2006).

-Protein and amino acid metabolism

The accretion of protein is essential for fetal growth and must be

sustained by the active transfer of amino acids from maternal circulation. There

is no evidence that pregnant women store protein during early pregnancy, when

fetal needs are scarce. Therefore, the increased requirements of late pregnancy

must be met by metabolic adjustments that enhance both dietary protein

utilization and nitrogen retention in order to satisfy fetal demands. Protein

metabolism changes gradually throughout gestation, so that nitrogen

conservation for fetal growth achieves full potential during the last quarter of

pregnancy (Hadden and McLaughlin, 2009).

The rate of maternal nitrogen retention between 20 and 40 weeks of

gestation was greater than predicted, due to a reduction in urinary nitrogen

excretion because of decreased urea synthesis. In late pregnancy, nitrogen

balance is improved, with more efficient use of dietary proteins .Although these

alterations that favor nitrogen conservation, pregnancy is associated with

hypoaminoacidemia, which is more evident during fasting and reflects enhanced

placental amino acid uptake (von Versen-Hoeynck and Powers, 2007).

Contrary to glucose, the concentration of most amino acids in fetal

plasma is higher than that found in the mother, and placental transfer of amino

acids is carried out by an active process, using selective transporters and

metabolic energy (Herrera, 2005).


6

-Lipid metabolism

Fat accumulation occurs during the first two trimesters and represents

most of the increase in maternal structures that occurs during pregnancy. It is

the result of both hyperphagia and enhanced lipid synthesis driven by the

enhanced adipose tissue insulin responsiveness .Increments of maternal fat

depots stop in the third trimester, with an increased adipose tissue lipolytic

activity, which is especially manifest under fasting conditions (Toescu et al.,

2004).

The placental transfer of the products of lipolysis released into the

circulation, non-esterified fatty acids (NEFA) and glycerol is low, and their

main destiny is maternal liver where NEFA are converted into acyl-CoA, and

glycerol into glycerol-3-phosphate, which are partially re-esterified for the

synthesis of triacylglycerols. These are released back into the circulation in the

form of very low density lipoprotein (VLDL), as maternal liver production is

enhanced. Whereas glycerol is also used as a preferential substrate for

gluconeogenesis, NEFA are used for β-oxidation, leading to energy production

and ketone body synthesis. Ketone bodies easily cross the placenta .Although

not synthesized by the fetus, in fetal circulation, they reach the same

concentration as in the mother (Herrera, 2005).

There is change in low density lipoprotein (LDL) profile towards smaller

species and the decrease in serum total antioxidant status (TAS) with increased

levels of oxidised low-density lipoprotein (Ox-LDL)( Belo et al., 2004).


7

Fig (2): Relationship of adipose tissue lipolytic activity with lipoprotein

(EFA=essential fatty acid, LCPUFA= long-chain polyunsaturated fatty

acid, CETP=cholesterol ester transfer protein, CE=cholesterol esters,

HDL=high density lipoprotein, LDL=low density lipoprotein, VLDL=very

low density lipoprotein, LPL=lipoprotein lipase, HL=hepatic lipase,

KBs=Ketone Bodies (Herrera, 2005).


8

-Classification of diabetes during pregnancy

The White classification system for diabetes in pregnancy, developed in

1949, is based on age of onset and duration of disease, as well as disease

progression with respect to vascular complications (Hare, 1994).

Class Description

A1 Diet-controlled gestational diabetes

A2 Insulin-treated gestational diabetes

B Onset at age 20 years or older and duration of less than 10 years

C Onset at age 10-19 years or duration of 10-19 years

D Onset before 10 years of age, duration over 20 years,

benign(background) retinopathy, or hypertension (not

preeclampsia)

D1 Onset before age 10 years

D2 Duration over 20 years

D3 Calcification of vessels of the leg (macrovascular disease), formerly

called Class E

D4 Benign retinopathy (microvascular disease)

D4 Hypertension (not preeclampsia)

R Proliferative retinopathy or vitreous hemorrhage

F Nephropathy with over 500 mg/day proteinuria

RF Criteria for both classes R and F

G Many pregnancy failures

H Evidence of arteriosclerotic heart disease

T Prior renal transplantation

Table (1): Priscilla White’s last classification for diabetes in pregnancy

modified by Pedersen (Hare, 1994).

*All classes following Class A require insulin therapy.* Classes R, F, RF, H

and T have no onset/duration criteria but usually occur in long-term diabetes.


9

GESTATIONAL DIABETES MELLITUS

Gestational diabetes mellitus (GDM) is defined as an impairment of

glucose tolerance first recognised during pregnancy. GDM occurs in 2.2%–

8.8% of pregnancies, depending on the ethnic mix of the population and the

criteria used for diagnosis (Theodoraki and, Baldeweg, 2008). The incidence

of GDM is increasing, in parallel to the increase in type 2 diabetes (Ben-

Haroush et al., 2004).

-Mechanisms leading to the development of gestational diabetes

The mechanisms leading to the development of gestational diabetes

mellitus (GDM) are probably related to an exacerbation of the beta-cell

dysfunction in subjects genetically predisposed to beta-cell alterations. Several

mechanisms could be involved, with high progesterone levels may play a

relevant role (Buchanan and Xiang, 2005; Xu et al., 2008).

The hyperlipidemia during pregnancy may decrease the capability of beta

cells to secrete insulin (Kasuga, 2006; Ethier-Chiasson et al., 2008).Although

fatty acids may induce insulin secretion (Rojo-Martinez et al., 2006; Laura

Lee et al., 2009), prolonged high levels of fatty acids may damage the beta cell,

through activation of endoplasmic reticulum(ER) stress (Laybutt et al., 2007;

Lai et al., 2008; Mühlhausler, 2009). In certain genetically predisposed

subjects, the higher supply of glucose and fatty acids to the beta cell may

increase the cell metabolism, with glucose augments lipotoxicity through

amplification of the ER stress response, leading to increased beta-cell apoptosis

and cell death. Beta cells fail to secrete enough insulin in a period of high

insulin requirements together with development of insulin resistance, leads to

the development of GDM( Prentki and Nolan, 2006; Bachar et al., 2009).


10

Hormonal effects in normal and diabetic pregnancy

-Estrogen and progesterone

In early pregnancy, both progesterone and estrogen rise but their effects

on insulin activity are counterbalanced. Progesterone causes insulin resistance

whereas estrogen is protective. In cultured rat adipose tissue, treated with

estrogen, there was no effect on glucose transport, but maximum insulin binding

was increased. However, progesterone decreased both maximum glucose

transport and insulin binding (Waters et al., 2009).

Moreover, estrogens help the adaptation of the islets of Langerhans to the

high glucose stimulated insulin secretion (GSIS) and increase beta-cell mass,

which increase insulin biosynthesis and secretion (Nadal et al., 2009).

-Cortisol

Cortisol levels increase as pregnancy advances and by the end of

pregnancy concentrations are threefold higher than in the non-pregnant state

(Lindsay and Nieman, 2005). Under conditions of high amounts of cortisol,

hepatic glucose production is increased and insulin sensitivity decreased with

development of insulin resistance and beta-cell dysfunction (Bernal-Mizrachi

et al., 2007).

The nuclear receptor peroxisome proliferator-activated receptor -alpha

(PPAR-α) plays an important role in cortisol-induced hepatic insulin resistance

and hyperglycaemia (Bernal-Mizrachi et al., 2007).PPAR-α, is predominantly

expressed in the liver acting as a fatty acid sensor and it is a major regulator of

energy homeostasis by promoting fatty acid oxidation, gluconeogenesis and

ketogenesis (Van Raalte et al., 2004).


11

-Prolactin

During pregnancy, maternal prolactin levels increase 7- to10-fold. The

basal insulin concentration and post-challenge glucose and insulin responses

were greater in women with hyperprolactinemia than in healthy controls.

Prolactin shares in the adaptation to insulin resistance during pregnancy through

increasing beta-cell mass (Amaral et al., 2004, Grattan et al., 2008). This

participation is mediated through its action on prolactin receptors and

phosphatidylinositol 3-kinase and mitogen activated protein kinase (MAPK)

pathways (Huang et al., 2009).

-Human placental lactogen

Human placental lactogen (hPL) levels rise at the beginning of the second

trimester, causing a decrease in phosphorylation of insulin receptor substrate-1

(IRS-1) and profound insulin resistance (Freemark, 2006).

-Leptin

Leptin is a protein, secreted by adipose tissue. It can modulate energy

expenditure by direct action on the hypothalamus. Receptors to leptin are found

in skeletal muscle, liver, pancreas, adipose tissue, uterus and the placenta; this is

responsible for both peripheral and central insulin resistance. Reductions in

leptin concentrations are caused by weight loss, fasting, while leptin

concentrations are increased with weight gain and hyperinsulinemia. Leptin

directly affects whole body insulin sensitivity by regulating the efficiency of

insulin mediated glucose metabolism by skeletal muscle, and by hepatic

regulation of gluconeogenesis. Leptin may also exert an acute inhibitory effect

on insulin secretion (Coll et al., 2007).


12

Leptin levels are significantly higher in pregnancy than in the non-

pregnant state, especially during the second and third trimesters; this is

consistent with changes in maternal fat stores and glucose metabolism. Plasma

leptin was higher in the women with GDM than in the women with normal

glucose tolerance, and higher in both these groups than in the non-pregnant

controls (Henson and Castracane, 2006; Briana and Malamitsi-Puchner,

2009). Umbilical cord leptin concentration was an independent risk factor for

fetal macrosomia in non-diabetic women (Hauguel et al., 2006), in GDM cord

blood leptin levels are significantly higher, and a source other than fetal

adipocytes appears to contribute to this rise (Okasha et al., 2007).

-Adiponectin

Adiponectin is an adipose tissue hormone that facilitates the regulation of

the glucose and lipid metabolism. Adiponectin suppresses the secretion of TNF-

α by adipose tissue, decreases the hepatic glucose production and insulin

resistance by enhancing the beta oxidation of free fatty acids and by decreasing

the intracellular concentrations of triglycerides (Williams et al., 2004).

A cord blood adiponectin level was extremely high in comparison to

serum levels in children and adults and was positively correlated to fetal birth

weights. No correlation was found between cord adiponectin levels and

maternal body mass index, cord leptin, or insulin levels. Serum adiponectin

level was significantly lower in gestational diabetes in comparison with healthy

pregnant both in pregnancy, as well as postpartum women (Ranheim et al.,

2004; Soheilykhah et al., 2009). Significant reduction in adiponectin level was

observed postpartum in GDM (Vitoratos et al., 2008).Mode of delivery didn’t

influence levels of adiponectin and insulin in IDMs (El Sheemy et al., 2008).


13

-Tumour necrosis factor-alpha

Tumour necrosis factor-alpha (TNF-α) is involved in regulation of

glucose and lipid metabolism and the pathogenesis of insulin resistance in

pregnancy, pathogenesis and progression of GDM (Altinova et al., 2007).

There is an increased TNF-α genes expression in adipose tissue of

pregnant women with gestational diabetes (Kuźmicki et al., 2006).

-Adrenomedullin

Placental adrenomedullin is a hypotensive peptide upregulated in diabetic

pregnancy and that it may be important to prevent excessive vasoconstriction of

placental vessels (Sekine et al., 2006).It is involved in the insulin regulatory

system and it may play a role in modifying diabetes in pregnancy. At picomolar

concentrations it directly inhibits insulin secretion from beta-cells (Harmancey

et al., 2007).


14

Maternal Metabolic Changes in Gestational Diabetes Mellitus

-Glucose metabolism alterations in GDM

Because the maternal-fetal transfer of glucose is concentration-dependent,

under conditions of maternal hyperglycemia and normal placental function,

there is increased placental transfer of glucose .Fetal hyperglycemia develops

and secondary to this alteration, hyperinsulinism occurs. The hyperinsulinism

remains in the neonatal period and increases the risk of hypoglycemia once the

umbilical supply of glucose is suddenly arrested after delivery. The newborn

will need frequent monitoring of blood glucose, early feeds and may require the

intravenous administration of glucose (Persson, 2009).

-Amino acid metabolism alterations in GDM

In GDM, there is an increase in a number of essential and nonessential

amino acids in umbilical venous and arterial concentration compared to the

values found in normal pregnancies. The higher plasma levels of fetal amino

acids do not seem to be related to a higher concentration in maternal plasma, as

only ornithine has been shown to increase in plasma from pregnant women with

GDM (Cetin et al., 2005). Second trimester increase in maternal serum

homocysteine has been reported and this suggests that placental amino acid

exchange and/or fetoplacental metabolism is altered in GDM (Guven et al.,

2006).

Among the different amino acid transporters, the expression of system A,

which mediates the transfer of neutral amino acids such as alanine, serine, and

glutamine, is increased in diabetic pregnancies. Specific system for leucine

(system L), have also been shown to be increased in microvillous plasma

membranes isolated from GDM pregnancies with large babies for their

gestational age (Jansson and Powell, 2006).


15

Leucine has been proven to be an effective stimulus for fetal insulin

secretion in human pancreas studied in vitro (Jansson and Powell 2006; Liu et

al., 2008), a rise in glucose concentration is necessary for leucine to stimulate

significant insulin secretion (Kalogeropoulou et al., 2008).

-Lipid metabolism alterations in GDM

Higher levels of triglycerides and cholesterol are pro-oxidant and this

leads to increased LDL oxidation, but this effect may be blunted by higher

levels of vitamin E and estradiol whose levels are increased in pregnancy. A

correlation between LDL oxidation and birth weight, suggesting that conditions

where LDL oxidation is increased, fetal growth may be compromised

(Sánchez-Vera et al., 2005). The small, dense LDL particles are associated

with insulin resistance (Goff et al., 2005; Herrera, 2005), and with a 4-fold

increased risk of GDM (Qiu et al., 2007).

In GDM as in other conditions of insulin resistance and beta-cell

dysfunction, there is an increase in plasma levels of triglycerides and cholesterol

(DiCianni et al., 2005).

The acylation stimulating protein (ASP) is a potent lipogenic adipokine

that correlates with postprandial triglyceride clearance .Maternal

hypertriglyceridemia is associated with increased fetal ASP production, thus

enhancing fetal fat storage independent of maternal glucose variations in non

diabetic women(Saleh et al.,2008).

Chapter

I

16

Review of LLiterature


17

Insulin signalling system in normal pregnancy and in gestational diabetes

mellitus

The mechanisms involved in pregnancy-induced insulin resistance are

related to different factors. There are several hormonal and metabolic alterations

that lead to insulin resistance. These includes hypertriglyceridemia , TNF-alpha,

high levels of progesterone found in the second half of pregnancy, and

decreased adiponectin levels(DiCianni et al., 2005;Vitoratos et al., 2008).

-Insulin Receptor

The action of insulin is triggered when it binds to the insulin receptor

(IR). The IR belongs to the insulin growth factor receptor (IGFR) family, which

has an intrinsic tyrosine kinase (TK) activity. The IR is composed of two alpha

subunits, each linked to a beta subunit and to each other by disulfide bonds;

only the beta subunit has enzymatic TK activity. When insulin binds to the

receptor, the conformational change activates the beta-subunit with

autophosphorylation of cellular substrates. Insulin Receptor Substrate-1 (IRS-

1), a cytosolic protein, binds to the phosphorylated intracellular substrates,

transmitting the insulin signal downstream. A single insulin molecule can

contact both alpha subunits in the insulin receptor dimer during high affinity

binding (Chan et al., 2007).

In GDM, the skeletal muscle contains less IRS-1and significantly less

insulin-stimulated IRS-1 tyrosine phosphorylation, while levels of the IRS-2 are

increased. This suggests that the insulin resistance of GDM may be exerted

through a decrease in the insulin signal cascade at the level of the IRS. The

increased IRS-2 level may be a compensation for the reduced IRS-1 level (Qu

et al.,2007).Post receptor defects are present in the insulin signalling pathway in


18

placenta of women with pregnancies complicated by diabetes and obesity

(Colomiere et al.,2009).

The insulin resistance of normal pregnancy is multifactorial, involving

reduced ability of insulin to phosphorylate the IR, decreased expression of IRS-

1, and increased levels of the p85α subunit of PI 3-kinase. IRS-1 is further

decreased in most GDM subjects compared with obese pregnant women at term.

However, in GDM, there are reciprocal and inverse changes in the degree of

serine and tyrosine phosphorylation of IR and IRS-1 that further inhibit

signaling, leading to substantially reduced GLUT4 translocation and decreased

glucose uptake beyond that of normal pregnancy. Women with a history of

GDM have evidence of subclinical inflammation and there is evidence for

increased TNF-α. Adiponectin, a key insulin-sensitizing hormone produced by

adipose tissue, is significantly lower in women with a history of GDM and

declines with advancing gestation, suggesting it could be involved in the

transition to insulin resistance. In adipose tissue, the lipogenic transcription

factor PPAR-γ declines in obese women during pregnancy and may shift genes

in metabolic pathways to favor increased lipolysis, thus accelerating adipose

tissue insulin resistance and the switch from lipid storage to lipolysis. This

transition to insulin resistance contributes to greater postprandial increases in

FFAs and increased hepatic glucose production and results in greater fuel

availability to the fetus of women with GDM. Thus, like a perfect storm,

subclinical inflammation, placental hormones, reduced adiponectin secretion,

and excess lipolysis conspire to cause severe insulin resistance in liver, muscle,

and adipose tissue in women with GDM (Barbour et al., 2007).

Chapter

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20

(Stefanović and Antić, 2004). PC-1 overexpression impairs insulin stimulation

of insulin receptor (IR) activation and downstream signalling. PC-1 binds to the

connecting domain of the IRα -subunit that is located in residues 485–599. The

connecting domain transmits insulin binding in α -subunit to activation of

tyrosine kinase activation in the β-subunit. When PC-1 is overexpressed, it

inhibits insulin-induced IR β-subunit tyrosine kinase activity. In addition, a

polymorphism of PC-1 (K121Q) in various ethnic populations is closely

associated with insulin resistance. The product of this polymorphism has a 2- to

3-fold increased binding affinity for the IR and is more potent than the wild type

PC-1 K in inhibiting the IR (Ira et al., 2008).

-The peroxisome proliferator-activated receptors (PPARs)

The peroxisome proliferator-activated receptors (PPARs) are a family of

fatty acid sensors, which transduce stimuli from fatty acids into changes in gene

expression. PPARγ is highly expressed in adipose tissue and plays an essential

role in the regulation of insulin sensitivity. The target genes induced by PPAR

include (among others) adiponectin, lipoprotein lipase, the intracellular fatty

acid binding protein aP2, and the mitochondrial uncoupling protein UCP2

(Qiao et al., 2005). The PPAR-γ2 Pro12Ala polymorphism in patients with

GDM gained significantly more weight during their pregnancy (Tok et al.,

2006).


21

-Risk Factors in development of GDM

1-Genetic Factors

Genetic predisposition to GDM has been suggested since GDM clusters

in families. Also, women with mutations in MODY (Maturity onset diabetes of

the young) genes often present with GDM. In addition, common variants in

several candidate genes (e.g. potassium inwardly rectifying channel subfamily J,

member 11 [KCNJ11], hepatocyte nuclear factor-1alpha [HNF1A] etc.) have

been demonstrated to increase the risk of GDM (Shaat and Groop, 2007).

Mutations in the glucokinase gene occur in no more than 5% of GDM patients

(Okruszko et al., 2007).

Human leukocyte antigen-G (HLA-G) expression that functions to protect

the fetus from immune attack by down-regulating cytotoxic T cell responses to

fetal trophoblast antigens is postulated to protect the islet cells of the pancreatic

tissue also. HLA-G and nuclear factor-κB (NF-κB) interaction is suggested to

be central in the events leading to GDM development (Oztekin, 2007).

2-Immunological Factors

Pregnancy represents a distinct immunologic state; the fetus acts as an

allograft to the mother, needs protection against potential rejection. The final

effect of pregnancy on previously active autoimmune processes is controversial,

and multiple autoimmune disturbances may be manifested during pregnancy

specific to other organs: thyroid, adrenal cortex and gastric mucosa

(Jurczyńska and Zieleniewski, 2004).

Humoral immunoreactivity does not change much during pregnancy, with

the exception of lowered immunoglobulin G concentration at late phase,

probably explained by placental transport. Site-specific suppression, in which


22

maternal immune responses are controlled locally at the maternal- fetal

interface, plays a fundamental role in controlling maternal allogeneic immune

responses (Cody et al., 2007).

Regarding cellular immunity, CD4+ CD25+ T regulatory cells (TReg)

suppress antigen-specific immune responses and are important for allograft

tolerance. Normal pregnancy is associated with an elevation in the number of

TReg cells which may be important in maintaining materno-fetal tolerance

(Somerset et al., 2004).

-Autoimmune gestational diabetes

Some GDM patients depicting humoral autoimmune markers against

pancreatic cells, express several autoantibodies (AA) against various pancreatic

islet cell autoantigens, typically detected in Type 1 diabetes (Ben-Haroush et

al., 2004).

-Islet-cell autoantibodies

Islet cell autoantibodies (AA) include AA to islet cell cytoplasm (ICAs);

to native insulin (IAAs); to glutamic acid decarboxylase (GAD65A)-directed

against the 65 K isoform of glutamic acid decarboxylase and to two tyrosin

phosphatases (insulinoma associated antigens IA-2A and IA-2βA) with a higher

prevalence of ICA than other AAs (Damanhouri et al., 2005).

The titres of the different autoantibodies have been shown to be lower

than in type 1 and pre-type 1 relative. These autoantibodies have also been used

to identify high-risk individuals for the development of the disease, specifically

first-degree relatives of subjects with type 1 DM (Järvela et al., 2006).

There is an increased risk of DM-1 in women with GDM and positivity

for ICA, GADA and with the risk increasing with the number of AAs. The

Chapter

autoim

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24

3-Body Mass Index (BMI)

Maternal prepregnancy BMI is directly associated with the risk of

developing GDM and is a strong predictor for GDM requiring insulin treatment

(Rudra et al., 2007; Stothard et al., 2009).

Obesity causes major changes in maternal intermediary metabolism, and

insulin resistance appears to play a central role (Ginsberg et al., 2006;

Ghiadoni et al., 2008). Insulin receptors and post-receptor defects associated

with obesity may be further exacerbated by pregnancy (Andreasen et al.,

2004).

Inflammation is another possible explanation for the link between

obesity and GDM, a systemic inflammation seems to be involved as indicated

by higher levels of serum C- reactive protein, interleukin-6 (Qiu et al., 2004)

and ferritin (Chen et al., 2006).As adipocytes secrete proinflammatory

cytokines, inflammation is usually associated with obesity. Therefore, the

abundance of adipocytes in obese women could produce excess inflammatory

markers that in turn would lead to the development of GDM (Kriketos et al.,

2004).

4-Maternal Age

The highest risk for GDM is maternal age. In a prospective study the

relative risk for GDM rose by 4% for each year of age after 25(Williams et al.,

2004).

5-Family History Maternal inheritance is stronger in GDM unlike type 1diabetes which is

mostly inherited from the father (Tabák et al., 2009). Women with a sibling

history of diabetes were more likely to have GDM than women with other

family history patterns (Kim et al., 2009).


25

6-Smoking The Increased insulin resistance, hyperinsulinemia and type 2 diabetes

have been linked with cigarette smoking outside of pregnancy in some but not

all studies, but whether cigarette smoking is a risk factor for GDM remains

controversial (England et al.,2004;Wendland et al., 2008).

7-ethnicity Risk of GDM appears to vary among ethnic groups, particularly more

among Asian women, and most markedly among women from South Central

Asia for whom the risk also is rising over time. The more modestly risk is

among Latin American women. The reasons for differences among ethnic

groups include, genetic variation based on geographic origin, lifestyle and

cultural factors in those countries resulting from different religious and dietary

traditions (Savitz et al., 2008).

8-Poor obstetric outcomes History of previous GDM is associated with risk of recurrence with rates

of up to 70% have been reported. GDM recurrence rates are influenced by

maternal health characteristics and past pregnancy history (Bottalico, 2007;

Kwak et al., 2008).

Unexplained multiple miscarriages, stillbirths, or birth defects may be

due to undiscovered GDM. Women who have multiple loss history tend to have

increased rates of GDM (Khatun et al., 2009).

9- Polycystic ovary syndrome (PCOS) The risk of developing GDM in patients with PCOS occurs independent

of obesity (Boomsma et al., 2006; Kashanian et al., 2008).This is consistent


26

with the known association of PCOS and glucose intolerance(Legro et al.,

2005).

10- Hypertension GDM risk increased among women with prehypertension and women

with hypertension during early pregnancy (Hedderson and Ferrara, 2008).

11-Iron supplementation Iron, which is particularly abundant in the placenta, is important in the

production of free radicals. Protective mechanisms against free radical

generation and damage increase throughout pregnancy and protect the fetus,

which, however, is subjected to a degree of oxidative stress. Oxidative stress

peaks by the second trimester of, what appears to be a vulnerable period for

fetal health and gestational progress (Jiang et al., 2004).

Iron supplementation in pregnancy is beneficial for neonatal/maternal

outcomes, but it is associated with glucose impairment and hypertension in

midpregnancy; its potential harmful effects might be carefully debated

regarding its effectiveness (Bo et al., 2009).

Maternal Risks of GDM

Hyperglycemia in GDM is usually mild to affect adversely women’s

health, although there are reports of ketoacidosis (Parker and Conway, 2007)

and retinopathy (Khaldi et al., 2008).

Women with a history of GDM were more likely to have recurrent

diabetes especially if they were obese and waited longer between pregnancies

(Holmes et al., 2010).GDM is associated with a higher risk of pre-eclampsia

and metabolic syndrome (Carr et al., 2006).


27

Screening for GDM

Screening for gestational diabetes should be routine for all pregnancies

(Nicholson et al., 2005).

Screening for gestational diabetes is performed between 24 and 28 weeks

of pregnancy and may be done earlier in the pregnancy if the clinician suspects

that the woman has gestational diabetes because of risk factors such as a history

of previous GDM, obesity or a strong family history of diabetes (Dodd et al.,

2007; Simmons, 2008).

On the day of the screening test, the woman may eat and drink normally.

She will be given 50 grams of glucose, usually in the form of a specially

formulated orange or cola drink; this should be consumed within few minutes.

One hour later, a small sample of blood is drawn to measure the woman's blood

glucose level (Kim et al., 2007).

If the woman's blood glucose is elevated, further testing is needed to

determine with certainty if she has GDM. Clinicians vary in their definition of

elevated blood glucose; most consider a value greater than 126mg/dL to be

"elevated"(according to WHO). The one hour glucose test is a screening test,

meaning that not everyone who has an elevated one hour blood glucose level

will have gestational diabetes. However, if the one hour blood glucose level is

very high ≥200 mg/dL, many clinicians do not perform any further testing

because there is a very good chance that the woman has GDM (Simmons,

2008).


28

Further testing for diagnosis of GDM

The three hour (or two hour, in some locations) oral glucose tolerance test

(GTT) is used to determine with certainty if a woman has GDM. The test is

done by measuring the woman's fasting glucose level, then again one, two, and

three hours after she drinks a glucose 100 grams. A woman is said to have

GDM if her blood glucose values are above the following levels:

Fasting>95 mg/dL, 1-hour >180 mg/dL, 2-hours>155 mg/dL and 3-hours > 140

mg/dl (American Diabetic Association).

The recommended values for the diagnosis of GDM are those in (table 2)

according to Dodd et al., (2007).


29

Recommendation for diagnosis of GDM Plasma glucose level (mg/dl)

ACOG National Diabetes Data Group (USA)

-Fasting glucose

-One-hour post-100-g load

-Two-hour post-100-g load

-Three-hour post-100-g load

105

190

165

145

American Diabetes Association (USA)

-Fasting glucose

-One-hour post-100-g load


-Three-hour post-100-g load

95

180

155

140 WHO 1998

-Fasting glucose


126

180 ADIPS

-Fasting glucose


99

144

NZSSD

-Fasting glucose


99

162

ACOG=American College of Obstetricians and Gynecologists; ADIPS= Australian Diabetes in Pregnancy Society, NZSSD= New Zealand Society for the Study of Diabetes; WHO= World Health Organization

Table (2): Recommended values for the diagnosis of gestational diabetes

(Dodd et al., 2007).


30

Management of GDM

-Blood glucose monitoring

Women with GDM should perform home blood glucose monitoring.

Blood glucose levels are monitored in fasting state and 1–2 hours after meals.

Treatment to post-prandial targets results in superior outcomes compared to pre-

prandial targets (Jovanovic and Pettitt, 2007).

-Dietary therapy

All women should receive individualized counselling to provide

adequate calories and nutrients to meet the needs of pregnancy and consistent

with the blood glucose goals (fasting ≤105 mg/dl, 1 hr ≤155 mg/dl, and 2 hrs

≤130 mg/dl). For obese women, a 30%–33% calorie restriction to

approximately 25 kcal/kg body weight per day is recommended. Carbohydrate

should be restricted to 35%–40% of calories. Studies in which women with

GDM had less carbohydrate diet, with low glycemic index ( The glycemic index

or GI describes the ranking of carbohydrates according to their effect on our

blood glucose levels), had lower postprandial glucose levels, less likely to

require insulin, and had a lower incidence of large for gestational age newborn

(Moses et al., 2006).

-Physical activity

Women with GDM should maintain a sensible level of light and moderate

intensity physical activity, like walking for 20–30 minutes each day, and

attendance at antenatal exercise classes until the latter stages of the pregnancy.

Physical activity lowers fasting glucose levels, glucose responses to a glucose

challenge, and glycosylated hemoglobin (HbA1c), postprandial glucose levels,

and a delay in the need of insulin (Brankston et al.,2004).


31

-Insulin therapy

When treatment targets are not achieved by dietary means, then insulin is

required. Fast-acting (regular) insulin and intermediate-acting (isophane) insulin

have been the preferred insulins for the treatment of GDM. The rapid acting

insulin analogs lispro and aspart are also safe in pregnancy, and indeed, they are

commonly used (Aydin et al., 2008).

Chapter

mortal

develo

infants

and m

glucos

diabete

diabete

Figure

Newbo

II

Diabetes

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32

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Chapter II Review of Literature

33

Problems found in Infants of Diabetic Mothers

-Altered Fetal Growth

*Macrosomia

This refers to fetal growth beyond a specific weight regardless of

gestational age, usually above 4,000 g or 4,500 g. With the development of a

national reference for fetal growth based on data from over 3.8 million births,

clinicians can distinguish between macrosomia and large-for-gestational-age

(LGA) which refers to fetal growth above the 90th percentile for a given

gestational age. Women with gestational diabetes, the mildest form of

carbohydrate intolerance, have as great an incidence of macrosomia as women

with pre-existing diabetes (Zhang et al., 2008).

Macrosomia in IDM results primarily from increased adiposity because

IDM have both adipocytes hyperplasia and adipocytes hypertrophy. IDM also

have excess non fatty tissue. The liver and heart often are enlarged, and skeletal

muscle increased. Much of this excess tissue is located in the shoulders and

intrascapular area. Because IDM have normal brain growth, this results in a

disproportion between head and shoulder size and greatly increases the risk of

shoulder dystocia (Maticot-Baptista et al., 2007).

Because insulin has both mitogenic and anabolic effects in the fetus, the

fetal hyperinsulinemic state is central to the development of macrosomia. The

effect of insulin probably is mediated to some extent through stimulation of

insulin-like growth factors. Hyperinsulinemia "primes" various tissues to the

mitogenic influence of growth factors (Thureen et al., 2006). The excess fat in

IDM develops during the third trimester; IDM delivered before 30 weeks of

gestation rarely are LGA (Grissa et al., 2007).


34

Fluctuations in glucose levels rather than basal levels are probably more

determinant in fetal growth acceleration. In diabetic pregnancies, only overall

daily glucose values < or =95 mg/dl throughout the second and third trimesters

can avoid alterations in fetal growth. These fetuses cannot be identified by a

single ultrasound examination at 29-34 weeks' gestation(Ben-Haroush et

al.,2007).Combination of sonographic estimates with clinical and demographic

variables does not improve the prediction of macrosomia at delivery in

comparison with a routine ultrasound scan within a week before delivery

(Balsyte et al., 2009).

The macrosomic offspring born to diabetic mothers are prone to the

development of glucose intolerance and obesity as a function of age. It seems

that in utero programming during diabetic pregnancy creates a "metabolic

memory" which is responsible for the development of obesity in macrosomic

offspring (Khan et al., 2007).

Macrosomia is responsible for the great risk of birth trauma, meconium

aspiration syndrome, persistent pulmonary hypertension, and high incidence of

cesarean section delivery of IDM (Dickstein et al., 2008).

*Intrauterine growth retardation

This refers to fetal growth less than or equal to the 10th percentile for

gestational age. Growth retardation in diabetic pregnancy may result from

alterations in maternal metabolic fuel availability during early gestation and it

has been attributed to maternal vascular disease, causing uteroplacental

insufficiency (Irfan et al., 2004; Howarth et al., 2007; Haeri et al., 2008).


35

-Hyperviscosity

IDM have a 10% to 20% risk of being polycythemic and developing

neonatal hyperviscosity syndrome. Several factors are responsible for this; the

hematocrit of umbilical-cord blood at birth tends to be elevated; as a result of

increased erythropoiesis. Also hyperinsulinemia results in decrease in protein C

and increases in fibrinogen factors V, VII, and XI. The increased incidence of

renal vein thrombosis reported in IDM may be related to hyperviscosity,

although this disorder does occur in IDM with normal hematocrit(Sarkar et al.,

2005).

-Cardiomyopathy

IDM are at increased risk for various cardiomyopathies. Many have

thickening of the interventricular septum and left or right ventricular wall. The

increased cardiac muscle mass results from the fetal hyperinsulinemic state.

Most of these infants are asymptomatic, and the thickening is detected by

electrocardiogram or echocardiogram. These abnormalities generally regress

over 3 to 6 months, and the condition appears to have no permanent effect on

the myocardium (Abu-Sulaiman and Subaih, 2004).

In a small fraction of infants, outflow obstruction severe enough to cause

left ventricular failure; these infants have suffered intrapartum asphyxia and are

hypoglycemic and hypocalcemic. Pregnancies of both type 1 and 2 diabetes

carry an increased risk for foetal development of pathologic ventricular

hypertrophy (PVH) compared with those with GDM (Ullmo et al., 2007).

-Congenital Abnormalities

Poor control of maternal diabetes during the first trimester, a critical

period of organogenesis, has been proposed as the mechanism for the increased


36

incidence of malformations. In his 1980 Banting Lecture, the late Norbert

Freinkel articulated the concept of “fuel-mediated teratogenesis” and pointed

out the temporal relationships between exposure to a metabolic insult and the

type of adverse effects that might ensue (Metzger, 2007). Diabetes-induced

fetal abnormalities are accompanied by some metabolic disturbances including

elevated superoxide dismutase (SOD) activity, reduced levels of myoinositol

and arachidonic acid and inhibition of the pentose phosphate shunt

pathway(Abu Sief et al., 2007;Dheen et al.,2009).

Although many abnormalities occur in IDMs, ventricular septal defects,

transposition of the great arteries, and spinal agenesis-caudal regression

syndrome occur with particular frequency. Neural tube defects, gastrointestinal

atresia, and urinary tract malformations also are relatively common (Kumar et

al., 2007; Kaissi et al., 2008).

A transient anomaly unique to IDM is known as the neonatal small left

colon, microcolon, or lazy colon syndrome. This condition presents as

gastrointestinal obstruction, and barium contrast studies suggest congenital

aganglionic megacolon.Unlike infants with Hirschsprung disease where

aganglionosis begins with the anus, which is always involved, and continues

proximally for a variable distance; these infants with small left colon syndrome

have normal innervation of the bowel and ultimately have normal bowel

function (Chen, 2005).

-Postnatal Problems

IDM are at increased risk for development of obesity and altered glucose

metabolism (impaired fasting glucose, IGT, diabetes) in the offspring in later

life, compared to infants of mothers with normal carbohydrate metabolism

(Figure 7)(Metzger, 2007). In utero hyperinsulinism may be responsible for

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38

Gestational diabetes hinders expressive language in offspring into middle

childhood. Genes are strongly associated with the risk of delays in infants of

diabetic mothers. Genetic modeling revealed that additive genes moderate the

effect of GD on expressive language: protection or vulnerability genes are thus

strongly associated with IDMs’ expressive language skills. However, what these

genes are or do remains speculative. (Dionne et al., 2008).

Children and adults who were IDM have an increased incidence of

diabetes mellitus. It is possible that the altered metabolic state of the diabetic

pregnancy may modulate the genetic predisposition. The insulin secretory

defect could be related to low parasympathetic tone (Nold and Georgieff,

2004).

-Respiratory Distress Syndrome (RDS)

IDM are at increased risk of developing RDS. The increased risk of RDS

in poorly regulated diabetic women is due in great part to fetal hyperinsulinism,

which adversely affects fetal lung maturation by inhibiting the development of

enzymes necessary for the synthesis of the phospholipid components of

surfactant. Polycythemia is another factor with associated stagnant hypoxia. As

macrosomia is common and may cause birth injuries that may be result in

central form of respiratory distress (Barnes-Powell, 2007).

*Evaluation of the newborn's blood gas status

The transition from foetal to neonatal life is a dramatic one; it demands

considerable and effective physiological alteration in the newborn to ensure

survival. Simultaneously cardio-respiratory adjustments are initiated and

breathing maintained on a continuous basis. The basic movements in the human

foetus being about 8 weeks after conception, and by 12 weeks some of these

foetal breathing movements have attained a pattern similar to respiration. At


39

birth also, the regulatory neural network responsible for respiratory control is

capable of generating robust rhythm-driven ventilation that can adjust to

homeostatic needs. The so far unexplained conversion from episodic to

continuous breathing with the onset of birth remains one of the mysteries of

perinatal medicine. The initiation and establishment of breathing is of

paramount importance to the survival of the newborn (Arikawe and Iyawe,

2006).

Blood gas measurements are as important for ill newborn infants as for

other critically ill patients, but unique challenges are provided by rapidly

changing physiology, difficult access to arterial and mixed venous sampling

sites, and small blood volumes. Normal values for arterial blood gases are very

dependent on postnatal age. Values of PaO2 and SaO2 may also be lower in

premature infants, caused by reduced lung function (Blickstein and Green,

2007).

-Assessment of oxygenation

Blood gas measurements and noninvasive estimations provide important

information about oxygenation. Oxygen delivery (DO2) to tissues is the product

of cardiac output (c.o.) and blood oxygen content (CaO2), DO2 = c.o. x CaO2.

Ignoring the negligible oxygen dissolved in plasma, the equation can be

expanded to DO2 = (HR x SV) x (SaO2 x 1.34 x Hgb), where HR = heart rate,

SV = stroke volume, SaO2 = hemoglobin saturation, and Hb = hemoglobin

content. Insufficient oxygen delivery to tissues, hypoxia, can therefore be

caused by cardiac failure (decreased HR and (or) SV leading to decreased c.o.),

or by low hemoglobin (anemia) or low Sao2 (hypoxemia) leading to low

CaO2.When insufficient oxygen is provided to tissues, hypoxia leads to

metabolic acidosis (Brouillette and Waxman,1997). A sensor for combined

assessment of pulse oximetry oxygen saturation (Spo2) and transcutaneous


40

measurement of Pco2 (Ptcco2) has been introduced in a single ear sensor

(Bernet-Buettiker et al., 2005).

The general goals of oxygen therapy in the neonate are to maintain

adequate PaO2 and SaO2, and to minimize cardiac work and the work of

breathing .Optimal oxygenation will result in different PaO2/SaO2 goals for

different types of neonatal patients. Most commonly, premature infants in

respiratory failure should have PaO2 values between 50–80 mm Hg; these goals

minimize the chances of blindness caused by retinopathy of prematurity and

lower the inspired O2 and airway pressure requirements that, if higher, might

increase the risk of bronchopulmonary dysplasia (Walsh et al., 2009).

-Assessment of alveolar ventilation

Arterial blood gas determinations of PCO2 provide the most accurate

determinations of the adequacy of alveolar ventilation. The PaCO2

concentration reflects the balance between metabolic production of CO2 and

excretion by ventilation. There is acceptable range for PaCO2 for a given

patient. Although the normal range of PaCO2 after the first hours of life can be

considered (35–45 mm Hg), desirable CO2 values for a specific situation may

be higher or lower (Sankar et al., 2008).

-Assessment of acid–base status

Blood gases provide essential information on acid–base status both in

critically ill neonates and in chronically or less severely ill patients. One can

approach the analysis of simple acid–base disorders by answering three

questions. First, is the condition one of acidosis or alkalosis (is the pH less than

or greater than 7.4)? Second, is the primary cause metabolic (is bicarbonate high

or low) or respiratory (is PCO2 high or low)? Third, is the compensation

appropriate? (Victory et al., 2004).


41

Glucose homeostasis in newborn infants

The neonate's ability to maintain glucose homeostasis is less well

developed than the older child or adult because it is in a metabolic transition

period. The abrupt switch from intrauterine life, in which glucose and metabolic

fuels are provided in a well-regulated manner, to a situation in which meals are

intermittent and which necessitates regulation of exogenous glucose and

production of endogenous glucose. As the capability to perform these functions

continues to develop in the neonate, clinical disorders that can afflict the

neonate may perturb this balance, resulting in hypoglycemia or hyperglycemia

(Milcic, 2008).

-Glucose Producing and Glucose Regulatory Capabilities in the

Fetus

The development of glucose production and regulatory capabilities in the fetus

involves the following:

-Glycogen

As the third trimester progresses, fat deposition and hepatic glycogen

storage increase. The human fetus can synthesize and mobilize glycogen and

respond to the signals that regulate these processes as early as the ninth week of

gestation. However, only minute quantities of hepatic glycogen are present in

early gestation as the great bulk of hepatic glycogen accumulates during the

third trimester .Several types of infants are at risk for neonatal hypoglycemia as

a result of limited hepatic glycogen stores. Infants delivered prematurely have

an abbreviated or no third trimester and thus have limited glycogen stores

(Hume et al., 2005).


42

Fetuses that are growth-retarded on the basis of limited metabolic fuel

availability and diminished gaseous exchange (i.e., uteroplacental insufficiency)

will use these fuels for growth and not for glycogen synthesis. Perinatal stress

causes neonatal hypoglycemia in part because of catecholamine-stimulated

mobilization of hepatic glycogen stores (Hay, 2006).

-Gluconeogenesis

The fetus can carry out gluconeogenesis to a limited degree, although it is

likely that under normal circumstances it does not need to call on this function.

The four key gluconeogenic enzymes are present in fetal liver by 2 to 3 months

of gestation. The activities of these enzymes increase throughout gestation and

the neonatal period. Thus, all appropriately grown newborns, including the very

premature, have some degree of gluconeogenic capability (Beardsall and

Dunger, 2007).

-Endocrine Regulation

Newborn infants increase insulin and limit glucagon secretion sluggishly

in response to glucose challenge; these responses become adult-like between the

first and second weeks of life. Insulin and glucagon, important hormones for

regulating glucose, can be measured in fetal plasma as early as 12 weeks of

gestation .Although plasma concentrations of these hormones are low; the

relative content of these hormones in the fetal pancreas is quite high. Both

premature and term infants have limited secretory capacity to secrete these

hormones in response to a glucose challenge. Amino acids have a greater effect

in stimulating insulin and limiting glucagon secretion than glucose in the fetus

(Tammaro, 2007).

Insulin may be more important for enhancing growth than for regulating

metabolic fuels during fetal life. Excessive insulin secretion during fetal life


43

resulting from such conditions as IDMs causes the disproportionate growth of

insulin-sensitive tissues, and macrosomia. A lack of insulin, as in infants with

transient neonatal diabetes mellitus, always is accompanied by fetal growth

retardation (Coelho et al., 2007).

Glucagon or a critical glucagon/insulin ratio is important for inducing

gluconeogenic enzymes both vitro and in vivo. Plasma glucagon concentrations

increase progressively during fetal life, and this is associated with a concomitant

increase in gluconeogenic enzyme activity. At birth, plasma glucagon

concentrations surge, coinciding with the rapid postnatal increase in

gluconeogenic activity. However; insulin may modulate glucagon's effect

because it can inhibit gluconeogenic enzyme induction. Thus, a balance

between these two hormones controls gluconeogenic enzyme induction during

perinatal life (Hume et al., 2005).

Adrenergic mechanisms can stimulate hepatic glycogenolysis during fetal

life, much as in the adult. As labor progresses, fetal sympathoadrenal activity

increases, resulting in an increase in circulating catecholamine levels. Cord

clamping triggers an increase in glucagon secretion, as plasma glucose

concentrations drop with cord clamping, insulin secretion slowly decreases.

These adjustments, particularly the remarkable increase in catecholamine

secretion, stimulate glycogenolysis and gluconeogenesis in the neonate

(Jackson et al., 2004).

Fetal glucose metabolism depends on additive effects of fetal plasma

glucose and insulin. Glucose-stimulated insulin secretion increases over

gestation, is down-regulated by constant hyperglycemia, but enhanced by

pulsatile hyperglycemia. Insulin production is diminished in fetuses with

intrauterine growth restriction (IUGR) by inhibition of pancreatic β-cell

replication, but not by mechanisms that regulate insulin production or secretion,


44

while the opposite occurs with hypoglycemia alone, despite its common

occurrence in IUGR. Chronic hyperglycemia down-regulates glucose tolerance

and insulin sensitivity with decreased expression of skeletal muscle and hepatic

Glut 1 and 4 glucose transporters, while chronic hypoglycemia up-regulates

these transporters(Hay,2006).

Neonatal Glucose Requirements

A normal plasma glucose concentration is interpreted to mean that

glucose supply to the brain and other organs is adequate for ongoing metabolic

needs. Glucose turnover represents the rate of production of glucose by the liver

and other organs and the simultaneous use or uptake of glucose by the brain and

other organs. Turnover is usually expressed as milligrams of glucose per

kilogram of body weight per minute .In general, plasma glucose concentrations

roughly correlate with glucose turnover. Diminished plasma glucose

concentrations suggest that glucose production is limited or that glucose use is

increased. Elevated plasma glucose concentrations suggest that either

production is excessive or, more likely, organ uptake and use are diminished.

These are the dynamic physiologic conditions that define hypoglycemia and

hyperglycemia (Kapoor et al., 2009).

Neonatal Hypoglycaemia

The incidence of hypoglycaemia varies with the category of fetal growth

and the nursery feeding protocols. Early feeding decreases the incidence,

whereas prematurity, hypothermia, hypoxia, maternal diabetes, maternal

glucose infusion in labor, and intrauterine growth restriction (IUGR) increase

the incidence of hypoglycemia. Serum glucose levels decline after birth until 1–

3 hr of age, when levels spontaneously increase in normal infants (Uchigata,

2006).


45

Hypoglycaemia in the newborn, if not corrected, may lead to brain

damage and other perinatal risk factors, such as hypoxia, neonatal seizure that

would exacerbate hypoglycaemic brain injuries (Kapoor et al., 2009).

The clinical manifestations of inadequate glucose provision to the

neonatal brain range from no symptoms to lethargy or mild tremors to frank

convulsions. The issue of potential long-term sequelae is complicated by the

fact that hypoglycaemia often occurs with coexisting conditions that also can

cause brain damage .Prolonged hypoglycaemia with a greater risk of brain

damage than brief hypoglycaemia, and the extent of damage is closely

correlated to the presence of seizure-like activity (Bree et al., 2009).

A variety of blood and plasma glucose concentration values based on

screening of neonates or clinical experience have been recommended as values

defining hypoglycaemia. All of these are somewhat arbitrary because they

cannot be correlated directly with glucose use rate or severity of symptoms.

Because plasma or blood glucose concentrations only roughly reflect glucose

turnover, a plasma glucose concentration less than 40 mg/dL is used to define

hypoglycaemia (Montassir et al., 2008).

Diagnosis and Treatment of Hypoglycaemia

Asymptomatic hypoglycemia: This diagnosis is made when the blood

glucose level is below the operational threshold (to be confirmed by laboratory

estimation) in the absence of clinical signs. Symptomatic hypoglycemia: This

diagnosis should be made if the criteria according to Whipple’s Triad are

satisfied: (i) Presence of signs attributable to hypoglycemia; (ii) Low blood

glucose documented by accurate, sensitive and precise methods and (iii)

Resolution of clinical signs within minutes to hours once the blood glucose

level is normalized.


46

All infants at risk for development of hypoglycaemia should undergo

frequent plasma glucose determinations during the first 4 hours of life and then

at 4-hour intervals until the risk period has passed. If an infant is feeding, blood

sampling should be done before feeding. For IDM the screening should

continue for at least 24hours (Montassir et al., 2008).

Infants who have borderline asymptomatic hypoglycaemia, who do not

have respiratory distress syndrome (RDS) or other serious disorders, and who

are capable of enteral feeding may receive either 5% dextrose solution or

formula as their initial treatment. Intravenous administration of glucose in a

quantity sufficient to meet tissue requirements is the treatment of choice for

hypoglycaemia. The administration of 10% or 15% dextrose solution at 5 to 10

mL/kg body weight, followed by a continuous infusion at 5 to 6 mg/kg body

weight/minute, will increase plasma glucose concentrations to 40 mg/dL or

greater and acutely meet tissue requirements. The maintenance rates may

require adjustment depending on the etiology of hypoglycaemia (Stanley,

2006).

Glucagon and epinephrine increase glucose production. Because both

mobilize hepatic glycogen stores, their efficacy in treating hypoglycaemia is

variable, particularly in infants with limited hepatic stores. The numerous

cardiovascular effects of epinephrine also limit its usefulness in infants. Infants

who are hypoglycaemic for prolonged periods as a result of an inability to

produce glucose can be treated with corticosteroids (hydrocortisone 5

mg/kg/day every 12 hours; prednisone 2 mg/kg/day orally). Steroids exert some

of their effects by inducing gluconeogenic enzyme activity (Pearson, 2008).


47

Calcium Homeostasis in newborn infants

Calcium (Ca) is the most abundant mineral in the body and, together with

phosphorus (P) form the major inorganic constituent of bone. The maintenance

of Ca homeostasis requires a complex interaction of hormonal and non

hormonal factors; adequate functioning of various body systems, particularly

the renal, gastrointestinal, and skeletal systems; At all ages, the total body

content of Ca and P is about 99% and 60%, respectively(Hsu and

Levine,2004).

The mechanisms to maintain mineral homeostasis in neonates are the

same as for children and adults. However, the newborn infant has a number of

unique challenges to maintain mineral homeostasis during adaptation to

extrauterine life and to continue a rapid rate of growth. These include an abrupt

discontinuation of the high rate of intrauterine accretion of Ca (approximately

120 mg/kg/day) There may be diminished end-organ responsiveness to

hormonal regulation of mineral homeostasis, although the functional capacity of

the gut and kidney improves rapidly within days after birth. The effects of these

tissues are exaggerated in infants with heritable disorders of mineral

metabolism, such as extracellular calcium-sensing receptor (CaR) mutations

(Egbuna and Brown, 2008), and in infants who have experienced adverse

antenatal events such as maternal diabetes (Lapillonne et al., 2008).

Circulating Concentration

Serum Ca occurs in three forms: approximately 40% is bound, mainly to

albumin; approximately 10% is chelated and complexed to small molecules

such as bicarbonate, phosphate, or citrate; and approximately 50% is ionized.

Complexed and ionized Ca (iCa) is ultrafiltrable. Total Ca concentrations (tCa)

in cord sera increase with increasing gestational age. Serum tCa reaches a nadir


48

during the first 2 days after birth; thereafter, concentrations increase and

stabilize at a level generally above 80mg/L (Hsu and Levine, 2004).

Physiological Control

Calciotropic hormones, including parathyroid hormone (PTH), 1, 25

dihydroxyvitamin D (1, 25(OH) 2 D), and possibly calcitonin (CT), appear to

maintain Ca homeostasis by intermodulation of their physiologic effects on each

other and on the classic target organs: kidney, intestine, and bone (Ramasamy,

2006).

-Parathyroid Hormone (PTH)

PTH concentrations in cord blood are low and do not correlate with PTH

concentrations in maternal sera. Serum PTH concentrations increase postnatally

coincidentally with the fall in serum Ca in both term and preterm infants. The

rise in serum PTH is greater for preterm infants with hypocalcemia compared to

term infants reflecting appropriate PTH response (Lambers et al., 2006).

PTH affects on end-organ systems through its binding to specific

receptors. The type 1 PTH/PTHrP receptor has been identified in bone,

cartilage, kidney, intestine, aorta, urinary bladder, adrenal gland, brain, and

skeletal muscle. It binds equally to PTH and PTHrP. Parathyroid hormone

(PTH) and PTH-related protein activate the same receptor but can produce

divergent effects. Another PTH receptor (type 2) responds only to PTH,

although its main endogenous ligand appears to be a 39-amino-acid peptide,

hypothalamic tubular infundibular peptide. It has been found in the brain,

pancreas, and intestines (Robert et al., 2005).

The strongest and best-characterized second messenger signalling

pathway is the PTH-stimulated coupling of the type 1 PTH receptor to the


49

stimulating G protein (Gs) however, coupling of the type 1 PTH receptor to the

Gq class protein activates phospholipase C, which generates inositol

triphosphate (IP3) and diacylglycerol (DAG). These second messengers in turn

lead to stimulation of protein kinases A and C and Ca transport channels and

result in a variety of hormone-specific tissue responses (Murray et al., 2005).

PTHrP stimulates Ca ATPase in the human syncytiotrophoblast basal

plasma membrane (BM) vesicles by activating the IP (3)-DAG-PKC pathway,

that PTHrP is important in maintaining the calcium concentration gradient

across the placental barrier in the human (Rosenblatt, 2009).

PTH acts synergistically with 1, 25(OH) 2D and is the most important

regulator of extracellular Ca concentration. PTH acts directly on bone and

kidney, and indirectly on intestine. Immediate control of blood Ca is due to

PTH-induced mobilization of Ca from bone and increased renal distal tubular

reabsorption of Ca (D’Amour et al., 2006).

There is a sigmoidal type of PTH secretion in response to decreased

serum Ca, which is most pronounced when serum Ca is in the mildly

hypocalcemic range. PTH secretion is 50% of maximal at a serum iCa of about

4 mg/dL; this is considered the calcium set point for PTH secretion (Chen and

Goodman, 2004).

-Vitamin D

Vitamin D can be obtained from diet or synthesized endogenously. It

must undergo several metabolic transformations primarily in the liver and

kidney to form the physiologically most important metabolite, 1, 25(OH)2D,

which functions as a hormone in the maintenance of mineral homeostasis. Like

other steroid hormones, 1, 25 (OH) 2D functions is mediated primarily through

modulation of the cellular genome by binding to a specific nuclear receptors,


50

vitamin D receptor, a 424-amino-acid phosphoprotein for which the x-ray

crystallographic structure has been determined (Heaney, 2005).

The genomic action of 1,25(OH)2D can be preceded by more rapid non

genomic actions that occur in minutes and involve membrane-associated events

such as increased Ca transport, and PKC and mitogen-activated protein kinase

activation. This non genomic rapid increase in cytosolic Ca within seconds

occurs in various cell types from the intestine and parathyroid, osteoblasts,

myocytes, and leukemic cells. The wide distribution of the vitamin D receptor

provides a number of clinical targets for vitamin D and its analogs. The wide

distribution of CYP27B1, the enzyme required to convert circulating 25OHD to

1, 25(OH) 2D enables a number of cells to make their own 1, 25(OH) 2D3 if

circulating 25OHD levels are maintained (Bikle, 2007).

In humans, the cord-serum vitamin D concentration is very low or

undetectable; the 25-OHD concentration is directly correlated with, but is lower

than, maternal values, consistent with placental crossover of this metabolite; and

1, 25(OH)2D concentrations also are lower than maternal values, but there is no

agreement on the maternofetal relationship of this and other dihydroxylated

vitamin D metabolites .However, the placenta, like the kidney, produces 1,

25(OH)2D, making it difficult to ascertain just how much fetal 1, 25(OH)2D

results from placental crossover versus placental synthesis(Belkacemi et al.,

2005).

There is a positive correlation between maternal vitamin D status during

pregnancy and the development of hypocalcaemia (Camadoo et al.,

2007).Maternal vitamin D deficiency in early pregnancy is associated with an

elevated risk for GDM(Zhang et al., 2008).


51

-Calcitonin (CT)

CT function is mediated by binding to receptors linked to G proteins,

members of the GPCR superfamily; CT receptors (CTR) have been identified in

the central nervous system, testes, skeletal muscle, lymphocytes, and placenta.

Secretion of CT is stimulated by an increase in serum Ca and Mg concentrations

and by gastrin, glucagon, and cholecystokinin, glucocorticoid, norepinephrine,

and calcitonin gene related peptide (CGRP); secretion is suppressed by

hypocalcemia, propranolol, somatostatin, and vitamin D (Jain et al., 2008).

Hypocalcemia

Neonatal hypocalcaemia is defined as a serum tCa concentration of less

than 8 mg/dL in term infants and 7 mg/dL in preterm infants with iCa below 4.0

to 4.4 mg/dL, depending on the particular ion-selective electrode used (Cooper

and Gittoes 2008).Clinically, there are two peaks in the occurrence of neonatal

hypocalcaemia. An early form typically occurs during the first few days after

birth, with the lowest concentrations of serum Ca being reached at 24 to 48

hours of age and late neonatal hypocalcaemia that occurs toward the end of the

first week. Many neonates, particularly those with genetic defects in Ca

metabolism, may be hypocalcemic, but remain asymptomatic and undetected

during the early neonatal period. Serum Ca values are lower in ELBW infants

(Altirkawi and Rozycki, 2008).

Hypocalcemia is not uncommon in neonates receiving gentamicin

therapy, and it may occur more frequently in boys and late-preterm infants, so

monitoring of serum Ca levels should be considered when gentamicin is given >

or = 4 days (Chiruvolu et al., 2008).


52

Pathophysiology of Hypocalcaemia:

In the neonate, hypocalcaemia frequently occurs in the presence of rising

concentrations of PTH in the circulation. This represents either a relative

inadequate response of the parathyroid gland or end-organ resistance to PTH.

Resistance to pharmacologic doses of 1, 25(OH)2D, demonstrated in vitro and in

vivo in infants, may also contribute to hypocalcaemia. Serum CT concentrations

continue to increase after birth in neonates of normal and diabetic pregnancies

(Jain et al., 2008).

Complications of hypocalcaemia

Acute complications are associated with clinical manifestations, including

seizure, apnea, cyanosis and hypoxia, bradycardia, and hypotension. Therapy-

related complications, such as cardiac arrhythmia, arterial spasm, tissue

necrosis, and extravasation of Ca solution, can be avoided by continuous

electrocardiogram monitoring during Ca infusion, avoiding infusion of Ca into

the arterial line, and checking for venous patency before Ca infusion. There is

also a risk for metastatic calcification from aggressive Ca treatment in the

presence of hyperphosphatemia (Cooper and Gittoes 2008).


53

Blood Picture and IDMs

Fetal Erythropoiesis

Early hematopoietic cells originate in the yolk sac. By the eighth week of

gestation, more definitive fetal erythropoiesis is taking place in the liver. The

liver remains the primary site of erythroid production throughout the early fetal

period. By 6 months of gestation, the bone marrow becomes the principal site of

erythroid cell development. Later during gestation, a switch occurs in the type

of haemoglobin being formed, with adult haemoglobin (HbA) re-placing fetal

haemoglobin (HbF). The site of production of erythropoietin (EPO) switches

from the less sensitive hepatic to the more sensitive renal site

(Stamatoyannopoulos, 2005).

The major difference between fetal and adult erythropoiesis is in the

response to EPO. Erythropoiesis is controlled by a feedback loop involving

EPO. A decrease in erythrocyte mass is reflected by an increase in EPO, which

drives erythropoiesis to increase erythrocyte mass and diminish EPO

production. The expected correlation between EPO and measures of oxygen

delivery (e.g., haemoglobin level, mixed venous oxygen tension, and available

oxygen) can be detected in premature neonates, providing evidence that the

same feedback loop exists. The measured levels of EPO are much lower than

those of older children and adults with corresponding degrees of anemia (Palis,

2008).

The magnitude of the EPO response was lowest in the least mature infant

(27 to 31 weeks of gestation) with low EPO values in cordocentesis samples

from infants between 18 and 37 weeks of gestation. This poor EPO response

persists through the neonatal period, resulting in a reduced erythropoietic


54

stimulus and lower haemoglobin levels in premature infants (Saizou et al.,

2004).

When maternal iron stores are depleted, the levels of iron in the fetus will

also end up with reduced fetal iron stores but no change in free iron availability.

Maternal diabetes causes depletion of fetal iron stores and is associated with

higher fetal iron demands as indicated by higher serum transferrin receptors

(STfR) and their ratio to ferritin (TfR-F index) in cord blood(Verner et al.,

2007).

Hemoglobin switching Hemoglobin synthesis proceeds in a process referred to as “hemoglobin

switching” (Stockman and Pochedly 1988). The blood of early human

embryos contains two slowly migrating haemoglobins, Gower-1 and Gower-2,

and Hb Portland, which has Hb F–like mobility. The zeta (ζ) chains of Hb

Portland and Gower-1 are structurally quite similar to α chain. Both Gower

haemoglobins contain a unique type of polypeptide chain, the epsilon (ε) chain.

Hb Gower-1 has the structure ζ2ε2, while Gower-2 has the structure α2ε2. Hb

Portland has the structure ζ2γ2. In embryos of 4–8 wk gestation, the Gower

haemoglobins predominate, but by the 3rd month they have disappeared. Hb F

contains γ polypeptide chains in place of the β chains of Hb A. Its after the 8th

gestational wk, Hb F is the predominant hemoglobin; at 24 wk gestation it

constitutes 90% of the total hemoglobin. During the 3rd trimester, a gradual

decline occurs, so that at birth Hb F averages 70% of the total. Some Hb A

(α2β2) can be detected in even the smallest embryos (Manca and Masala,

2008).

IDM shows delay in switching from production of fetal hemoglobin to

adult hemoglobin.

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globin for

decrease

obin, 11 g

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zarro et al

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in range i

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ntent is

6 wk in

careful


56

AGE

Gestational

(weeks)

HEMOGLOBIN

(g/dL)

HEMATO

CRIT (%) MCV (μ3)

RETICULOCYTES

(%)

18–20(*) 11.5 ± 0.8 36 ± 3 134 ± 8.8 N/A

21–22(*) 12.3 ± 0.9 39 ± 3 130 ± 6.2 N/A

23–25(*) 12.4 ± 0.8 39 ± 2 126 ± 6.2 N/A

26–27 19.0 ± 2.5 62 ± 8 132 ± 14.4 9.6 ± 3.2

28–29 19.3 ± 1.8 60 ± 7 131 ± 13.5 7.5 ± 2.5

30–31 19.1 ± 2.2 60 ± 8 127 ± 12.7 5.8 ± 2.0

32–33 18.5 ± 2.0 60 ± 8 123 ± 15.7 5.0 ± 1.9

34–35 19.6 ± 2.1 61 ± 7 122 ± 10.0 3.9 ± 1.6

36–37 19.2 ± 1.7 64 ± 7 121 ± 12.5 4.2 ± 1.8

38–40 19.3 ± 2.2 61 ± 7 119 ± 9.4 3.2 ± 1.4

* Based on samples collected in utero. Results expressed as mean value ± 1 standard deviation from the mean

Table (3): Normal Hemoglobin levels during fetal and neonatal period

(Bizzarro et al., 2004).


57

One factor that can significantly influence the haemoglobin level in

newborn infants is the amount of placental transfusion. At birth, blood is rapidly

transferred from the placenta to the infant, with one-fourth of the placental

transfusion occurring within 15 seconds of birth and one-half by the end of the

first minute. Delaying clamping of the umbilical cord in full-term neonates for a

minimum of 2 minutes following birth is beneficial to the newborn, extending

into infancy. Although there was an increase in polycythemia among infants in

whom cord clamping was delayed, this condition appeared to be benign

(Hutton and Hassan, 2007).

-Polycythemia

Venous haemoglobin exceeding 22 g/dL or a venous hematocrit more

than 65% during the first week of life should be regarded as polycythemia.

Although neonatal polycythemia may be the result of fetal disorders such as

twin-to-twin transfusion, placental insufficiency, and certain metabolic

disorders, most cases occur in otherwise normal infants. Most of these infants

have been full-term, appropriate for gestational age and without asphyxia at

birth (Sarkar and Rosenkrantz, 2008).

The symptoms in the polycythemic infant are due to hypervolemia and an

increase in blood viscosity. After the central venous hematocrit reaches 60% to

65%, the increase in blood viscosity becomes greater due to the exponential

relationship between hematocrit and viscosity. Respiratory distress,

thrombocytopenia, cyanosis, congestive heart failure, convulsions, priapism,

jaundice, renal vein thrombosis, hypoglycaemia, and hypocalcaemia appear to

be more common in infants with polycythemia. Many infants with

polycythemia are asymptomatic (Jeevasankar et al., 2008).


58

-Treatment of symptomatic polycythemia

Partial exchange transfusion (with normal saline). The Hct level at which

a partial exchange transfusion is indicated, in an asymptomatic infant, is unclear

but should not be considered if the Hct is ≤70–75%. Partial exchange will lower

the Hct and viscosity and improve acute symptoms (Pappas and Delaney-

Black, 2004).

The long-term prognosis of polycythemic infants is unclear. Reported

adverse outcomes include speech deficits, abnormal fine motor control, reduced

IQ, school problems, and other neurologic abnormalities. It is thought that the

underlying etiology (chronic intrauterine hypoxia) and hyperviscosity contribute

to adverse outcomes. It is unclear whether partial exchange transfusion

improves the long-term outcome. Most asymptomatic infants develop normally

(Dempsey and Barrington, 2006).

Chapter

-Form

major

haemo

oxidati

enzym

methan

(CO)

subseq

2008;

Figure

bilirub

II

mation, Str

Bilirubin

source i

oglobin inv

ive proce

me found i

ne bridge

and biliv

quently, bi

Ryter and

e (9): ch

bin (Feve

Bilir

ructure, a

is the en

s circulat

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ss catalyz

in the ret

of the h

verdin is

ilirubin) is

d Choi, 2

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ry, 2008).

rubin M

and Prope

nd produc

ting haem

moval of t

zed by th

ticuloendo

heme porp

formed .O

s formed f

009).

structure

.

59

etabolism

erties of B

ct of the c

moglobin.

the iron an

he enzyme

othelial sy

phyrin ring

One mole

for each m

e of nat

m and ID

Bilirubin

catabolism

The form

nd protein

e microso

ystem and

g is open

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molecule o

turally o

DMs

m of hem

mation of

n moieties

omal heme

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CO and

f heme de

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f bilirubin

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biliverdin

egraded (F

g unconju

Literature

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d by an

ase, an

es. The

onoxide

n (and,

Fevery,

ugated


60

-Fetal Bilirubin Metabolism

The major route of fetal bilirubin excretion is the placenta. Because

virtually all the fetal plasma bilirubin is unconjugated, it is readily transferred

across the placenta to the maternal circulation to be excreted by the maternal

liver. Thus, the newborn rarely is born jaundiced, except in the presence of

severe hemolysis, when there may be accumulation of unconjugated bilirubin in

the fetus. Conjugated bilirubin is not transferred across the placenta, and it may

accumulate in the fetal plasma and tissues (McDonagh, 2007).

Bilirubin can be detected in normal amniotic fluid after about 12 weeks of

gestation, but it disappears by 36 to 37 weeks' gestation. The ability of human

fetal liver to remove bilirubin from the circulation and to conjugate it is severely

limited. Between 17 and 30 weeks of gestation, uridine diphosphoglucuronosyl

transferase (UDPGT) activity in fetal liver is only 0.1% of adult values, but it

increases tenfold to 1% of adult values between 30 and 40 weeks' gestation.

After birth, activity increases, reaching adult levels by 6 to 14 weeks' gestation

(Macias et al., 2009).

Neonatal Bilirubin Metabolism

-Bilirubin Production

The normal destruction of circulating erythrocytes accounts for about

75% of the daily bilirubin production in the newborn. Senescent erythrocytes

are removed and destroyed in the reticuloendothelial system, where the heme is

catabolized and converted to bilirubin (Maisels and Kring, 2006).

-Transport and Hepatic Uptake of Bilirubin

Once bilirubin leaves the reticuloendothelial system, it is transported in

the plasma and bound reversibly to albumin. When the bilirubin-albumin


61

complex reaches the plasma membrane of the hepatocyte, a proportion of the

bilirubin, but not the albumin, is transferred across the cell membrane into the

hepatocyte, a process that involves four different transport proteins. In the

hepatocyte, bilirubin is bound principally to ligandin and possibly other

cytosolic-binding proteins. A network of intracellular microsomal membranes

plays an important role in transfer of bilirubin within the cell and to the

endoplasmic reticulum (Reiser, 2004).

-Conjugation and Excretion of Bilirubin

Unconjugated bilirubin is nonpolar and insoluble in aqueous solutions at

pH 7.4 and must be converted to its water-soluble conjugate before it can be

excreted. This is achieved when bilirubin is combined enzymatically with

glucuronic acid, producing bilirubin monoglucuronide and diglucuronide

pigments that are more water soluble and sufficiently polar to be excreted into

the bile or filtered through the kidney (Chen et al., 2005).

The process of conjugation is catalyzed by glucuronoyl transferase which

is synthesized in the hepatocyte, a specific enzyme A1 isoform (UGT1A1)

belonging to the uridine diphosphoglucuronate glucuronosyltransferase (UGT)

family of enzymes (Costa, 2006).

-Physiologic Mechanisms of Neonatal Jaundice

At any time in the infant's first few days after birth, the serum bilirubin

level reflects a combination of the effects of bilirubin production, conjugation,

and enterohepatic circulation. An imbalance between bilirubin production and

conjugation is fundamental in the pathogenesis of neonatal hyperbilirubinemia

(Reiser, 2004).


62

A-Increased Bilirubin Load on the Liver Cell

1-Increased Bilirubin Production

CO is produced in equimolar quantities with bilirubin and measurements

of CO production show that the normal newborn produces an average of 8 to 10

mg/kg of bilirubin per day. This is more than twice the rate of normal daily

bilirubin production in the adult and is explained by the fact that the neonate has

a higher circulating erythrocyte volume, a shorter mean erythrocyte lifespan,

and a larger early bilirubin peak. Bilirubin production decreases with increasing

postnatal age but is still about twice the adult rate by age 2 weeks (Newman et

al., 2005).

2-Increased Enterohepatic Circulation

The newborn reabsorbs larger quantities of unconjugated bilirubin by

way of the enterohepatic circulation, than the adult. Infants have fewer bacteria

in the small and large bowel and greater activity of the deconjugating enzyme

b-glucuronidase .As a result, conjugated bilirubin, which is not reabsorbed, is

not converted to urobilinogen but is hydrolyzed to unconjugated bilirubin,

which is reabsorbed, and increasing the bilirubin load on an already stressed

liver. In the first few days after birth, caloric intake is low, which contributes to

an increase in the enterohepatic circulation (Tiribelli and Ostrow, 2005).

B-Decreased Clearance of Bilirubin from the Plasma

1-Impaired Uptake

Ligandin, the predominant bilirubin-binding protein in the human liver

cell, is deficient in the liver of newborn monkeys. It reaches adult levels in the

monkey by 5 days of age, coinciding with a fall in bilirubin levels. And


63

administration of Phenobarbital increases the concentration of ligandin; this

suggests that impaired uptake may contribute to the pathogenesis of physiologic

jaundice (Rigato et al., 2005).

2-Impaired Conjugation

Deficient UGT1A1 activity, with impairment of bilirubin conjugation,

has long been considered a major cause of physiologic jaundice. In human

infants, the early postnatal increase in serum bilirubin appears to play an

important role in the initiation of bilirubin conjugation. In the first 10 days after

birth, UGT1A1 activity in full-term and premature neonates usually is less than

1% of adult values then, the activity increases at an exponential rate, reaching

adult values by 6 to 14 weeks of age, that increase in UGT1A1 activity is

independent of the infant's gestation(Wang et al., 2006).

3-Limited Excretion

The absence of an elevated serum level of conjugated bilirubin in

physiologic jaundice suggests that, under normal circumstances, the neonatal

liver cell is capable of excreting the bilirubin that it has just conjugated.

However, the ability of the newborn liver to excrete conjugated bilirubin and

other anions (e.g., drugs, hormones) is more limited than that of the older child

or adult and may become rate limiting when the bilirubin load is significantly

increased. Thus, when intrauterine hyperbilirubinemia occurs, usually as a result

of isoimmunisation, it is not uncommon to find an elevated serum level of

conjugated bilirubin (Fevery, 2008).

Subjects and Methods

64


This study was carried on 40 neonates their gestational age ranged from 32-41

weeks.

Their mothers have diabetes mellitus have both pregestational (including

type I and type II diabetes) and gestational diabetes admitted to Neonatal

Intensive Care Unit (NICU) with apparent clinical complications due to

maternal diabetes. They were collected from Abu Alreish hospital and NICU of

Obstetric hospital within Al Kasr Al Aini in the period from August 2008 to

August 2009.They were 10 males and 30 females .

20 healthy neonates of the same gestational age and the same

socioeconomic standards ;their mothers had no diabetes or other diseases ; were

taken as a control group.

*Neonates have been divided into the following 3 groups:-

Group I: Control group. (n=20)

Group II: IDMs whose mothers had pregestational diabetes (n=20)

Group III: IDMs whose mothers had gestational diabetes mellitus. (n=20)

In group II (IDMs whose mothers had pregestational diabetes) respiratory

distress (RD) was the commonest cause of admission in this group, followed by

hypoglycemia and jaundice in addition to heart failure. The congenital

anomalies appeared in this group affected five of the patients and were in the

form of cardiomegaly, tricuspid regurge (TR), mitral regurge (MR), and

pulmonary regurge (PR).


65

In group III (IDMs whose mothers had gestational diabetes), also the

most common complication to maternal diabetes in this group is respiratory

distress in addition to hypoglycemia, jaundice and hypoxic ischemic

encephalopathy. The congenital anomalies appeared in this group affected

five patients of group III and were in the form of bone and joint anomalies,

hydrocephalus, menngomyelocele, renal cyst, left ventricular hypertrophy,

septal hypertrophy and patent ductus arteriosus (PDA).

A full history was taken and thorough clinical examination for all neonates was

performed.

*The following parameters were assessed:

1- Serum glucose level.

2- Serum calcium level.

3- Complete Blood Count (CBC) with differential leucocytic count.

4- Serum bilirubin level.

5- Arterial Blood Gases (ABG).

6-Acid base status (HCO3, pH and BE/BD).

All samples were taken on first day of admission (patients are referred to as

Group IIa for IDM whose mothers had pregestational diabetes and Group IIIa

for patients whose mothers had gestational diabetes mellitus) and before

discharge from NICU for IDMs(patients are referred to as Group IIb for IDM

whose mothers had pregestational diabetes and Group IIIb for patients whose

mothers had gestational diabetes mellitus).

For control group; we assessed the parameters once on first day of life just after

birth.

-Meth

neurom

files. T

criteria

tone is

betwee

2006).

Neurol

2009).

hodology

The gest

muscular m

The exam

a. The neu

s more use

en two ob

It slightl

logical si

Fig (

y:

tational a

maturity a

mination co

uromuscul

eful than a

bservers in

ly overest

gns are m

(1): NewB

age asses

and physic

onsists of

lar criteria

active tone

n NBS as

timates th

more relia

Ballard Sc

66

ssed by

cal maturi

f six neuro

a are base

e in indica

ssessment

he GA wit

able than

core (Mar

New Ba

ity and it

omuscular

d on the u

ating gesta

was don

th increas

physical

rín Gabri

allard sco

was prov

r criteria a

understand

ational age

ne (Marín

sing postn

ones (Sas

iel et al., 2

Subjects and

ore (NBS

ided in ne

and six ph

ding that p

e. The agre

n Gabriel

natal age (

sidharan

2006)

d Methods

S), for

eonates

hysical

passive

eement

et al.,

(PNA).

et al.,


67

Measurements were obtained through automated systems. We measured

Serum glucose, calcium, bilirubin by (Beckman Coulter Hmx-analyzer,

Fullerton, CA).Complete Blood Picture for anticoagulated blood samples

(EDTA in the collecting tubes) were measured by Sysmex KX-21N, America,

Inc. ABG was measured by GASTAT-602i Blood gas system.


68

Statistical analysis

Data were statistically described in terms of, mean and standard deviation

(± SD).

-The Arithmetic Mean (x)

The mean is the sum of the observations divided by the number of observations

(Altman, 2005).

X=S(x)/n

S(x) =sum of the individual values.

n = numbers of measurements.

-Standard Deviation (SD)

SD= 1

2

−nd

d2 =sum of deviation of the individual values from the arithmetic mean of the

series.

n-1=degree freedom (Altman, 2005).

-Comparisons:

Comparison of quantitative variables between the study groups was done using

Kruskal Wallis analysis of variance (ANOVA) test. Within group comparison


69

of quantitative variables was done using Wilcoxon signed rank test for paired

(matched) samples.

-Probability ″P value ″

It can be estimated from the degree of freedom.

Limits of significance:

P>0.050 =non-significant.

P<0.050 = significant.

Correlation

Correlation was done to show the association between two quantitive variables.

It is described from two main parameters:

(1) The strength:

It is expressed as a number that ranges between 0 in case of absence and 1 in

case of perfect correlation.

(2)The direction:

It is expressed either as positive or negative. The positive correlation means that

as the values of one variable increase, the value of the other variable increase

too. The negative correlation means that as the values of one variable decrease,

the value of the other variable increase, i.e. Inverse relation (Knapp and

Miller, 1992).


70

All statistical calculations were done using computer programs Microsoft Excel

2003 (Microsoft Corporation, NY, USA) and SPSS (Statistical Package for the

Social Science; SPSS Inc., Chicago, IL, USA) version 17 for Microsoft

Windows.

Results

71

Results

A-Descriptive statistics

Table (1): Shows mean ±standard deviation (SD) of the measured variables among studied groups

Parameter

Control(n=20)Group IIa (n=20)

Group IIb (n=20)

Group IIIa (n=20)

Group IIIb (n=20)

Glucose(mg/dl) 84.25±14.414 49.95±20.493 84.25±16.049 65.45±41.140 88.15±13.816

Calcium(mg/dl) 9.80±.894 7.68±1.348 8.59±1.002 7.34±1.203 8.71±1.173

PH 7.39±.028 7.24±.156 7.38±.045 7.31±.133 7.41±.083

PO2(mm Hg) 88.06±5.263 47.71±22.368 89.28±4.322 63.79±25.185 90.32±16.482

PCO2(mm Hg) 40.14±3.093 52.69±19.187 38.50±3.744 42.97±24.030 36.29±13.367

HCO3(mEq/L) 21.35±2.067 22.00±4.677 22.71±2.795 19.15±5.284 22.91±3.429

BE/BD(mEq/L) -1.16±.644 -3.82±6.742 -1.68±2.376 -5.97±5.116 -2.08±2.060

TSB(mg/dl) 2.79±1.261 9.80±5.807 7.89±4.197 5.81±3.898 6.82±4.068

DSB(mg/dl) 0.80±.433 1.42±2.857 0.74±.446 0.56±.239 0.64±.343

Results

72

Hb(g/dL) 16.71±2.495 17.12±3.828 16.31±3.224 14.49±4.719 14.08±3.288

RBCs(million/cmm) 5.34±.846 5.27±.968 5.07±.774 4.40±1.097 4.35±.865

PCV (%) 53.09±7.168 52.45±11.807 50.83±10.780 45.54±13.936 43.72±11.179

MCV(fL) 105.53±6.673 96.83±9.567 94.91±9.224 97.63±10.801 97.26±10.589

MCH(pg) 35.10±2.872 33.35±3.699 33.48±3.448 32.17±4.121 32.18±3.524

MCHC(g/dL) 35.22±2.768 34.40±2.427 34.45±2.669 32.90±3.102 32.96±2.506

RDW (%) 16.08±2.994 18.94±5.213 18.39±4.290 20.13±3.916 18.95±3.499

Retics(%) 1.43±.892 3.11±2.566 2.91±2.360 2.41±1.280 2.31±1.051

WBC(1000/cmm) 17.85±6.144 15.36±6.063 15.73±6.407 16.88±8.253 15.34±6.615

Staff (%) 3.30±3.063 7.35±5.314 6.10±5.973 9.65±7.358 5.55±5.652

Segmented (%) 55.50±6.613 48.00±10.926 48.00±10.214 49.05±10.211 52.90±11.652

Platelets(1000/cmm) 332.75±88.859 244.90±113.973 237.85±112.657 181.55±106.119 222.25±135.704

TSB=Total Serum Bilirubin, DSB =Direct Serum Bilirubin. RBCs=Red Blood Corpuscles, Hb=Hemoglobin, PCV=Packed Cell Volume,

MCV=Mean Corpuscular Volume, MCH=Mean Corpuscular Hemoglobin, MCHC= Mean Corpuscular Hemoglobin Concentration, RDW=Red

Cell Distribution Width, WBC=White Blood Cells.

Results

73

B- Comparative studies of different parameters among the studied groups

1-Comparison of quantitative variables within the same group at

admission and before discharge -Group II (IDMs whose mothers had pregestational diabetes)

-As revealed from table (2):

There was a significant increase (P value < 0.05) in serum glucose level

in group II before discharge (84.25±16.049mg/dl)in comparison to values on

admission (49.95±20.493mg/dl).There was also a significant increase (P value <

0.05) in serum calcium level before discharge (8.59±1.002mg/dl)compared to

level on admission (7.68±1.348mg/dl).

Table (2) Paired sample test for serum glucose and calcium at admission

and before discharge (Group II) Pairs t Sig. (2-tailed)

Glucose2 - Glucose1 6.551 .000*

Calcium2 - Calcium1 4.577 .000*

* P<0.05= significant


In group II There was a significant increase (P value < 0.05) in pH in

before discharge (7.38±.045) compared to values on admission

(7.24±.156).Also, there was a significant increase (P value < 0.05) in PO2

values before discharge (89.28±4.322mmHg) compared to values on admission

(47.71±22.368) mm Hg.

There was a significant decrease (P value < 0.05) in PCO2 values before

discharge (38.50±3.744 mm Hg) compared to values on admission

(52.69±19.187 mm Hg).

Results

74

There was no statistically significant difference between, HCO3 levels

before discharge (22.71±2.795 mEq/L) to values measured on admission

(22.00±4.677 mEq/L).Also there was no significant difference in BE/BD

measurements before discharge (-1.68±2.376 mEq/L) compared to those on

admission(-3.82±6.742 mEq/L).

Table (3) Paired sample test for Arterial blood gas analysis components at

admission and before discharge (Group II). Pairs t Sig. (2-tailed)

PH2 - PH1 4.515 .000*

PO2. 2 - PO2. 1 8.109 .000*

PCO2. 2 - PCO2. 1 -3.168 .005*

HCO3.2 - HCO3. 1 .635 .533

BE/BD 2 - BE/BD 1 1.374 .185

*P<0.05=Significant

-As revealed from table (4)

In group II there was no statistically significant difference between, TSB

levels before discharge (7.89±4.197 mg/dl) to values measured on admission

(9.80±5.807 mg/dl).Also there was no significant difference in DSB

measurements before discharge(0.74±.446 mg/dl) compared to those on

admission(1.42±2.857 mg/dl).

Table (4) Paired sample test for total and direct bilirubin at admission and

before discharge (Group II) Pairs t Sig. (2-tailed)

TSB2 - TSB1 -1.243 .229

DSB2 - DSB1 -1.002 .329

TSB=Total Serum Bilirubin, DSB =Direct Serum Bilirubin.

Results

75


In group II there was a significant decrease (P value < 0.05) in

hemoglobin value measured before discharge (16.31±3.224gm/dl) compared to

value on admission (17.12±3.828gm/dl).There was a significant decrease (P

value < 0.05) in RBCs count before discharge (5.07±.774 million/cmm)

compared to count on admission (5.27±.968 million/cmm).Other variables of

complete blood counts (CBC) didn’t show significant difference in values

before discharge compared to the values measured on admission.

Table (5) Paired sample test for Complete Blood Count at admission and

before discharge (Group II). Pairs t Sig. (2-tailed)

Hb2 - Hb1 -2.406 .026*

RBCs2 - RBCs1 -2.164 .043*

PCV2 - PCV1 -1.765 .094

MCV2 - MCV1 -1.548 .138

MCH2 - MCH1 .443 .663

MCHC2 - MCHC1 .201 .843

RDW2 - RDW1 -1.070 .298

Retics.2 - Retics.1 -1.313 .205

TLC2 - TLC1 .367 .718

staff.2 - staff.1 -.974 .342

segmen.2 - segmen.1 .000 1.000

Lymph.2 - Lymph.1 -.299 .768

Basophil2 - Basophils1 -1.277 .217

esinophils2 - esinophils1 -.279 .783

PLT.2 - PLT.1 -.516 .612

*P<0.05=Significant

RBCs=Red Blood Corpuscles, Hb=Hemoglobin, PCV=Packed Cell Volume,

MCV=Mean Corpuscular Volume, MCH=Mean Corpuscular Hemoglobin, MCHC= Mean

Corpuscular Hemoglobin Concentration, RDW=Red Cell Distribution Width,

WBC=White Blood Cells.

Results

76

-Group III (IDMs whose mothers had gestational diabetes)


There was a significant increase (P value < 0.05) in serum glucose level

in group III before discharge (88.15±13.816mg/dl)in comparison to values on

admission (65.45±41.140mg/dl).There was also a significant increase (P value <

0.05) in serum calcium level before discharge (8.71±1.173mg/dl)compared to

level on admission (7.34±1.203mg/dl).

Table (6) Paired sample test for serum glucose and calcium at admission

and before discharge (Group III).

Pairs t Sig. (2-tailed)

Glucose2 - Glucose1 2.275 .035*

Calcium2 - Calcium1 7.850 .000*

*P<0.05=Significant


In group III There was a significant increase (P value < 0.05) in pH in

before discharge (7.41±.083) compared to values on admission

(7.31±.133).Also, there was a significant increase (P value < 0.05) in PO2

values before discharge (90.32±16.482mmHg) compared to values on

admission (63.79±25.185 mm Hg).There was no statistically significant

difference in PCO2 values before discharge (36.29±13.367mm Hg) compared to

values on admission (42.97±24.030mm Hg).

Both HCO3 and BE/BD levels were significantly increased (P value <

0.05) in measurements before discharge compared to those on admission

(22.91±3.429 mEq/L versus 19.15±5.284 mEq/L and -2.08±2.060 mEq/L versus

-5.97±5.116 mEq/L respectively).

Results

77

Table (7) Paired sample test for Arterial blood gas analysis components at

admission and before discharge (Group III). Pairs T Sig. (2-tailed)

PH2 - PH1 3.086 0.006*

PO2. 2 - PO2. 1 4.163 0.001*

PCO2. 2 - PCO2. 1 1.041 0.311

HCO3.2 - HCO3. 1 3.253 0.004*

BE/BD 2 - BE/BD 1 3.255 0.004*

*P<0.05= significant

-As revealed from table (8)

In group III there was no statistically significant difference between, TSB

levels before discharge (6.82±4.068 mg/dl) to values measured on admission

(5.81±3.898 mg/dl).Also there was no significant difference in DSB

measurements before discharge(0.64±.343 mg/dl) compared to those on

admission(0.56±.239mg/dl).

Table (8) Paired sample test for total and direct bilirubin at admission and

before discharge (Group III). Pairs t Sig. (2-tailed)

TSB2 - TSB1 .877 .392

DSB2 - DSB1 .895 .382

TSB=Total Serum Bilirubin, DSB =Direct Serum Bilirubin.


In group III there was a significant decrease (P value < 0.05) in RDW in

measurement before discharge (18.95±3.499%) compared to those on admission

(20.13±3.916%).

There was a significant decrease in staff PMNL count in values measured

before discharge (5.55±5.652%) as compared to those on admission

(9.65±7.358%). Other variables of complete blood counts (CBC) didn’t show

Results

78

significant difference in values before discharge compared to the values

measured on admission.

Table (9) Paired sample test for Complete Blood Count at admission and

before discharge (Group III). Pairs t Sig. (2-tailed)

Hb2 - Hb1 -1.253 .226

RBCs2 - RBCs1 -.419 .680

PCV2 - PCV1 -1.639 .118

MCV2 - MCV1 -.723 .479

MCH2 - MCH1 .050 .961

MCHC2 - MCHC1 .269 .791

RDW2 - RDW1 -2.855 .010*

Retics.2 - Retics.1 -1.169 .257

TLC2 - TLC1 -1.257 .224

staff.2 - staff.1 -5.626 .000*

segmen.2 - segmen.1 1.660 .113

Lymph.2 - Lymph.1 .000 1.000

Basophil2 - Basophils1 .736 .471

esinophils2 - esinophils1 -1.000 .330

PLT.2 - PLT.1 -.326 .748

*P<0.05=Significant

Hb=Hemoglobin, RBCs=Red Blood Corpuscles, PCV=Packed Cell Volume, MCV=Mean

Corpuscular Volume, MCH=Mean Corpuscular Hemoglobin, MCHC= Mean Corpuscular

Hemoglobin Concentration, RDW=Red Cell Distribution Width, WBC=White Blood Cells.

Results

79

2-Analysis of Variance (ANOVA) test

-Comparison between variables on admission in group II and group III and

control group:


There was a significant decrease (P value < 0.05) in serum glucose level

on admission in both group II (49.95±20.493mg/dl) and group III

(65.45±41.140 mg/dl) compared to control group (84.25±14.414mg/dl) (Figure

1).

There was also a significant decrease (P value < 0.05) in serum calcium

level in both group II (7.68±1.348 mg/dl) and groupIII (7.34±1.203 mg/dl) on

admission compared to control group (9.80±.894 mg/dl) (Figure 2).

Table (10) Comparison of serum glucose and calcium in group II, group III

on admission and control group.

Measured variable Control

(n=20)

Group IIa

(n=20)

Group IIIa

(n=20)

P-value

Glucose (mg/dl) 84.25±14.414 49.95±20.493 65.45±41.140 0.000*

Calcium (mg/d)l 9.80±.894 7.68±1.348 7.34±1.203 0.000*



There was a significant decrease in pH (P value < 0.05) in group II

(7.24±.156) and group III on admission (7.31±.133) compared to control group

(7.39±.028) (Figure14).

A significant decrease (P value < 0.05) in PO2 in group II (47.71±22.368

mmHg) and groupIII on admission (63.79±25.185 mmHg) compared to control

group (88.06±5.263mmHg) as shown in (Figure11).On the opposite side a

Results

80

significant increase (P value < 0.05) was revealed in PCO2 in group II

(52.69±19.187mmHg) and group III on admission (42.97±24.030mmHg)

compared to control group (40.14±3.093mmHg) (Figure 12).

There was no significant difference in HCO3 values between group II

(22.00±4.677mEq/L) and group III on admission (19.15±5.284 mEq/L) and

control group (21.35±2.067mEq/L), (Figure13).

BE/BD was significantly decreased (P value < 0.05) both in group II (-

3.82±6.742 mEq/L) and groupIII on admission (-5.97±5.116 mEq/L) compared

to control group (-1.16±.644 mEq/L) (Figure15).

Table (11) Comparison of Arterial Blood Gas analysis in group II, group

III on admission and control group.

Measured

Parameter

Control

(n=20)

Group IIa

(n=20)

Group IIIa

(n=20)

P-value

PH 7.39±.028 7.24±.156 7.31±.133 0.000*

PO2(mm Hg) 88.06±5.263 47.71±22.368 63.79±25.185 0.000*

PCO2(mm Hg) 40.14±3.093 52.69±19.187 42.97±24.030 0.006*

HCO3(mEq/L) 21.35±2.067 22.00±4.677 19.15±5.284 0.101

BE/BD(mEq/L) -1.16±.644 -3.82±6.742 -5.97±5.116 0.001*



There was a significant increase (P value < 0.05) in TSB in group II

(9.80±5.807 mg/dl) and groupIII on admission (5.81±3.898 mg/dl) compared to

control group (2.79±1.261mg/dl) (Figure 3).On the other hand there was no

statistically significant difference between DSB levels in group II (1.42±2.857

mg/dl) and groupIII on admission (0.56±0.239 mg/dl) compared to control

group (0.80±0.433 mg/dl) (Figure 4).

Results

81

Table (12) Comparison of total and direct serum bilirubin in group II,

group III on admission and control group.

Measured

Parameter

Control

(n=20)

Group IIa

(n=20)

Group IIIa

(n=20)

P-value

TSB(mg/dl) 2.79±1.261 9.80±5.807 5.81±3.898 0.000*

DSB(mg/dl) 0.80±.433 1.42±2.857 0.56±.239 0.180


TSB=Total Serum Bilirubin, DSB =Direct Serum Bilirubin


There was a significant decrease (P value < 0.05) in RBCs count in group

II (5.27±.968million/cmm) and groupIII on admission (4.40±1.097

million/cmm) compared to control group (5.34±.846 million/cmm).

There was a significant decrease in blood indices (MCV, MCH, MCHC)

in group II and groupIII on admission compared to control group.

There was also a significant increase (P value < 0.05) in RDW in group II

(18.94±5.213%) and groupIII on admission (20.13±3.916%) compared to

control group (16.08±2.994%) (Figure10).

A significant increase (P value < 0.05) in retics was observed in group II

(3.11±2.566%) and group III on admission (2.41±1.280%) in comparison to

control group (1.43±.892%).

There was a significant increase (P value < 0.05) in staff PMNL count in

group II (7.35±5.314%) and groupIII on admission (9.65±7.358%) compared to

control group (3.30±3.063%) (Figure8).While there was a significant decrease

(P value < 0.05) in segmented count in group II (48.00±10.926%) and group III

on admission (49.05±10.211%) compared to control group (55.50±6.613%).

Results

82

There was a significant decrease (P value < 0.05) in platelets count in

group II (244.90±113.973 x 1000/cmm) and group III (181.55±106.119 x

1000/cmm) on admission compared to control group (332.75±88.859 x

1000/cmm) (Figure 9).

Table (13) Comparison of Complete Blood Count in group II, group III on

admission and control group. Measured

Parameter

Control

(n=20)

Group IIa

(n=20)

Group IIIa

(n=20)

P-value

Hb(gm/dl) 16.71±2.495 17.12±3.828 14.49±4.719 0.195

RBCs(million/cmm) 5.34±.846 5.27±.968 4.40±1.097 0.011*

PCV (%) 53.09±7.168 52.45±11.807 45.54±13.936 0.118

MCV(fL) 105.53±6.673 96.83±9.567 97.63±10.801 0.009*

MCH(pg) 35.10±2.872 33.35±3.699 32.17±4.121 0.056*

MCHC(g/dl) 35.22±2.768 34.40±2.427 32.90±3.102 0.018*

RDW (%) 16.08±2.994 18.94±5.213 20.13±3.916 0.011*

Retics (%) 1.43±.892 3.11±2.566 2.41±1.280 0.037*

TLC(1000/cmm) 17.85±6.144 15.36±6.063 16.88±8.253 0.389

Staff (%) 3.30±3.063 7.35±5.314 9.65±7.358 0.003*

Segmented (%) 55.50±6.613 48.00±10.926 49.05±10.211 0.047*

Lymph (%) 26.25±9.227 29.90±11.544 26.15±8.689 0.491

Mon (%) 9.90±5.590 9.35±5.631 10.20±5.197 0.863

Basophils (%) .95±.887 1.25±.967 1.05±.999 0.641

Esinophils (%) 4.10±2.075 4.15±2.254 3.80±1.989 0.860

Platelets(1000/cmm) 332.75±88.85

9

244.90±113.973 181.55±106.119 0.000*

*P<0.05=Significant

Hb=Hemoglobin, RBCs=Red Blood Corpuscles, PCV=Packed Cell Volume, MCV=Mean

Corpuscular Volume, MCH=Mean Corpuscular Hemoglobin, MCHC= Mean Corpuscular

Hemoglobin Concentration, RDW=Red Cell Distribution Width, WBC=White Blood Cells.

Results

83

-Comparison between variables before discharge in group II and group III

and control group:


There was no significant difference in serum glucose level in both group

II (84.25±16.049mg/dl) and group III (88.15±13.816 mg/dl) before discharge

compared to control group (84.25±14.414mg/dl) (Figure 1).

There was a significant decrease (P value < 0.05) in serum calcium level

in both group II (8.59±1.002mg/dl) and groupIII (8.71±1.173mg/dl) before

discharge relative to control group (9.80±.894 mg/dl) (Figure 2).

Table (14) Comparison of serum glucose and calcium in, group II, group

III before discharge and control group.

Measured

Parameter

Control

(n=20)

Group IIb

(n=20)

Group IIIb

(n=20)

P-value

Glucose(mg/dl) 84.25±14.414 84.25±16.049 88.15±13.816 0.644

Calcium(mg/dl) 9.80±.894 8.59±1.002 8.71±1.173 0.005*



There was a significant increase (P value < 0.05) in HCO3 values in

group II (22.71±2.795 mEq/L) and group III (22.91±3.429mEq/L) before

discharge compared to control group (21.35±2.067mEq/L) (Figure13). Other

variables measured in ABG didn’t show statistically significant difference in

group II and group III before discharge compared to control group.

Results

84

Table (15) Comparison of Arterial Blood Gas analysis in group II, group

III before discharge and control group.

Measured

Parameter

Control

(n=20)

Group IIb

(n=20)

Group IIIb

(n=20)

p-value

PH 7.39±.028 7.38±.045 7.41±.083 0.835

PO2(mm Hg) 88.06±5.263 89.28±4.322 90.32±16.482 0.853

PCO2(mm Hg) 40.14±3.093 38.50±3.744 36.29±13.367 0.452

HCO3(mEq/L) 21.35±2.067 22.71±2.795 22.91±3.429 0.026*

BE/BD(mEq/L) -1.16±.644 -1.68±2.376 -2.08±2.060 0.501

*P<0.05=Significant


There was a significant increase (P value < 0.05) in TSB in group II

(7.89±4.197mg/dl) and groupIII (6.82±4.068mg/dl) before discharge compared

to control group (2.79±1.261mg/dl) (Figure 3).On the other hand there was no

statistically significant difference between DSB levels in group II (0.74±.446

mg/dl) and groupIII (0.64±.343 mg/dl) before discharge compared to control

group (0.80±.433 mg/dl) (Figure 4).

Table (16) Comparison of total and direct serum bilirubin in group II,


Measured

Parameter

Control

(n=20)

Group IIb

(n=20)

Group IIIb

(n=20)

P-value

TSB(mg/dl) 2.79±1.261 7.89±4.197 6.82±4.068 0.000*

DSB(mg/dl) 0.80±.433 0.74±.446 0.64±.343 0.451


Results

85


There was a significant decrease (P value < 0.05) in Hb level in group II

(16.31±3.224 gm/dl) and groupIII (14.08±3.288 gm/dl) before discharge in

comparison to control group (16.71±2.495 gm/dl).

There was a significant decrease (P value < 0.05) in RBCs count in group

II (5.07±.774 million/cmm) and groupIII (4.35±.865 million/cmm) before

discharge compared to control group (5.34±.846 million/cmm).

A significant decrease (P value < 0.05) in PCV in group II

(50.83±10.780%) and groupIII (43.72±11.179%) before discharge as compared

to control group (53.09±7.168%) (Figure 6).

There was a significant decrease in blood indices (MCV, MCH, MCHC)

in group II and groupIII before discharge compared to control group.

A significant increase (P value < 0.05) in retics was observed in group II

(2.91±2.360%) and group III (2.31±1.051%) before discharge in comparison to

control group (1.43±.892%).

There was a significant decrease (P value < 0.05) in platelets count in

group II (237.85±112.657 x1000/cmm) and group III (222.25±135.704

1000/cmm) before discharge as compared to control group (332.75±88.859

1000/cmm) (Figure9).

Results

86

Table (17) Comparison of Complete Blood Count in, group II, group III

before discharge and control group.

Measured

Parameter

Control

(n=20)

Group IIb

(n=20)

Group IIIb

(n=20)

P-value

Hb(gm/dl) 16.71±2.495 16.31±3.224 14.08±3.288 0.032*

RBCs(million/cmm) 5.34±.846 5.07±.774 4.35±.865 0.002*

PCV (%) 53.09±7.168 50.83±10.780 43.72±11.179 0.024*

MCV(fL) 105.53±6.673 94.91±9.224 97.26±10.589 0.002*

MCH(pg) 35.10±2.872 33.48±3.448 32.18±3.524 0.025*

MCHC(gm/dl) 35.22±2.768 34.45±2.669 32.96±2.506 0.027*

RDW (%) 16.08±2.994 18.39±4.290 18.95±3.499 0.069

Retics.(%) 1.43±.892 2.91±2.360 2.31±1.051 0.027*

TLC(1000/cmm) 17.85±6.144 15.73±6.407 15.34±6.615 0.364

Staff (%) 3.30±3.063 6.10±5.973 5.55±5.652 0.395

Segmented (%) 55.50±6.613 48.00±10.214 52.90±11.652 0.075

Lymph (%) 26.25±9.227 29.45±11.067 26.15±9.885 0.571

Mon (%) 9.90±5.590 11.60±5.968 11.00±4.611 0.573

Basophils(%) .95±.887 .90±1.021 .80±.834 0.877

Esinophils(%) 4.10±2.075 3.95±2.665 3.60±1.984 0.729

Platelets(1000/cmm) 332.75±88.859 237.85±112.657 222.25±135.704 0.002*

*P<0.05=Significant

RBCs=Red Blood Corpuscles PCV=Packed Cell Volume, Hb=Hemoglobin,

MCV=Mean Corpuscular Volume, MCH=Mean Corpuscular Hemoglobin, MCHC= Mean

Corpuscular Hemoglobin Concentration, RDW=Red Cell Distribution Width, WBC=White

Blood Cells,

Results

Figure

group

*signifi

Figuregroup

1

1

0

2

4

6

8

10

12

mg/

e (1) Com

s

icant P as co

e (2): Coms

0

20

40

60

80

100

120

mg/dl

/dl

*

mparison o

ompared to

mparison

84.25

control

9.8

control

significant P

of serum

control

of serum

49.95

G

groupIIa

7.675

Grou

groupIIa

87

P as compa

glucose le

m calcium

84.25

Group

GlucoseGroupA

groupIIb

8.59

Group

CalciupA*and

groupIIb

ared to contr

evel (mg/d

level (mg

65.45

eA*

groupIIIa

7.335

iumd Group

groupIIIa

rol

dl) among

g/dl) amon

88.15

groupIIIb

8.71

p B*

groupIIIb

g the stud

ng the stu

b

died

udied

Results

*signifi

Figurestudie

Figurethe stu

1

1

2

‐2

‐1

0

1

2

3

4

5

mg/d

icant P as co

e (3): Comed groups

e (4): Comudied gro

0

5

10

15

20

0.

mg/dl

dl

ompared to

mparison

mparison up

2.79

control

8051.4

control gr

control

of serum

of serum

9.795

Grou

groupIIa

4170.74

Gro

DS

roupIIa gr

88

m total bili

m level of d

7.89

Group

TSBpA* and

groupIIb

425 0.5

oup

SB

roupIIb gro

irubin (m

direct bili

5.81

Bd Group

groupIIIa

56 0.64

oupIIIa gr

g/dl) leve

irubin (m

6.818

pB*

groupIII

4

roupIIIb

el among t

g/dl) amo

b

the

ong

Results

*signifi

Figure

*signif

Figuregroup

1

1

2

2

1

2

3

4

5

6

7

gl

icant P as co

e (5): Com

ficant P as

e (6): Com

0

5

10

15

20

25

0

10

20

30

40

50

60

70

%

gm/dl

ompared to

mparison

compared

mparison

16.95263158

control

53.09

control

control

of hemog

d to contro

of packed

17.115

G

groupIIa

52.45

groupIIa

89

globin lev

ol

d cell volu

16.3114

Group

HbGroupB*

groupIIb

50.83

PCVGroup

groupIIb

vel among

ume (%)

4.48947368

*

groupIIIa

45.54

B*

groupIIIa

g the studi

among th

14.075

groupIIIb

43.72

groupIIIb

ied group

he studied

p

d

Results

Figure

*signif

Figure

‐

1

1

2

10

e (7): Com

ficant P as

e (8): Com

0

5

10

15

20

25

30

‐5

0

5

10

15

20

000/cmm

%

mparison

compared

mparison

17.85

control

3.3

control

of total le

d to contro

of staff. C

15.36

groupIIa

7.35

groupIIa

90

eucocytic

ol

Count am

15.73

Group

TLC

groupIIb

6.1

Group

StaffGroupA

groupIIb

count am

mong the s

16.8751

groupIIIa

9.65

A*

groupIIIa

mong the s

studied gr

15.335

a group

5.55

groupIIIb

studied gr

roup

IIIb

b

roup

Results

*signif

Figure

*signif

Figuregroup

1

2

3

4

5

1

1

2

2

3

10

ficant P as

e (9): Com

ficant P as

e (10): Co

0

100

200

300

400

500

0

5

10

15

20

25

30

000/cmm

%

compared

mparison

compared

omparison

332.75

control

16.085

control

d to contro

of platele

d to contro

n of red c

244.9

Group

groupIIa

18.94

groupIIa

91

ol

ets counts

ol

cell distrib

237.85

Group

PlatelepA* and

groupIIb

18.39

Group

RDWGroupA

groupIIb

s among t

bution wid

181.55

etsd Group

groupIIIa

20.125

WA*

groupIIIa

the studie

dth amon

222.25

B*

groupIIIb

18.95

groupIIIb

d group

ng the stud

b

died

Results

*signif

Figuregroup

*signif

Figuregroup

0

20

40

60

80

m

m

ficant P as

e (11): Co

ficant P as

e (12): Co

0

20

40

60

80

100

120

mmHg

mHg

compared

omparison

compared

omparison

40.145

control

88.06

control

d to contro

n of oxyge

d to contro

n of carbo

52.685

G

groupIIa

47.715

groupIIa

92

ol

en tension

ol

on dioxid

38.495

Pco2GroupA

groupIIb

89.275

Group

PO2Group

groupIIb

n (mm Hg

e tension

42.97

*

groupIIIa

63.79

2A*

groupIIIa

g) among

among th

36.285

groupIIIb

90.315

groupIIIb

the studi

he studied

ied

d

Results

*signif

Figure

*signif

Figure

1

1

2

2

3

6.8

6.9

7

7.1

7.2

7.3

7.4

7.5

7.6

ficant P as

e (13): Co

ficant P as

e (14): Co

0

5

10

15

20

25

30

c

mEq/L

compared

omparison

compared

omparison

21.345

control

7.391

7

ontrol gr

d to contro

n of bicar

d to contro

n of pH a

22

G

groupIIa

7.23635

Gr

roupIIa g

93

ol

rbonate le

ol

mong the

22.71

Group

HCO3GroupB

groupIIb

7.38457.3

Group

pHroupA*

roupIIb g

evel amon

e studied g

19.15

*

groupIIIa

06315789

groupIIIa

ng the stud

group

22.91

groupIIIb

7.4065

groupIIIb

died grou

ups

Results

*signif

Figure

‐8

‐6

‐4

‐2

0

2

4

ficant P as

e (15): Co

compared

omparison

‐1.16

control

d to contro

n of base

‐3.82

groupIIa

94

ol

deficit/ex

‐1.68

BE/BD 1

BE/Grou

groupIIb

xcess amo

‐5.965

/BDup A*

groupIIIa

ng the stu

‐2.085

groupIIIb

udied gro

b

up

Results

95

C-Correlations

1-Correlation between serum glucose level (mg/dl) and total serum bilirubin level (mg/dl) bilirubin:

A- Correlation between serum glucose level TSB in control group (groupI):

Table (18): No significant correlation between serum glucose levels TSB in control group (group I)

Glucose TSB

Glucose Pearson Correlation 1 .416

Sig. (2-tailed) .068

TSB Pearson Correlation .416 1


Figure (16): No significant correlation between serum glucose level TSB in control group (group I)

Results

96

B- Correlation between serum glucose (mg/dl) levels TSB (mg/dl) in group II on admission (group IIa):

Table(19): A significant positive correlation between serum glucose level and total serum bilirubin in group II on admission

Glucose1 TSB1

Glucose1 Pearson Correlation 1 .463*


TSB1 Pearson Correlation .463* 1


Figure (17): A significant positive correlation between serum glucose level and total serum bilirubin in group II on admission

Results

97

C- Correlation between serum glucose (mg/dl) levels TSB (mg/dl) in groupIII on admission (groupIII a) Table (20): No significant correlation between serum glucose (mg/dl) levels and TSB (mg/dl) in groupIII on admission (groupIII a)

Glucose1 TSB1

Glucose1 Pearson Correlation 1 -.120


TSB1 Pearson Correlation -.120 1


Figure (18): No significant correlation between serum glucose (mg/dl) levels and TSB (mg/dl) in groupIII on admission (group IIIa)

Results

98

2-Correlation between gestational age and total leucocytic count A- Correlation between gestational age and total leucocytic count in control group (group I): Table (21): No significant correlation between gestational age and total leucocytic count in control group (group I)

GA(WKs) TLC

GA(WKs) Pearson Correlation 1 .023


TLC Pearson Correlation .023 1


Figure (19): No significant correlation between gestational age and total leucocytic count in control group (Group I)

Results

99

B- Correlation between gestational age and total leucocytic count group II on admission (group IIa) Table (22): No significant correlation between gestational age and total leucocytic count group II on admission (group IIa)

GA(WKs) TLC1



TLC1 Pearson Correlation .008 1


Figure (20): No significant correlation between gestational age and total leucocytic count in group II on admission (group IIa)

Results

100

C-Correlation between gestational age and total leucocytic count in groupIII on admission (group IIIa) Table (23): No significant correlation between gestational age and total leucocytic count in groupIII on admission (group IIIa)

GA(WKs) TLC1



TLC1 Pearson Correlation .022 1


Figure (21): No significant correlation between gestational age and total leucocytic count in groupIII on admission (group IIIa)

Results

101

3-Correlations between staff count and gestational age: A- Correlations between staff count and gestational age in control group (group I) Table (24): No significant correlation between staff count and gestational age in control group (group I)

GA(WKs) staff



staff. Pearson Correlation .145 1


Figure (22): No significant correlation between staff count and gestational age in control group (group I)

Results

102

B-Correlations between staff count and gestational age in group II on admission (group IIa) Table (25): No significant correlation between staff count and gestational age in group II on admission (group IIa)

GA(WKs) staff.1



staff.1 Pearson Correlation .033 1


Figure (23): No significant correlation between staff count and gestational age in group II on admission (group IIa)

Results

103

C-Correlations between staff count and gestational age in groupIII on admission (group IIIa) Table (26): No significant correlation between staff count and gestational age in groupIII on admission (group IIIa)

GA(WKs) staff.1



N 20 20

staff.1 Pearson Correlation .032 1


N 20 20

Figure (24): No significant correlation between staff count and gestational age in groupIII on admission (group IIIa)

Results

104

4-Correlation between reticulocytic index and gestational age

A-Correlation between Reticulocytic index and gestational age in control group (group I)

Table (27) No significant correlation between reticulocytic index and gestational age in control group (group I)

GA(WKs)

RETICULOCYT

E INDEX



RETICULOCYTE INDEX Pearson Correlation .227 1


Figure (25): No significant correlation between reticulocytic index and gestational age in control group (group I)

Results

105

B-Correlation between Reticulocytic index and gestational age in group II on admission (group IIa) Table (28): A significant positive correlation between reticulocytic index and gestational age in group II on admission (group IIa)

GA(WKs)

RETICULOCYT

E INDEX

GA(WKs) Pearson Correlation 1 .504*


RETICULOCYTE INDEX Pearson Correlation .504* 1


*. Correlation is significant at the 0.05 level (2-tailed).

Figure (26): A significant positive correlation between Reticulocytic index and gestational age in group II on admission (group IIa)

Results

106

C- Correlation between reticulocytic index and gestational age in groupIII on admission (group IIIa) Table (29): No significant correlation between reticulocytic index and gestational age in groupIII on admission (group IIIa)

GA(WKs)

RETICULOCYT

E INDEX



RETICULOCYTE INDEX Pearson Correlation .105 1


Figure (27): No significant correlation between reticulocytic index and gestational age in groupIII on admission (group IIIa)

Results

107

5-Correlations between total serum bilirubin and gestational age A- Correlations between total serum bilirubin and gestational age in control group (group I) Table (30): No significant correlation between total serum bilirubin and gestational age in control group (group I)

GA(WKs) TSB



TSB Pearson Correlation .058 1


Figure (28): No significant correlation between total serum bilirubin and gestational age in control group (group I)

Results

108

B- Correlations between total serum bilirubin and gestational age in group II on admission (group IIa) Table (31): No significant correlation between total serum bilirubin and gestational age in group II on admission (group IIa)

GA(WKs) TSB1

GA(WKs) Pearson Correlation 1 -.026




Figure (29): No significant correlation between total serum bilirubin and gestational age in group II on admission (group IIa)

Results

109

C- Correlations between total serum bilirubin and gestational age in groupIII on admission (group IIIa) Table (32): No significant correlation between total serum bilirubin and gestational age in groupIII on admission (group IIIa)

GA(WKs) TSB1

GA(WKs) Pearson Correlation 1 -.134




Figure (30): No significant correlation between total serum bilirubin and gestational age in groupIII on admission (group IIIa)

Discussion

110

Discussion The presence of diabetes before pregnancy is well known to be a risk

factor for adverse neonatal outcomes, including increased rates of perinatal

mortality, congenital anomaly, and macrosomia (Walkinshaw, 2005). In 1989, the St. Vincent Declaration in Europe made it a healthcare goal

to improve outcomes of diabetic pregnancies such that the incidence of adverse

outcomes approached those of the general population. Since 1989, care of

diabetes in general and during pregnancy has changed; however, population-

based studies show that the goals of the St. Vincent Declaration have not been

reached (Platt et al., 2002).

The present study tried to investigate the effect of maternal diabetes (both

gestational and pregestational diabetes) on some hematological and biochemical

parameters of their offspring, and the effect of treatment and admission in

NICU on these parameters.

Serum glucose level, serum calcium, serum bilirubin (both total and

direct bilirubin levels), complete blood count (CBC), arterial blood gases

(ABG) were determined in 60 newborn infants , fulfilled the criteria for the

study and classified into 3groups:

Group I (control group) which contained twenty healthy neonates.

Group II which contained twenty infants of diabetic mothers whose mothers

had pregestational diabetes (both type I and type II).

Group III which contained twenty infants of diabetic mothers whose mothers

had gestational diabetes mellitus.

Both group II and III are infants admitted to NICU due to any outcome of

maternal diabetes and the variables under investigation were measured twice,

on admission (group IIa ,group IIIa) and before discharge (group IIb ,group

IIIb).For control group measurements were performed once just after birth.

Discussion

111

In the present study, serum glucose level significantly increased in the

same group before discharge than on admission; in group II (84.25±16.049

mg/dl before discharge and 49.95±20.493 mg/dl on admission), and group III

(88.15±13.816 mg/dl before discharge and 65.45±41.140 mg/dl on admission).

Serum glucose level was significantly decreased in group II and group III

on admission as compared to control group (84.25±14.414 mg/dl) (table 10,

figure1), with no significant difference between serum glucose in group II and

group III before discharge and control group (table 14, figure1).

There was a significant positive correlation in group II on admission

between serum glucose level (mg/dl) and total serum bilirubin level (mg/dl)

(table 19, figure 17).

The alterations in maternal metabolism resulting from diabetes mellitus

causes excess provision of maternal metabolic fuels to the fetus, resulting in

pancreatic beta-cell hypertrophy, hyperplasia, fetal and neonatal

hyperinsulinism .Hypoglycaemia is more likely to occur in macrocosmic IDMs

because hyperinsulinism is responsible for both fetal overgrowth and

hypoglycaemia. Several studies also suggest that these IDM may fail to release

glucagon or catecholamine in response to hypoglycaemia; these hormonal

alterations result in both increased glucose clearance and diminished glucose

production (Persson, 2009).

Glucose production rates vary from attenuated to normal, likely,

reflecting differences in maternal glycemic control. The Hyperglycemia and

Adverse Pregnancy Outcome (HAPO) study of around 25,000 non-diabetic

pregnancies revealed strong associations between glucose values and increased

fetal size and hyperinsulinemia at birth - findings adding strong support to the

maternal hyperglycemia - fetal hypinsulinism theory. Mothers with the highest

Discussion

112

fasting glucose had infants with the highest frequency of clinical neonatal

hypoglycaemia (Persson, 2009).

Vela-Huerta et al., (2008) concluded that insulin levels and insulin

resistance were significantly higher in IDMs. The trend of higher leptin levels in

IDMs than infants of non diabetic mothers (INDMs) shows that leptin could be

related to insulin resistance in these infants. This is in agreement with Westgate

et al., (2006) who demonstrated raised cord insulin and leptin concentrations

in offspring of mothers with type 2 diabetes and GDM.

Maayan-Metzger et al., (2009) demonstrated that infants born to

diabetic mothers tend to have a high rate of hypoglycemia on the first day of life

when a relatively high cut-off point (47 mg/dl) is used, and should be closely

monitored. With presumably tighter control of gestational diabetes, the risk of

symptomatic hypoglycemia appears diminished. If glucose monitoring of

asymptomatic newborns is to be performed, it needs only be done in the first 2

hours of life (Van Howe and Storms, 2006).

In the current study serum calcium levels were significantly increased in

the same group before discharge than on admission in group II (8.59±1.002

mg/dl before discharge and 7.68±1.348 mg/dl on admission), and group III

(8.71±1.173 mg/dl before discharge and 7.34±1.203 mg/dl on admission).

Serum calcium level was significantly decreased in group II and group III

on admission as well as before discharge as compared to control group

(9.80±.894 mg/dl) (table 10,14; figure2).

Hypocalcaemia is a common problem among IDMs during the neonatal

period. This usually occurs in association with hyperphosphatemia and

occasionally with hypomagnesemia (Barnes-Powell, 2007).

Discussion

113

Banerjee et al. (2003) suggested a possible mechanism for

hypocalcaemia in infants of diabetic mothers; poor diabetic control leads to

glycosuria and consequent increased urinary loss of magnesium and therefore a

low maternal blood magnesium concentration, consequently maternal

hypomagnesaemia leads to fetal hypomagnesaemia. The paradoxical block of

PTH release under magnesium deficiency seems to be mediated through a

mechanism involving an increase in the activity of G alpha subunits of

heterotrimeric G-proteins with consequent hypoparathyroidism, causing

neonatal hypocalcaemia (Quitterer et al., 2001).

Moreover, IDMs exhibit hypomagnesemia and hypocalcemia, urinary

excretion of calcium and magnesium is reduced. The basis for reduced excretion

of calcium and magnesium involves increased tubular transport activity and

possibly increased sensitivity of these mechanisms to PTH (Bond et al., 2005).

Parathormone concentrations are significantly lower in IDM during the

first 4 days of life. This may be a result of hypomagnesaemia, which limits

parathormone secretion even in the presence of hypocalcaemia; high incidence

of birth asphyxia and prematurity in infants of diabetic mothers are also

contributing factors (Alam et al. 2006).

Asphyxia is associated with delayed introduction of feeds, increased

calcitonin production, increased endogenous phosphate load, and alkali therapy

all may contribute to hypocalcemia. In prematurity there is poor intake,

decreased responsiveness to vitamin D, increased calcitonin, and

hypoalbuminemia leading to decreased total but normal ionized calcium

(Lapillonne et al., 2008).

Also, there may be diminished end-organ responsiveness to hormonal

regulation of mineral homeostasis, although the functional capacity of the gut

Discussion

114

and kidney improves rapidly within days after birth (Egbuna and Brown,

2008).

In the present work, there was no significant difference between TSB or

DSB within the same group before discharge compared to level on admission;

in group II (TSB was 7.89±4.197 mg/dl before discharge and 9.80±5.807 mg/dl

on admission; DSB was 0.74±.446 mg/dl before discharge and 1.42±2.857

mg/dl on admission) and group III (TSB was 6.82±4.068 mg/dl before

discharge and 5.81±3.898 mg/dl on admission; DSB was 0.64±.343 mg/dl

before discharge and 0.56±.239 mg/dl on admission).

TSB was higher in IDMs from PGDM than IDMs from GDM (table 1,

figure 4). There was a significant increase in TSB in group II and group III both

on admission and before discharge compared to control group (2.79±1.261

mg/dl) (table 12,16; figure 3) .

There was no significant difference in DSB between group II and

groupIII neither on admission nor before discharge and the control group

(0.80±.433 mg/dl), as shown in (table 15, 19; figure 4).

Moreover, there was no significant correlation between TSB and

gestational age in group II , group III on admission and control group ,as shown

in (tables 30, 31, 32; figures 28, 29, 30).

At any time in the infant's first few days after birth, the serum bilirubin

level reflects a combination of the effects of bilirubin production, conjugation,

and enterohepatic circulation. An imbalance between bilirubin production and

conjugation is fundamental in the pathogenesis of neonatal hyperbilirubinemia

(Reiser, 2004).

Discussion

115

Deficient UGT1A1 activity, with impairment of bilirubin conjugation,

has long been considered a major cause of physiologic jaundice. In human

infants, the early postnatal increase in serum bilirubin appears to play an

important role in the initiation of bilirubin conjugation (Wang et al., 2006).

In contrast to the current study Jaber, (2006) found that total bilirubin

was significantly elevated in GDM group compared to PGDM group, with total

bilirubin levels higher than reference range in all groups of IDM.

The rate of prematurity in infants of diabetic mothers is five times that of

the general population (Michael Weindling, 2009). Hyperbilirubinemia in

preterm infants is more prevalent, more severe, and its course more protracted

than in term neonates, as a result of exaggerated neonatal red cell, hepatic, and

gastrointestinal immaturity. The postnatal maturation of hepatic bilirubin uptake

and conjugation may also be slower in premature infants. In addition, a delay in

the initiation of enteral feedings so common in the clinical management of sick

premature newborns may limit intestinal flow and bacterial colonisation

resulting in further enhancement of bilirubin enterohepatic circulation

(Cashore, 2000). Ligandin, the predominant bilirubin-binding protein in the

human liver cell, is deficient in the liver of newborn monkeys. It reaches adult

levels in the monkey by 5 days of age, coinciding with a fall in bilirubin levels

(Rigato et al., 2005).

Moreover; polycythemia frequently occurs in IDM, and the normal

breakdown of this increased erythrocyte mass also causes hyperbilirubinemia

(Pappas and Delaney-Black, 2004). There is increased haemoglobin

breakdown and bilirubin production. The increased rate of erythrocyte

breakdown in IDM may be linked to altered erythrocyte membrane composition

that results from changes in maternal fuel availability (Winkler et al., 2008).

Discussion

116

In the present work, group II showed a significant decrease in RBCs

count before discharge compared to RBCs count on admission (5.07±.774

million/cmm before discharge and5.27±.968 million/cmm on admission);

however there was no significant difference in RBCs count within group III

before discharge compared to RBCs count on admission (4.35±.865

million/cmm before discharge and 4.40±1.097 million/cmm on admission).

There was significant decrease in RBCs count in group II and group III

both on admission and before discharge compared to control group (5.34±.846

million/cmm) (table13) (table 17)

In the present study, in group II there was a significant decrease in

hemoglobin before discharge compared to level on admission (16.31±3.224

gm/dl before discharge and 17.12±3.828 gm/dl on admission), however in

group III there was no significant difference in hemoglobin value before

discharge compared to that measured on admission (14.08±3.288 gm/dl before

discharge and 14.49±4.719 gm/dl on admission).

Although there was no significant difference in Hb between group II and

group III on admission and the control group (16.71±2.495 gm/dl)(table 13,

figure 5), there was significant decrease in Hb in group II and group III before

discharge compared to control group as shown in (table 17, figure 5).

In the present study there was no significant difference in PCV within

the same group before discharge compared to values on admission neither in

group II (50.83±10.780% before discharge and 52.45±11.807% on admission),

nor in group III (43.72±11.179% before discharge and 45.54±13.936% on

admission).

Discussion

117

There was no significant difference in PCV in group II and group III on

admission compared to control group (53.09±7.168%) (table 13; figure 6),

however there was significant decrease in PCV in group II and group III before

discharge compared to control group (table 17; figure 6).

Several factors may contribute to polycythemia observed in group II .

Insulin itself may promote erythropoiesis. Insulin, at levels found in IDMs, can

stimulate growth of late erythroid progenitors in tissue culture. There is an

inverse changes of circulating fetal insulin like growth factor 1 ( IGF-1) and

insulin like growth factor binding protein-1 (IGFBP-1 ) at birth with decrease

in circulating IGFBP-1 and an increase in circulating IGF-1(Lindsay et al.,

2007).

IGF-1 stimulates Hypoxia-inducible factor (HIF)-1 transcription and

translation (Slomiany and Rosenzweig, 2007).HIF-1 and HIF-2 are

heterodimeric transcription factors permits the activation of genes essential to

cellular adaptation to low oxygen conditions including the vascular endothelial

growth factor (VEGF), erythropoietin and glucose transporter-1(Déry et al.,

2005).

Although under basal conditions the fetal kidneys are the main site of

erythropoietin (EPO) production, during hypoxia there is an important role of

the placenta. Teramo and Widness, (2009) reported that amniotic fluid EPO

levels have been shown to increase exponentially during fetal hypoxia in

diabetic pregnancies.

Tissue hypoxia is the major stimulus of EPO synthesis in fetuses and

adults. Since EPO does not cross the placenta and is not stored, fetal plasma and

amniotic fluid levels indicate EPO synthesis and elimination. Acutely, the rate

and magnitude of the increase in plasma EPO levels correlate with the intensity

of hypoxia.

Discussion

118

In fetuses of diabetic mothers, hypoxia is the result of an increased

affinity of oxygen for glycosylated hemoglobin in the mother. The

hyperglycaemic environment also results in erythroblastosis in the fetus which

is accompanied by a delay in the switch from embryonic to fetal hemoglobin

chain production (Al- Mufti et al., 2004).

However ,Pappas and Delaney-Black, (2004) found that polycythemia

does not correlate with higher maternal hemoglobin A1 concentration or with

increased infant weight percentile, but it correlates with neonatal

hypoglycaemia .

During periods of hypoxia, the fetus is reliant on the activation of a

growth-driving cascade, the hypoxia-inducible factor (HIF) cascade. The

upregulation of HIF in hypoxic conditions leads to expression of genes

encoding vascular endothelial growth factor, thus increasing vascularization, as

well as erythropoietin, to increase red blood cell production for the transport of

oxygen. It also results in increased expression of glucose transporters and

glycolytic enzymes. Unfortunately in the hypoxic condition of fetuses of

diabetic mothers, glucose is already present, in abundance. This hyperglycemia,

which initially is enhanced by HIF, causes a negative feedback of the hypoxia

inducible factor cascade by degrading HIF (Lampl & Jeanty, 2004). Thus, the

fetus is faced with a conundrum due to the overly abundant glucose availability

and inevitable hypoxia. Consequences of hypoxia include increasing the level of

glucose available for neurons, with glucose signalling its own sufficiency, thus

prematurely turning the adaptive mechanisms off, and starving the body and

brain of oxygen (Lampl & Jeanty, 2004).

Axelsson et al., (2005) showed that leptin level may be a predictor of

EPO sensitivity. The effect could be either direct stimulation of erythropoiesis

or indirect stimulation by associated adipokines.

Discussion

119

Atègbo et al., (2006) demonstrated that GDM is linked to the down-

regulation of adiponectin and up-regulation of leptin and inflammatory

cytokines.

In the present work there was no significant difference in MCV,MCH and

MCHC within the same group before discharge compared to values on

admission neither in group II (table 5 ), nor in group III (table 9).

There was significant decrease in MCV, MCH and MCHC in group II

and group III both on admission and before discharge compared to control

group (tables 13, 17).

In the present study there was no significant difference in retics within the

same group before discharge compared to values on admission neither within

group II (2.91±2.360% before discharge and 3.11±2.566% on admission) nor

group III (2.31±1.051% before discharge and 2.41±1.280% on admission).

There was significant increase in retics in group II and group III both on

admission and before discharge compared to control group (1.43±.892%)

(tables 13, 17).

There was a significant positive correlation between reticulocytic index

and gestational age in group II on admission (table 28, figure 26).

Ervasti et al., (2008) found a positive correlations between EPO and the

percentage of hypochromic red blood cells and reticulocytes. Thus, in newborn

cord blood, the higher number of red cells and reticulocytes with lower Hb

content may have impaired the oxygen carrying capacity that has been a trigger

for EPO production. Furthermore, signs of lower hemoglobinization of red cells

are associated with low umbilical vein pH in the newborns, indicating an

increased risk of birth asphyxia.

Discussion

120

In the present study, although there was no significant difference in RDW

within the same group before discharge compared to values on admission in

group II (18.39±4.290% before discharge and 18.94±5.213%on admission),

there was a significant decrease in RDW within groupIII before discharge

compared to values on admission (18.95±3.499% before discharge and

20.13±3.916% on admission)

There was a significant increase in RDW in group II and group III on

admission compared to control group (16.08±2.994%) (table 13, figure 10),

however there was no significant difference in RDW in group II ,group III

before discharge, and control group (table 17; figure 10).

Red cell distribution width is a quantitative measure of anisocytosis, the

variability in size of the circulating erythrocytes. It is routinely measured by

automated haematology analyzers and is reported as a component of the

complete blood count. Red cell distribution width is typically elevated in

conditions of ineffective red cell production (such as iron deficiency, B12 or

folate deficiency, and hemoglobinopathies), increased red cell destruction (such

as hemolysis), or after blood transfusion. Conceivably, RDW may represent an

integrative measure of multiple pathologic processes in heart failure (e.g.,

nutritional deficiencies, renal dysfunction, hepatic congestion, inflammatory

stress), explaining its association with clinical outcomes (Ozkalemkas et al.,

2005).

In a study by Felker et al., (2007) RDW was found to be a very strong

marker associated with heart failure pathophysiology. Red cell distribution

width also may be related to other known markers of prognosis in heart failure,

such as inflammatory cytokines. Inflammatory cytokines have been shown to be

predictors of prognosis in heart failure, and also may impact bone marrow

function and iron metabolism . Proinflammatory cytokines have been found to

Discussion

121

inhibit erythropoietin-induced erythrocyte maturation, which is reflected in part

by an increase in RDW. Future studies that carefully evaluate RDW in the

context of more complete evaluation of iron metabolism and markers of

inflammation in heart failure patients may provide further insight into the

mechanisms of the interaction between the hematologic and cardiovascular

systems.

In the present study there was no significant difference in TLC within the

same group before discharge compared to count on admission neither in group

II (table 5) nor in group III (table 9).

There was no significant difference in TLC between group II and group III

neither on admission nor before discharge as compared to control group (tables

13, 17; figure 7).

No significant correlation was found between total leucocytic counts and

gestational age in group II, groupIII and control group; on admission (tables 21,

22, 23; figures 19, 20, 21).

In the present work, group II showed no significant difference in staff

PMNL count before discharge compared to count on admission

(6.10±5.973%before discharge and 7.35±5.314 %on admission), while in group

III there was significant decrease in staff PMNL count before discharge

compared to count on admission (5.55±5.652% before discharge and

9.65±7.358% on admission).

There was significant increase in staff in group II and group III on

admission compared to control group (table 13; figure 8) with no significant

difference in staff PMNL count between the studied groups before discharge

(table 17; figure 8).

Discussion

122

No significant correlation was found in group II, group III on admission

and control group between staff PMNL and gestational age (tables 24, 25, 26;

figures 22, 23, 24).

In the present study there was no significant difference in segmented

PMNL count within the same group before discharge compared to count on

admission neither within group II (48.00±10.214% before discharge and

48.00±10.926% on admission), nor within group III (52.90±11.652% before

discharge and 49.05±10.211% on admission).

There was significant decrease in segmented PMNL count in group II and

group III on admission compared to control(55.50±6.613%)(table 13 ),

however there was no significant difference in segmented PMNL count between

group II , group III before discharge and control (table 17 ).

Mimouni et al., (1986) demonstrated a significant "shift to the left” in

IDM's-LGA only. The usual cause of "shift to the left" such as maternal

hypertension or fever, respiratory distress syndrome, meconium aspiration,

neonatal asphyxia, sepsis, convulsions, or hypoglycemia could not explain this

finding. It is hypothesized that increased glucocorticoid secretion may possibly

play a role.

Mehta and Petrova,(2005) studied neutrophil functions in neonates

born to gestational diabetic mothers and concluded the impairment of cord

blood neutrophil motility and postphagocytic bactericidal capacity

independently from the insulin requirements for the maintenance of

normoglycemia during pregnancy.

In the present study there was no significant difference in platelets count

within the same group before discharge compared to count on admission

neither in group II (237.85±112.657X1000/cmm)before discharge and

Discussion

123

244.90±113.973 X1000/cmm on admission), nor group III (222.25±135.704

X1000/cmm before discharge and 181.55±106.119 X1000/cmm on admission).

There was significant decrease in platelets count in group II and group III

on admission and before discharge as compared to control (332.75±88.859

X1000/cmm), (table13; figure 9) (table 17; figure 9).

30% of patients in group III had anemia , shift to the left with toxic

granulation and thrombocytopenia.

Green et al., (1995), demonstrated that that in IDMs, increased

erythropoiesis is accompanied by decreased platelet counts. These data are

consistent with the theory of an erythropoietin-induced shift of fetal multipotent

stem cell differentiation toward erythropoiesis at the expense of thrombopoiesis.

In the present work there was a significant increase in PO2 within the

same group before discharge compared to value on admission both within

group II (89.28±4.322 mm Hg before discharge and 47.71±22.368 mm Hg on

admission) and group III (90.32±16.482 mm Hg before discharge and

63.79±25.185 mm Hg on admission).

There was a significant decrease in PO2 in group II and group III on

admission compared to control group (88.06±5.263 mm Hg), (table 11; figure

11), however there was no significant difference in PO2 between group II and

group III before discharge and control group(table 15; figure 11).

The low PO2 values in IDMs may be due to high incidence of

prematurity with reduced pulmonary functions or may be due to increased

incidence of RDS in premature IDMs.

Discussion

124

In the present work; group II showed a significant decrease in

PCO2within the same group before discharge compared to values on admission

(38.50±3.744 mm Hg before discharge and 52.69±19.187 mm Hg on

admission), however in group III there was no significant difference in PCO2

before discharge and on admission (36.29±13.367 mm Hg before discharge

and 42.97±24.030 mm Hg on admission).

There was significant increase in PCO2 in group II and group III on

admission as compared to control group (40.14±3.093 mm Hg) (table 11; figure

12). No significant difference in PCO2 between group II and group III before

discharge and control group (table 15; figure 12).

In the present study group II showed no significant difference in

HCO3within the same group before discharge compared to value on admission

(22.71±2.795 mEq/L before discharge and 22.00±4.677 mEq/L on admission).

In group III, there was significant increase in HCO3 within the same group

before discharge as compared to values on admission (22.91±3.429 mEq/L

before discharge and 19.15±5.284 mEq/L on admission).

There was no significant difference in HCO3 between group II and group

III on admission and control (21.35±2.067 mEq/L) (table 11), however there

was a significant increase in HCO3 in group II, group III before discharge and

control group (table 15; figure 13).

In the present work there was significant increase in pH within the same

group before discharge compared to values on admission both within group II

(7.38±.045 before discharge and 7.24±.156on admission) and within group III

(7.41±.083 before discharge and 7.31±.133 on admission).

There was a significant decrease in pH between group II and group III on

admission and control group(7.39±.028) (table 11), however there was no

Discussion

125

significant difference in pH between group II and group III before discharge and

control group (table 15).

In the present work group II showed no significant difference in BE/BD

within the same group before discharge compared to levels on admission (-

1.68±2.376 mEq/L before discharge and -3.82±6.742 mEq/L on admission) but

in group III there was significant increase in BE/BD within the same group

before discharge compared to values on admission (-2.08±2.060 mEq/L before

discharge and -5.97±5.116 mEq/L on admission).

There was a significant increase in BE/BD in group II and group III on

admission compared to control group (-1.16±.644 mEq/L) (table 11, figure

15).No significant difference in BE/BD between group II group III before

discharge and control group (table 15, figure 15).

The changes in acid base status is of respiratory type (respiratory

acidosis).This could be contributed to the fact that infants of diabetic mothers

are more likely to have respiratory symptoms in the newborn period from either

RDS (surfactant deficiency) or retained fetal lung fluid (transient tachypnea of

the newborn) especially after operative delivery (Barnes-Powell, 2007).

RDS occurs more frequently in IDMs (Infants of Diabetic Mothers)

because of later onset of maturity of the type II alveolar cells (Schumacher et

al., 2006) and is secondary to pulmonary surfactant deficiency. Fetal

hyperinsulinism is a key factor in the pathogenesis of RDS because insulin is

believed to antagonize the physiological maturing effect of cortisol.

Hyperinsulinism is also responsible for polycythemia, a condition inducing

persistent pulmonary hypertension which complicates the course of RDS (Nold

and Georgieff, 2007).

Summary and Conclusion

126

Summary and Conclusions

Diabetes mellitus during pregnancy increases fetal and maternal

morbidity and mortality. Infants born to mothers with glucose intolerance are at

an increased risk of morbidity and mortality related to the respiratory distress,

growth abnormalities, hyperviscosity secondary to polycythemia,

hyperbilirubinemia, hypoglycaemia, adverse neurodevelopment outcomes,

congenital anomalies, hypocalcaemia, hypomagnesaemia, and iron

abnormalities.

We conducted this study aiming to investigate the effect of maternal

diabetes on some hematological and biochemical parameters of their offspring

and the reversibility of changes in these parameters with admission to neonatal

intensive care unit(NICU).The study was carried on 60 neonates, their

gestational age ranged from 32-41 weeks. They were classified into three

groups:

Group I (control group): this group included 20 apparently healthy neonates,

their mothers are healthy, and have no diabetes or history of serious diseases.

Group II: this group included 20 IDMs from mothers with pregestational

diabetes (both type I and type II) and admitted to NICU for any complication of

maternal diabetes.

Group III: this group included 20 IDMs from mothers with gestational diabetes

and admitted to NICU for any complication of maternal diabetes.

For all subjects, serum glucose level, serum calcium level, total serum

bilirubin, direct serum bilirubin, arterial blood gases and complete blood count

were investigated. For control group; measurements were performed once just

after birth while for IDMs (both group II and III), measurements were

performed twice; on admission to NICU and before discharge.


127

Results were statistically analysed and revealed the following:

Serum glucose level was significantly increased in the same group before

discharge than on admission; in group II, and group III. Serum glucose level

was significantly decreased in group II and group III on admission as compared

to control group, with no significant difference between serum glucose in group

II and group III before discharge and control group. There was a significant

positive correlation in group II on admission between serum glucose level

(mg/dl) and total serum bilirubin level (mg/dl).

Serum calcium levels were significantly increased in the same group

before discharge than on admission in group II, and group III. Serum calcium

level was significantly decreased in group II and group III on admission as well

as before discharge as compared to control group.

There was no significant difference between TSB and DSB within the

same group before discharge compared to level on admission; in group II and

group III.TSB was higher in IDMs from PGDM than IDMs from GDM. There

was a significant increase in TSB in group II and group III both on admission

and before discharge compared to control group. There was no significant

difference in DSB between group II and groupIII neither on admission nor

before discharge and the control group. Moreover, there was no significant

correlation between TSB and gestational age in control group, group II group

III on admission.

In group II there was a significant decrease in hemoglobin before

discharge compared to level on admission, however in group III there was no

significant difference in hemoglobin value before discharge compared to that

measured on admission. Although there was no significant difference in Hb

between group II and group III on admission and the control group, there was


128

significant decrease in Hb in group II and group III before discharge compared

to control group.

There was no significant difference in PCV within the same group before

discharge compared to values on admission neither in group II, nor in group

III.There was no significant difference in PCV in group II on admission

compared to control group, however there was significant decrease in PCV

between group II and group III before discharge compared to control group.

No significant difference was observed in MCV, MCH and MCHC

within the same group before discharge compared to values on admission

neither in group II, nor in group III.There was significant decrease in MCV,

MCH and MCHC in group II and group III both on admission and before

discharge compared to control group.

There was no significant difference in retics within the same group before

discharge compared to values on admission neither within group II nor group

III.There was significant increase in retics in group II and group III both on

admission and before discharge compared to control group. There was a

significant positive correlation between reticulocytic index and gestational age

in group II on admission.

Although there was no significant difference in RDW within the same

group before discharge compared to values on admission in group II, there was

a significant decrease in RDW within groupIII before discharge compared to

values on admission .There was a significant increase in RDW in group II and

group III on admission compared to control group, however there was no

significant difference in RDW in group II ,group III before discharge, and

control group .

Group II showed no significant difference in staff PMNL count before

discharge compared to count on admission, while in group III there was


129

significant decrease in staff PMNL count before discharge compared to count

on admission. There was significant increase in staff in group II and group III

on admission compared to controls group with no significant difference in staff

PMNL count between the studied groups before discharge. No significant

correlation was found in group II, group III on admission and control group

between staff PMNL and gestational age.

There was no significant difference in platelets count within the same

group before discharge compared to count on admission neither in group II, nor

group III. There was significant decrease in platelets count in group II and

group III on admission and before discharge as compared to control.

Arterial blood gases measurements revealed that in IDMs the changes in

acid base status is of respiratory type (respiratory acidosis) with compensatory

increase in HCO3 levels.

In conclusion our results indicate that some of the biochemical changes in

IDMs (calcium and glucose) were improved with admission while for bilirubin

the rise persist within the same group .On the other hand when compared to

control, the reversibility in hypocalcaemia and hyperbilirubinemia tend to be

slower than the reversibility of hypoglycemia.

Polycythemia in group II of IDMs as compared to control was decreased

with discharge. The increase in reticulocytic index and the decrease in blood

indices persisted even before discharge.

RDW which indicates anisocytosis was more prolonged in group II than

group III.


130

The increase in staff PMNL count was improved while the decrease in

platelets count persisted even before discharge.

Recommendations:

1-Early diagnosis of hypoglycemia and hypocalcaemia is lifesaving and should

be expected in IDMs.

2-Respiratory complications in IDMs are reversible by proper and rapid

interference.

3-Further studies are recommended to investigate the required duration needed

for parameters that did not improve on admission and reversed back to normal.

4- RDW and its association with heart failure pathophysiology may be used as a

predictor for IDMs selection for having echocardiography.

References

131

-A-

Abu Sief I.Koraa S.Ibrahim GHussien A. (2007): Markers of oxidative stress and apoptosis in Infants of diabetic mothers’ .Paediatric master thesis. Faculty of medicine .Ain Shams University.

Abu-Sulaiman RM, Subaih B. (2004):

Congenital heart disease in infants of diabetic mothers: echocardiographic study. Pediatr Cardiol; 25(2):137-40.

Alam M, Raza SJ, Sherali AR, Akhtar AS. (2006):

Neonatal complications in infants born to diabetic mothers. J Coll Physicians Surg Pak.; 16:212-215.

Al-Mufti, R., Hambley, H., Farzaneh, F., & Nicolaides, K. H. (2004): Fetal and embryonic hemoglobins in erythroblasts from fetal blood and fetal cells enriched from maternal blood in pregnancies complicated by maternal diabetes mellitus. The Journal of Maternal and Fetal-Neonatal Medicine; 15(2): 109-114. Altirkawi K, Rozycki HJ. (2008):

Hypocalcemia is common in the first 48 h of life in ELBW infants. J Perinat Med.; 36(4):348-53.

Altinova AE, Toruner F, Bozkurt N, Bukan N, Karakoc A, Yetkin I, Ayvaz G, Cakir N, Arslan M.(2007):

Circulating concentrations of adiponectin and tumor necrosis factor-alpha in gestational diabetes mellitus. Gynecol Endocrinol.; 23(3):161-5.

Altman,D.(2005):

Comparing groups: three or more independent groups of observations in practical statistics for medical research. Chapman and Hall.

References

132

Amaral ME, Cunha DA, Anhê GF, Ueno M, Carneiro EM, Velloso LA, Bordin S, Boschero AC.(2004): Participation of prolactin receptors and phosphatidylinositol 3-kinase and MAP kinase pathways in the increase in pancreatic islet mass and sensitivity to glucose during pregnancy. J Endocrinol; 183(3):469-76. Andreasen KR, Andersen ML, Schant AL. (2004): Obesity and pregnancy. Acta Obstet. Gynecol. Scand.; 83:1022-1029.

Arikawe A P, Iyawe V (2006):

I Breathing Patterns in The Newborn And Related Cardiovascular Adjustments. Annals of Biomedical Sciences; 5:23-35.

Atègbo JM, Grissa O, Yessoufou A, Hichami A, Dramane KL, Moutairou K, Miled A, Grissa A, Jerbi M, Tabka Z, Khan NA.(2006):

Modulation of adipokines and cytokines in gestational diabetes and macrosomia. J Clin Endocrinol Metab;(10):4137-43.

Axelsson J, Qureshi AR, Heimbürger O, Lindholm B, Stenvinkel P, Bárány P. (2005):

Body fat mass and serum leptin levels influence epoetin sensitivity in patients with ESRD. Am J Kidney Dis.; 46(4):628-34.

Aydin Y, Berker D, Direktor N, et al.(2008):

Is insulin lispro safe in pregnant women: Does it cause any adverse outcomes on infants or mothers. Diab Res Clin Pract.; 80:444–448.

References

133

-B-

Bachar E, Ariav Y, Ketzinel-Gilad M, Cerasi E, Kaiser N, Leibowitz G.(2009):

Glucose amplifies fatty acid-induced endoplasmic reticulum stress in pancreatic beta-cells via activation of mTORC1 PLoS ONE; 4: e4954.

Balsyte, D, Schaffer, L, Burkhardt, T, et al. (2009):

Sonographic prediction of macrosomia cannot be improved by combination with pregnancy-specific characteristics. Ultrasound Obstet Gynecol .; 33:453-458.

Banerjee S, Mimouni FB, Mehta R, Llanos A, Bainbridge R, Varada K, Sheffer G. (2003):

Lower whole blood ionized magnesium concentrations in hypocalcemic infants of gestational diabetic mothers. Magnes Res.; 16(2):127-30.

Barbour LA, McCurdy CE, Hernandez TL, Kirwan JP, Catalano PM, Friedman JE. (2007):

Cellular mechanisms for insulin resistance in normal pregnancy and gestational diabetes. Diabetes Care. Suppl; 2:S112-9.

Barnes-Powell LL. (2007):

Infants of diabetic mothers: the effects of hyperglycemia on the fetus and neonate. Neonatal Netw; 26(5):283-90.

Beardsall K, Dunger D. (2007):

The physiology and clinical management of glucose metabolism in the newborn. Endocr Dev.; 12:124-37.

Belkacemi, L, Bedard, I, Simoneau, L, Lafond, J. (2005):

Calcium channels, transporters and exchangers in placenta: a review. Cell Calcium. ; 37:1-8.

References

134

Belo L, Caslake M, Santos-Silva A, Castro EM, Pereira-Leite L, Quintanilha A, Rebelo I .(2004):

LDL size, total antioxidant status and oxidised LDL in normal human pregnancy: a longitudinal study. Atherosclerosis; 177(2):391-399.

Ben-Haroush A, Chen R, Hadar E, Hod M, Yogev Y.(2007):

Accuracy of single fetal weight estimation at 29-34 weeks in diabetic pregnancies: can it predict large-for-gestational infants at term? .Am J Obstet Gynecol; 197:497.e1-6.

Ben-Haroush A, Yogev Y, Hod M. (2004):

Epidemiology of gestational Diabetes Mellitus and its association with Type 2 diabetes. Diabet Med.; 21:103–113.

Bernal-Mizrachi C, Xiaozhong L, Yin L, Knutsen RH, Howard MJ, Arends JJ et al.,. (2007):

An afferent vagal nerve pathway links hepatic PPARalpha activation to glucocorticoid-induced insulin resistance and hypertension. Cell Metab; 5:91–102.

Bernet-Buettiker V, Ugarte MJ, Frey B, Hug MI, Baenziger O, Weiss M. (2005):

Evaluation of a new combined transcutaneous measurement of PCO2/pulse oximetry oxygen saturation ear sensor in newborn patients. Pediatrics; 115(1):e64-8.

Bikle DD. (2007):

What is new in vitamin D: 2006-2007? Curr Opin Rheumatol; 19(4):383-8.

Bizzarro MJ, Colson E, Ehrenkranz RA. (2004):

Differential diagnosis and management of anemia in the newborn. Pediatr Clin North Am.; 51:1087-1107.

References

135

Blickstein I, Green T. (2007):

Umbilical cord blood gases. Clin Perinatol.; 34(3):451-9.

Bo S, Menato G, Villois P, Gambino R, Cassader M, Cotrino I, Cavallo-Perin P .(2009):

Iron supplementation and gestational diabetes in midpregnancy. Am J Obstet Gynecol.; 201: 158.e1-158.e6.

Bond H, Hamilton K, Balment RJ, Denton J, Freemont AJ, Garland HO, Glazier JD, Sibley CP. (2005):

Diabetes in rat pregnancy alters renal calcium and magnesium reabsorption and bone formation in adult offspring. Diabetologia; 48(7):1393-400.

Bond H, Sibley CP, Balment RJ, Ashton N. (2005):

Increased renal tubular reabsorption of calcium and magnesium by the offspring of diabetic rat pregnancy. Pediatr Res.; 57(6):890-5.

Boomsma CM, Eijkemans MJ, Hughes EG, Visser GH, Fauser BC, Macklon NS. (2006):

A meta-analysis of pregnancy outcomes in women with polycystic ovary syndrome.Hum Reprod Update; 12:673-83.

Bottalico JN. (2007):

Recurrent gestational diabetes: risk factors, diagnosis, management, and implications. Semin Perinatol.; 31:176-184.

Brankston GN, Mitchell BF, Ryan EA. (2004):

Resistance exercise decreases the need for insulin in overweight women with gestational diabetes mellitus. Am J Obstet Gynecol.; 190:188–193.

References

136

Bree AJ, Puente EC, Daphna-Iken D, Fisher SJ. (2009):

Diabetes increases brain damage caused by severe hypoglycemia. Am J Physiol Endocrinol Metab.; 297: 194-201.

Briana DD, Malamitsi-Puchner A. (2009): Reviews: adipocytokines in normal and complicated pregnancies.Reprod Sci.; 16(10):921-937. Brouillette RT, Waxman DH. (1997): Evaluation of the newborn's blood gas status. National Academy of Clinical Biochemistry. Clin Chem; 43(1):215-21.

Buchanan TA, Xiang AH. (2005):

Gestational diabetes mellitus. J Clin Invest ; 115:485–491.

Buchanan TA. (2001):

Pancreatic B-cell defects in gestational diabetes: Implications for the pathogenesis and prevention of type 2 diabetes. J Clin Endocrinol Metab.; 86:989-993.

Bulmer R, Hancock W. (1977):

Depletion of circulating T lymphocytes in pregnancy. Clin Exp Immunol ; 29: 302–307.

-C-

Cashore WJ. (2000):

Bilirubin and jaundice in the micropremie. Clin Perinatol; 27:171–9. Camadoo, L, Tibbott, R, Isaza, F.(2007): Maternal vitamin D deficiency associated with neonatal hypocalcaemic convulsions. Nutr J.; 19: 6-23.

References

137

Carr DB, Utzschneider KM, Hull RL, et al.(2006): Gestational diabetes mellitus increases the risk of cardiovascular in women with a family history of type 2 diabetes. Diabetes Care; 29:2078–2083. Cetin I, Nobile de Santis MS, Tarico E, et al. (2005) :

Maternal and fetal amino acid concentrations in normal pregnancies and pregnancies with gestational diabetes mellitus. Am J Obstet Gynecol; 192: 610–617.

Chan, SJ, Nakagawa, S, Steiner, DF. (2007):

Complementation analysis demonstrates that insulin cross-links both alpha subunits in a truncated insulin receptor dimer. J Biol Chem; 282:13754-13758.

Chang Y, Niu XM, Qi XM, Zhang HY, Li NJ, Luo Y.(2005):

Study on the association between gestational diabetes mellitus and tumor necrosis factor-alpha gene polymorphism Zhonghua Fu Chan Ke Za Zhi.; 40(10):676-8. Chen C (2005): Congenital Malformations Associated with Maternal Diabetes. Taiwanese Journal of Obstetrics and Gynecology ; 44: 1-7.

Chen RA, Goodman WG.(2004):

Role of the calcium-sensing receptor in parathyroid gland physiology. Am J Physiol Renal Physiol.; 286(6):F1005-11. Chen S, Beaton D, Nguyen N, Senekeo-Effenberger K, Brace-Sinnokrak E, Argikar U, Remmel RP, Trottier J, Barbier O, Ritter JK, et al. (2005): Tissue-specific, inducible, and hormonal control of the human UDP-glucuronosyltransferase-1 (UGT1) locus. J Biol Chem 280: 37547–37557.

Chen X, Scholl TO, Stein TP. (2006):

Association of elevated serum ferritin levels and the risk of gestational diabetes mellitus in pregnant women: the Camden study. Diabetes Care; 29: 1077–1082.

References

138

Cheung NW, Byth K.(2003):

The population health significance of gestational diabetes. Diabetes Care; 26:2005–2009.

Cheung NW, Smith BJ, Henriksen H, et al. (2007):

A group-based healthy lifestyle program for women with previous gestational diabetes. Diab Res Clin Pract.; 77:333–334.

Chiruvolu A, Engle WD, Sendelbach D, Manning MD, Jackson GL.(2008):

Serum calcium values in term and late-preterm neonates receiving gentamicin. Pediatr Nephrol. ; 23(4):569-74.

Cody A,Koch S, Jeffrey L,Platt T.(2007):

cell recognition and immunity in the fetus and mother .Cellular Immunology ; 248: 12-17.

Coelho R, Wells J, Symth J, Semple R, O'Rahilly S, Eaton S, Hussain K.(2007):

Severe hypoinsulinaemic hypoglycaemia in a premature infant associated with poor weight gain and reduced adipose tissue. Horm Res.; 68(2):91-8.

Coll AP, Faroqi IS, O’rahilyS.(2007):

The hormonal control of food intake. Cell.; 129:251-262.

Colomiere M, Permezel M, Riley C, Desoye G, Lappas M. (2009) :

Defective insulin signaling in placenta from pregnancies complicated by gestational diabetes mellitus. European Journal of Endocrinology; 160:567-578.

Cooper MS, Gittoes NJ.(2008):

Diagnosis and management of hypocalcaemia. BMJ; 336:1298-302.

References

139

Costa E.(2005)

Hematologically important mutations: bilirubin UDP-glucuronosyltransferase gene mutations in Gilbert and Crigler-Najjar syndromes. Blood Cells Mol Dis.; 36(1):77-80.

-D-

Damanhouri LH, Dromey JA, Christie MR, Nasrat HA, Ardawi MS, Robins RA, Todd I.(2005):

Autoantibodies to GAD and IA-2 in Saudi Arabian diabetic patients. Diabet Med.; 22: 448 – 452.

D'Amour, P,Rakel, A, Brossard, JH, et al.(2006): Acute regulation of circulating parathyroid hormone (PTH) molecular forms by calcium: utility of PTH fragments/PTH(1-84) ratios derived from three generations of PTH assays. J Clin Endocrinol Metab.; 91:283-289.

De Leon DD, Stanley CA. (2007):

Mechanisms of Disease: advances in diagnosis and treatment of hyperinsulinism in neonates. Nat Clin Pract Endocrinol Metab.;3:57-68.

Dempsey EM, Barrington K.(2006):

Short and long term outcomes following partial exchange transfusion in the polycythaemic newborn: a systematic review. Arch Dis Child Fetal Neonatal Ed.; 91:F2-F6.

Déry MA, Michaud MD, Richard DE.(2005)

Hypoxia-inducible factor 1: regulation by hypoxic and non-hypoxic activators. nt J Biochem Cell Biol.;37(3):535-40.

Dheen ST, Tay SS, Boran J, Ting LW, Kumar SD, Fu J, Ling EA.(2009):

Recent studies on neural tube defects in embryos of diabetic pregnancy: an overview. Curr Med Chem.; 16:2345-2354.

References

140

DiCianni G, Miccoli R, Volpe L, et al. (2005) :

Maternal triglyceride levels and newborn weight in pregnant women with normal glucose tolerance. Diabet Med ; 22: 21–25.

Dickstein, Y, Ohel, I, Levy, A, et al. (2008):

Lack of prenatal care: an independent risk factor for perinatal mortality among macrosomic newborns. Arch Gynecol Obstet.; 277:511.

Dionne G, Boivin M, Séguin JR, Pérusse D, Tremblay RE. (2008):

Gestational diabetes hinders language development in offspring. Pediatrics. ; 122:1073-1079. Dodd JM, Crowther CA, Antoniou G, Baghurst P, Robinson JS.(2007): Screening for gestational diabetes: the effect of varying blood glucose definitions in the prediction of adverse maternal and infant health outcomes. Aust N Z J Obstet Gynaecol.; 47(4):307-12.

-E-

Egbuna OI, Brown EM. (2008):

Hypercalcaemic and hypocalcaemic conditions due to calcium-sensing receptor mutations. Best Pract Res Clin Rheumatol.; 22(1):129-48.

El Sheemy S.Ibrahim G.Atef S. Mohamed S. (2008):

Study of cord blood Adiponectin level and lipid profile in full term Infants of Diabetic Mothers Pediatric thesis .Faculty of medicine .Ain Shams University.

England LJ, Levine RJ, Qian C, Soule LM, Schisterman EF, Yu KF, et al.(2004):

Glucose tolerance and risk of gestational diabetes mellitus in nulliparous women who smoke during pregnancy. Am J Epidemiol;160:1205-1213.

References

141

Ericsson A, Säljö K, Sjöstrand E, Jansson N, Prasad PD, Powell TL, Jansson T.(2007):

Brief hyperglycaemia in the early pregnant rat increases fetal weight at term by stimulating placental growth and affecting placental nutrient transport. Physiol. 15; 581(Pt 3):1323-32.

Eriksson UJ.(2009):

Congenital anomalies in diabetic pregnancy. Semin Fetal Neonatal Med.; 14(2):85-93.

Ervasti M, Sankilampi U, Heinonen S, Punnonen K. (2008):

Novel red cell indices indicating reduced availability of iron are associated with high erythropoietin concentration and low ph level in the venous cord blood of newborns. Pediatr Res.; 64(2):135-40.

Ethier-Chiasson M, Forest JC, Giguère Y, Masse A, Marseille-Tremblay C, Lévy E, Lafond.(2008):

Modulation of placental protein expression of OLR1: implication in pregnancy-related disorders or pathologies. J.Reproduction; 136: 491-502.

-F-

Felker GM, Allen LA, Pocock SJ, Shaw LK, McMurray JJ, Pfeffer MA, Swedberg K, Wang D, Yusuf S, Michelson EL, Granger CB.(2007): CHARM Investigators. J Am Coll Cardiol; 50(1):40-7.

Fevery J.(2008): Bilirubin in clinical practice: a review. Liver Int; 28(5):592-605.

Freemark M.(2006):

.Regulation of Maternal Metabolism by Pituitary and Placental Hormones: Roles in Fetal Development and Metabolic Programming. Horm Res;65 (Suppl. 3):41-49.

References

142

-G- Georgieff MK.(2006):

The effect of maternal diabetes during pregnancy on the neurodevelopment of offspring. Minn Med.; 3:44-7.

Ghiadoni L, Penno G, Giannarelli C et al.(2008):

Metabolic syndrome and vascular alterations in normotensive subjects at risk of diabetes mellitus. Hypertension; 51:440-445.

Gilmartin AB, Ural SH, Repke JT.(2006):

Gestational diabetes mellitus. Rev Obstet Gynecol.; 1(3):129-34. Ginsberg HN, Zhang YL, Hernandez-Ono A.(2006): Metabolic syndrome: focus on dyslipidemia. Obesity; 14:41S-49S. Glazier, J. D. & T. Jansson.(2004): Placental transport in early pregnancy--a workshop report. Placenta, 25 Suppl A, S57-9 . Goff DC, Jr, D’Agostino, Rb JR, Haffner SM, Otvos JD. (2005): Insulin resistance and adiposity influence lipoprotein size and subclass concentrations. Results from the Insulin Resistance Atherosclerosis Study.Metabolism.; 54: 264-270. Grattan DR, Steyn FJ, Kokay IC, Anderson GM, Bunn SJ. (2008) Pregnancy-induced adaptation in the neuroendocrine control of prolactin secretion. J Neuroendocrinol; 20(4):497-507.

Green DW, Mimouni F, Khoury J.(1995):

Decreased platelet counts in infants of diabetic mothers. Am J Perinatol. Mar; 12(2):102-5.

References

143

Grissa O, Atègbo JM, Yessoufou A, Tabka Z, Miled A, Jerbi M, Dramane KL, Moutairou K, Prost J, Hichami A, Khan NA.(2007):

Antioxidant status and circulating lipids are altered in human gestational diabetes and macrosomia. Transl Res; 150 (3):164-71.

Gude, N. M., J. L. Stevenson, P. Murthi, S. Rogers, J.D. Best, B. Kalionis & R. G. King(2005): Expression of GLUT12 in the fetal membranes of the human placenta. Placenta; 26:67-72. Guven MA, Kilinc M, Batukan C, Ekerbicer HC, Aksu T. (2006): Elevated second trimester serum homocysteine levels in women with gestational diabetes mellitus Arch Gynecol Obstet; 274: 333-337.

-H-

Hadden DR, McLaughlin C.(2009):

Normal and abnormal maternal metabolism during pregnancy. Semin Fetal Neonatal Med; 14:66-71.

Haeri S, Khoury J, Kovilam O, Miodovnik M.(2008):

The association of intrauterine growth abnormalities in women with type 1 diabetes mellitus complicated by vasculopathy. Am J Obstet Gynecol.; (3):278.e1-5.

HansenA, Lars; Pedersen,L Oluf G.(2005):

Genetics of type 2 diabetes mellitus: status and perspectives. Diabetes Metab. Res. Rev; 17: 422-428.

Hare JW. (1994): Diabetes and pregnancy. In: Kahn CR, Weir GC, eds.Joslin’s Diabetes Mellitus, 13th edn. Philadelphia: Lea & Febiger;, pp. 889–99.

References

144

Harmancey R, Senard JM, Rouet P, Pathak A, Smih F.(2007):

Adrenomedullin inhibits adipogenesis under transcriptional control of insulin.Diabetes; 56: 553-563.

Hauguel-de Mouzon, S, Lepercq, J, Catalano, P. (2006):

The known and unknown of leptin in pregnancy. Am J Obstet Gynecol.; 194:1537-1545.

Hay WW Jr. (2006):

Placental-fetal glucose exchange and fetal glucose metabolism. Trans Am Clin Climatol Assoc.;117:321-39; discussion 339-40.

Heaney, RP. (2005):

The Vitamin D requirement in health and disease. J Steroid Biochem Mol Biol.; 97:13-19.

Hedderson MM, Ferrara A. (2008):

High blood pressure before and during early pregnancy is associated with an increased risk of gestational diabetes mellitus. Diabetes Care.; 31:2362–2367.

Henson, MC, Castracane VD. (2006):

Leptin in pregnancy: an update. Biol Reprod; 74:218-229.

Herrera E. (2005) : Metabolic changes in diabetic pregnancy. In: Djelmis J,Desoye G, Ivanisevic M, eds. Diabetology of Pregnancy. Basel:Karger; 2005: 34–45.

Holmes HJ, Lo JY, McIntire DD, Casey BM. (2010): Prediction of Diabetes Recurrence in Women with Class A1 (Diet-Treated) Gestational Diabetes. Am J Perinatol. Am J Perinatol. 27(1):47-52.

References

145

Horal M, Zhang Z, Stanton R, Virkamaki A, Loeken MR. (2004): Activation of the hexosamine pathway causes oxidative stress and abnormal embryo gene expression: involvement in diabetic teratogenesis. Birth Defects Res A Clin Mol Teratol 70:519–527.

Howarth, C, Gazis, A, James, D.(2007):

Associations of Type 1 diabetes mellitus, maternal vascular disease and complications of pregnancy. Diabet Med.; 24:1229-1243.

Hsu SC, Levine MA.(2004):

Perinatal calcium metabolism: physiology and pathophysiology. Semin Neonatol.; 9(1):23-36.

Huang C, Snider F, Cross JC. (2009):

Prolactin receptor is required for normal glucose homeostasis and modulation of beta-cell mass during pregnancy. Endocrinology; 150: 1618-1626.

Hume R, Burchell A, Fiona L.R. Williams, Daisy K.M. Koh.(2005):

Glucose homeostasis in the newborn .Early Human Development ; 81: 95-101

Hutton EK, Hassan ES. (2007):

Late vs early clamping of the umbilical cord in full-term neonates: systematic review and meta-analysis of controlled trials. JAMA; 297(11):1241-52.

-I-

Ira D. Goldfine*, Betty A. Maddux, Jack F. Youngren, Gerald Reaven, Domenico Accili, Vincenzo Trischitta, Riccardo Vigneri, and Lucia Frittitta.(2008): The Role of Membrane Glycoprotein PC-1/ENPP1 in the Pathogenesis of Insulin Resistance and Related Abnormalities Endocrine Reviews; 29 (1): 62-75

References

146

Irfan, S, Arain, TM, Shaukat, A, Shahid, A.(2004):

Effect of pregnancy on diabetic nephropathy and retinopathy. J Coll Physicians Surg Pak.; 14:75-78.

-J-

Jaber SM.(2006):

Metabolic hormones profile in 2 weeks old healthy infants of diabetic mothers. Saudi Med J.; 27(9):1338-45.

Jackson L, Williams FL, Burchell A, Coughtrie MW, Hume R.(2004):

Plasma catecholamines and the counterregulatory responses to hypoglycemia in infants: a critical role for epinephrine and cortisol. J Clin Endocrinol Metab.; 89(12):6251-6.

Jain A, Agarwal R, Sankar MJ, Deorari AK, Paul VK. (2008):

Hypocalcemia in the newborn. Indian J Pediatr. ;75(2):165-9.

Jansson T, Powell TL. (2006):

Human placental transport in altered fetal growth: Does the placenta function as a nutrient sensor? A Review. Placenta; 27: 91–97.

Järvela I, Juutinen J, Koskela P, et al. (2006) :

Gestational diabetes identifies women at risk for permanent Type 1 and Type 2 diabetes in fertile age. Predictive role of autoantibodies. Diabetes Care; 29: 607–612.

Jeevasankar M, Agarwal R, Chawla D, Paul VK, Deorari AK.(2008):

Polycythemia in the newborn. Indian J Pediatr.;75(1):68-72.

References

147

Jiang R, Manson JE, Meigs JB, Ma J, Rifai N, Hu FB.(2004):

Body iron stores in relation to risk of type 2 diabetes in apparently healthy women. JAMA 291 : 711 –717. Jovanovic L, Pettitt DJ.(2007): Treatment with insulin and its analogs in pregnancies complicated by diabetes. Diabetes Care.; 30 Suppl 2:S220-4. Jurczyńska J, Zieleniewski W. (2004): Clinical implications of occurrence of antithyroid antibodies in pregnant women and in the postpartum period. Przegl Lek.;61:864-867.

-K-

Kaissi A, Klaushofer K, Grill F. (2008):

Caudal regression syndrome and popliteal webbing in connection with maternal diabetes mellitus: a case report and literature review. Cases J.; 19:407.

Kalogeropoulou D, Lafave L, Schweim K, Gannon MC, Nuttall FQ.(2008):

Leucine, when ingested with glucose, synergistically stimulates insulin secretion and lowers blood glucose. Metabolism; 57: 1747-1752.

Kapoor RR, Flanagan SE, James C, Shield J, Ellard S, Hussain K.(2009): Hyperinsulinaemic hypoglycaemia. : Arch Dis Child. ; 94:450-457.

Kashanian M, Fazy Z, Pirak A.(2008):

Evaluation of the relationship between gestational diabetes and a history of polycystic ovarian syndrome.Diabetes Res Clin Pract.; 80:289-292.

Kasuga M.(2006):

Insulin resistance and pancreatic beta cell failure. J Clin Invest; 116: 1756–1760.

References

148

Khaldi N, Essid M, Malek I, Boujemaa C, Bouguila H, Nacef L, Ayed S.(2008):

Proliferative diabetic retinopathy inauguring gestational diabetes .Ann Endocrinol; 69: 449-452.

Khan SE, Haffner SM, Heise MA, et al. (2007):

Glycemic durability of rosiglitazone, metformin, or glyburide monotherapy. N Eng J Med.; 355:2427–2443.

Khan, NA.(2007):

Role of lipids and fatty acids in macrosomic offspring of diabetic pregnancy. Cell Biochem Biophys ; 48:79-88.

Khatun N, Latif SA, Uddin MM.Mymensingh.(2009):

Risk factors for the development of gestational diabetes mellitus. Med J.; 18:20-23.

Kim C, Herman WH, Vijan S.(2007):

Efficacy and cost of postpartum screening strategies for diabetes among women with histories of gestational diabetes mellitus. Diabetes Care; 30:1102-6.

Kim C, Liu T, Valdez R, Beckles GL.(2009):

Does frank diabetes in first-degree relatives of a pregnant woman affect the likelihood of her developing gestational diabetes mellitus or nongestational diabetes?Am J Obstet Gynecol. ;201(6):576.e1-6.

Knapp R and Miller M (1992): Tests of statistical significance: Analysis of variance in clinical epidemiology and biostatistics. Williams and Wilkins, Baltimol, p.293.

References

149

Kriketos AD, Greenfield JR, Peake PW, Furler SM, Denyer GS, Charlesworth JA, Campbell LV. (2004): Inflammation, insulin resistance, and adiposity: a study of first-degree relatives of type 2 diabetic subjects. Diabetes Care; 27: 2033–2040.

Kumar SD,Dheen ST,Tay SS. (2007):

Maternal diabetes induces congenital heart defects in mice by altering the expression of genes involved in cardiovascular development. Cardiovasc Diabetol. 30;6:34.

Kuźmicki M, Szamatowicz J, Kretowski A, Kuć P, Kretowski M, Wawrusiewicz N, Okruszko A, Leroith D, Górska M.(2006):

Evaluation of adiponectin and TNFalpha genes expression in women with gestational diabetes. Ginekol Pol.; 77(12):930-6.

Kwak SH, Kim HS, Choi SH, Lim S, Cho YM, Park KS, Jang HC, Kim MY, Cho NH, Metzger BE.(2008):

Subsequent pregnancy after gestational diabetes mellitus: frequency and risk factors for recurrence in Korean women.Diabetes Care.;31:1867–1871.

-L-

Lai E, Bikopoulos G, Wheeler MB, Rozakis-Adcock M, Volchuk A.(2008):

Differential activation of ER stress and apoptosis in response to chronically elevated free fatty acids in pancreatic beta-cells. Am J Physiol Endocrinol Metab.; 294:540–550

Lain K, Catalno P.(2007):

Metabolic Changes in Pregnancy. Clinical Obstetrics and Gynecology; 50: 938-948

Lambers TT, Bindels RJ, Hoenderop JG.(2006): Coordinated control of renal Ca2+ handling. Kidney Int.; 69(4):650-4

References

150

Lampl, M., & Jeanty, P. (2004):

Exposure to maternal diabetes is associated with altered fetal growth patterns: A hypothesis regarding metabolic allocation to growth under hyperglycemic-hypoxic conditions. American Journal of Human Biology;16: 237-263.

Lapillonne A, Kermorvant-Duchemin E.(2008):

Neonatal hypocalcemia Arch Pediatr.; 15:645-647.

Lapolla A, Dalfrà MG, FedeleD.(2009):

D.iabetes related autoimmunity in gestational diabetes mellitus: Is it important? Nutr Metab Cardiovasc Dis. 19(9):674-82.

Laura Lee T. Goree, Betty E. Darnell, Robert A. Oster, Marian A. Brown and Barbara A. Gower. (2009):

Associations of Free Fatty Acids With Insulin Secretion and Action Among African-American and European-American Girls and Women. Obesity advance online publication, Epub ahead of print

Laybutt DR, Preston AM, Akerfeldt MC, Kench JG, Busch AK, et al.(2007):

Endoplasmic reticulum stress contributes to beta cell apoptosis in type 2 diabetes. Diabetologia. 50:552–563.

Legro RS, Gnatuk CL, Kunselman AR, Dunaif A.(2005):

Changes in glucose tolerance over time in women with polycystic ovary syndrome: a controlled study. J Clin Endocrinol Metab ; 90:3236–3242,

Li R, Chase M, Jung SK, Smith PJ, Loeken MR. (2005):

Hypoxic stress in diabetic pregnancy contributes to impaired embryo gene expression and defective development by inducing oxidative stress.AmJ Physiol Endocrinol Metab ;289:E591–E599.

References

151

Li HH, Tang P, Ding SJ, Wang ZY. (2007):

The study on the relationship between the serum adiponectin and TNF-α and insulin resistance in the GDM patients. Maternal Child Health (Chin); 22: 921-923.

Limesand SW, Regnault TR, Hay WW Jr. (2004):

Characterization of glucose transporter 8 (GLUT8) in the ovine placenta of normal and growth restricted fetuses. Placenta. ; 25(1):70-7.

Lindsay JR, Nieman LK. (2005):

The hypothalamic-pituitary-adrenal axis in pregnancy: challenges in disease detection and treatment. Endocr Rev; 6: 775-799.

Lindsay RS, Westgate JA, Beattie J, Pattison NS, Gamble G, Mildenhall LF, Breier BH, Johnstone FD. (2007):

Inverse changes in fetal insulin-like growth factor (IGF)-1 and IGF binding protein-1 in association with higher birth weight in maternal diabetes. Clin Endocrinol (Oxf); 66(3):322-8.

Liu Z, Jeppesen PB, Gregersen S, Chen X, Hermansen K.(2008):

Dose- and Glucose-Dependent Effects of Amino Acids on Insulin Secretion from Isolated Mouse Islets and Clonal INS-1E Beta-CellsRev Diabet Stud; 5:232-244.

Löbnner K, Knopff A, Baumgarten A, et al.(2006) :

Predictors of postpartum diabetes in women with gestational diabetes mellitus. Diabetes; 55: 792–797.

-M-

Maayan-Metzger A, Lubin D, Kuint J.(2009):

Hypoglycemia rates in the first days of life among term infants born to diabetic mothers. Neonatology; 96(2):80-5.

References

152

Macias RI, Marin JJ, Serrano MA. (2009):

Excretion of biliary compounds during intrauterine life. World J Gastroenterol. 21; 15(7):817-28.

Madazli R, Tuten A, Calay Z, Uzun H, Uludag S, Ocak V. (2008):

The incidence of placental abnormalities, maternal and cord plasma malondialdehyde and vascular endothelial growth factor levels in women with gestational diabetes mellitus and nondiabetic controls. Gynecol Obstet Invest.; 65(4):227-32.

Madazli R, Tuten A, Calay Z, Uzun H, Uludag S, Ocak V. (2008):

The incidence of placental abnormalities, maternal and cord plasma malondialdehyde and vascular endothelial growth factor levels in women with gestational diabetes mellitus and nondiabetic controls. Gynecol Obstet Invest.; 65(4):227-32.

Maisels MJ, Kring E.(2006):

The contribution of hemolysis to early jaundice in normal newborns. Pediatrics. ; 118(1):276-9.

Manca L, Masala B.(2008):

Disorders of the synthesis of human fetal hemoglobin. IUBMB Life; 60(2):94-111.

Marín Gabriel MA, Martín Moreiras J, Lliteras Fleixas G, Delgado Gallego S, Pallás Alonso CR, de la Cruz Bértolo J, Pérez Estévez E.(2006):

Assessment of the new Ballard score to estimate gestational age. An Pediatr (Barc); 64: 140-145.

Maticot-Baptista, D, Collin, A, Martin, A, et al.(2007):

Prevention of shoulder dystocia by an ultrasound selection at the beginning of labour of foetuses with large abdominal circumference. J Gynecol Obstet Biol Reprod (Paris); 36:42-49.

References

153

McDonagh AF. (2007):

Movement of bilirubin and bilirubin conjugates across the placenta. Pediatrics ; 119(5):1032-3.

Mehta R, Petrova A. (2005):

Neutrophil function in neonates born to gestational diabetic mothers. J Perinatol. ; 25:178-181.

Metzger BE. (2007):

Long-term outcomes in mothers diagnosed with gestational diabetes mellitus and their offspring. Clin Obstet Gynecol.; 50(4):972-9.

Michael Weindling A. (2009):

Offspring of diabetic pregnancy: short-term outcomes. Semin Fetal Neonatal Med.; 14(2):111-8.

Milcic TL.(2008):

Neonatal glucose homeostasis. Neonatal Netw. 2008; 27(3):203-7.

Mimouni F, Porat S, Merlob P, Zaizov R, Reisner SH.(1986):

Differential leukocyte count in infants of diabetic mothers. Increased band count associated with macrosomia. Clin Pediatr (Phila); 25(8):409-11.

Montassir H, Maegaki Y, Ogura K, Kurozawa Y, Nagata I, Kanzaki S, Ohno K.(2009):

Associated factors in neonatal hypoglycemic brain injury. Brain Dev.; 31: 649-656.

References

154

Moore LE, Briery CM, Clokey D.(2007) :

Metformin and insulin in the management of gestational diabetes mellitus. J Repro Med.; 52:1011–1015.

Moses RG, Cheung NW.(2009):

Point: Universal screening for gestational diabetes mellitus. Diabetes Care; 32(7):1349-51.

Moses RG, Luebcke M, Davis WS, et al.(2006):

Effect of a low-glycemic-index diet during pregnancy on obstetric outcomes. Am J Clin Nutr.; 84:807–812.

Mühlhausler BS.(2009):

Nutritional models of type 2 diabetes mellitus Methods Mol Biol.; 560:19-36.

Murray, TM, Rao, LG, Divieti, P, Bringhurst, FR.(2005) :

Parathyroid hormone secretion and action: evidence for discrete receptors for the carboxyl-terminal region and related biological actions of carboxyl- terminal ligands. Endocr Rev.; 26:78-113.

-N-

Nadal A, Alonso-Magdalena P, Soriano S, Ropero AB, Quesada I. (2009):

The role of estrogens in the adaptation of islets to insulin resistance. J Physiol.; 587(Pt 21):5031-7.

References

155

Negrato CA, Jovanovic L, Rafacho A, Tambascia MA, Geloneze B, Dias A, Rudge MV.(2009):

Association between different levels of dysglycemia and metabolic syndrome in pregnancy. Diabetol Metab Syndr. ;1(1):3.

Newman TB, Liljestrand P, Escobar GJ. (2005):

Combining clinical risk factors with serum bilirubin levels to predict hyperbilirubinemia in newborns. Arch Pediatr Adolesc Med; 159(2):113-9.

Nicholson WK, Fleisher LA, Fox HE, Powe NR.(2005):

Screening for gestational diabetes mellitus: a decision and cost-effectiveness analysis of four screening strategies. Diabetes Care; 28(6):1482-4.

Nold JL, Georgieff MK.(2004):

Infants of diabetic mothers. Pediatr Clin North Am.; 51(3):619-37.

-O-

OkashaS.Amin G.Mufeed H.El-Muhammady M (2007):

.Leptin and insulin levels in umbilical cord blood of infants of diabetic mothers, Relation to fetal birth groth.Pediatric thesis .Faculty of medicine .Cairo University.

Okruszko A, Kinalski M, Kuźmicki M, Mirończuk K, Wawrusiewicz-Kurylonek N, Kinalska I, Kretowski A.(2007):

Glucokinase gene mutations in gestational diabetes in Polish population. Prediction of diabetes mellitus development after delivery. Przegl Lek.; 64:401-405.

Ozkalemkas F, Ali R, Ozkocaman V, et al.(2005):

The bone marrow aspirate and biopsy in the diagnosis of unsuspected nonhematologic malignancy: a clinical study of 19 cases. BMC Cancer. ;5:144.

References

156

Oztekin O. (2007): New insights into the pathophysiology of gestational diabetes mellitus: possible role of human leukocyte antigen-G. Med Hypotheses; 69(3):526-30

-P- Palis J. (2008):

Ontogeny of erythropoiesis. Curr Opin Hematol. ; 15(3):155-61.

Pappas A, Delaney-Black V. (2004):

Differential diagnosis and management of polycythemia. Pediatr Clin North Am;51:1063-1086.

Parker JA, Conway DL. (2007):

Diabetic ketoacidosis in pregnancy. Obstet Gynecol Clin North Am.; 34, :533-543.

PearsonT. (2008):

Glucagon as a Treatment of Severe Hypoglycemia: Safe and Efficacious but Underutilized .The Diabetes Educator; 34: 128-134.

Persson B. (2009):

Neonatal glucose metabolism in offspring of mothers with varying degrees of hyperglycemia during pregnancy. Semin Fetal Neonatal Med.; 14(2):106-10.

Platt MJ, Stanisstreet M, Casson IF, Howard CV, Walkinshaw S, Pennycook S, et al. (2002):

St. Vincent's Declaration 10 years on: outcomes of diabetic pregnancies. Diabet Med; 19:216-20.

Prentki M, Nolan CJ. (2006):

Islet Beta-cell failure in type 2 diabetes. J Clin Invest.; 116: 1802–1812.

References

157

-Q-

Qiu C, Sorensen TK, Luthy DA, Williams MA. (2004):

A prospective study of maternal serum C-reactive protein (CRP) concentrations and risk of gestational diabetes mellitus. Paediatr Perinat Epidemiol.; 18: 377–384.

QIU C. RUDRA M. A. AUSTIN M. A. WILLIAMS C.(2007) :

Association of Gestational Diabetes Mellitus and Low-density Lipoprotein (LDL) Particle Size Physiol. Res.; 56: 571-578.

Qu HM, Ye YH, Peng W, Zhan Y. (2007):

Relationship between tyrosine phosphorylation and protein expression of insulin receptor substrate-1 and insulin resistance in gestational diabetes mellitus Zhonghua Fu Chan Ke Za Zhi.; 42:249-252.

Quitterer U, Hoffmann M, Freichel M, Lohse MJ.(2001):

Paradoxical block of parathormone secretion is mediated by increased activity of G alpha subunits. J Biol Chem. 2; 276(9):6763-9.

-R- Ramasamy I. (2006):

Recent advances in physiological calcium homeostasis. Clin Chem Lab Med.; 44(3):237-73.

Ranheim T, Haugen F, Staff AC, et al.(2004):

Adiponectin is reduced in gestational diabetes mellitus in normal weight women. Acta Obstet Gynecol Scand.; 83: 341–347.

References

158

Reiser DJ.(2004):

Neonatal jaundice: physiologic variation or pathologic process. Crit Care Nurs Clin North Am.; 16(2):257-69.

Rigato I, Ostrow JD, Tiribelli C.(2005):

Bilirubin and the risk of common non-hepatic diseases. Trends Mol Med.; 11(6):277-83.

Robert C. Gensurea, , Thomas J. Gardellaa and Harald Jüppner.(2005):

Parathyroid hormone and parathyroid hormone-related peptide, and their receptors.Biochemical and Biophysical Research Communications; 328: 666-678. Rojo-Martinez G, Esteva I, Ruiz de Aldana MS, et al.(2006):

Dietary fatty acids and insulin secretion: a population-based study. Eur J Clin Nutr.; 60: 1195–1200.

Rosales FJ, Zeisel SH.(2008):

Perspectives from the symposium: The role of nutrition in infant and toddler brain and behavioral development. Nutr Neurosci. ; 11:135-143.

Rosenblatt M. (2009):

When two keys fit one lock, surprises follow. Nat Chem Biol.; 5(10):707-8.

Rudra, CB, Sorensen, TK, Leisenring, WM, et al. (2007):

Weight characteristics and height in relation to risk of gestational diabetes mellitus. Am J Epidemiol ; 165:302-308.

References

159

Ryter SW, Choi AM.(2009):

Heme oxygenase-1/carbon monoxide: from metabolism to molecular therapy. Am J Respir Cell Mol Biol; 41(3):251-60.

-S-

Saito H, Maeda A, Ohtomo S, Hirata M, Kusano K, Kato S, Ogata E, Segawa H, Miyamoto K, Fukushima N.(2004): Circulating FGF-23 is regulated by 1alpha, 25-dihydroxyvitamin D3 and phosphorus in vivo. J Biol Chem. 28; 280(4):2543-9. Saizou C, Moriette G, Sauchez L.(2004): Erythropoietin and anemia in premature infants Arch Pediatr.; 11(12):1516-20.

Saleh J, Al-Riyami HD, Chaudhary TA, Cianflone K.(2008):

Cord blood ASP is predicted by maternal lipids and correlates with fetal birth weight. Obesity; 16: 1193–1198.

Sánchez-Vera I, Bonet B, Viana M, Quintanar A. López-Salva A.(2005):

Increased low-density lipoprotein susceptibility to oxidation in pregnancies and fetal growth restriction. Obstet Gynecol.; 106: 345–351.

Sankar MJ, Agarwal R, Deorari AK, Paul VK. (2008):

Chronic lung disease in newborns. Indian J Pediatr.; 75(4):369-76.

Sarkar S, Hagstrom NJ, Ingardia CJ, Lerer T, Herson VC.(2005):

Prothrombotic risk factors in infants of diabetic mothers. J Perinatol; 25:134-138.

Sarkar S, Rosenkrantz TS.(2008):

Neonatal polycythemia and hyperviscosity. Semin Fetal Neonatal Med.; 13(4):248-55.

References

160

Sasidharan K, Dutta S, Narang A.(2009):

Validity of New Ballard Score until 7th day of postnatal life in moderately preterm neonates. Arch Dis Child Fetal Neonatal Ed. ; 94: 39-44.

Savitz DA, Janevic TM, Engel SM, Kaufman JS, Herring AH.(2008):

Ethnicity and gestational diabetes in New York City, 1995-2003. BJOG;115(8):969-78.

Schaefer-Graf, UM, Pawliczak, J, Passow, D, et al.(2005):

Birth weight and parental BMI predict overweight in children from mothers with gestational diabetes. Diabetes Care; 28:1745-1750.

Schumacher A, Sidor J, Bühling KJ.(2006): Continuous glucose monitoring using the glucose sensor CGMS in metabolically normal pregnant women during betamethasone therapy for fetal respiratory distress syndrome. Z Geburtshilfe Neonatol, 210(5):184-90. Sekine N, Takano K, Kimata-Hayashi N, Kadowaki T, Fujita T. (2006):

Adrenomedullin inhibits insulin exocytosis via pertussis toxin-sensitive G protein-coupled mechanism.Am J Physiol Endocrinol Metab.; 291: 9-14.

Shaat N, Groop L.(2007):

Genetics of gestational diabetes mellitus. Curr Med Chem.; 14(5):569-83.

Siddappa AM, Georgieff MK, Wewerka S, Worwa C, Nelson CA, Deregnier RA.(2004) :

Iron deficiency alters auditory recognition memory in newborn infants of diabetic mothers. Pediatr Res.; 55:1034-1041.

References

161

Simmons D.(2008):

Diabetes during and after pregnancy: screen more, monitor better. CMAJ; 179:215-216.

Slomiany MG, Rosenzweig SA.(2006):

Hypoxia-inducible factor-1-dependent and -independent regulation of insulin-like growth factor-1-stimulated vascular endothelial growth factor secretion. J Pharmacol Exp Ther. ; 318(2):666-75.

Soheilykhah S, Mohammadi M, Mojibian M, Rahimi-Saghand S, Rashidi M, Hadinedoushan H, Afkhami-Ardekani M.(2009):

Maternal serum adiponectin concentration in gestational diabetes. ; 25: 593 – 596.

Somerset DA, Zheng Y, Kilby MD, Sansom DM, Drayson MT.(2004):

Normal human pregnancy is associated with an elevation in the immune suppressive CD25+ CD4+ regulatory T-cell subset. Immunology; 112: 38–43.

Stamatoyannopoulos G. (2005):

Control of globin gene expression during development and erythroid differentiation. Exp Hematol.; 33(3):259-71.

Stanley CA. (2006):

Hypoglycemia in the neonate. Pediatr Endocrinol Rev.; 4:76-81.

Stefanović V, Antić S.(2004): Plasma cell membrane glycoprotein 1 (PC-1): a marker of insulin resistance in obesity, uremia and diabetes mellitus. Clin Lab.; 50(5-6):271-8.

References

162

Stockmann III JA, Pochedly C (1988): Developmental and Neonatal Hematology. Raven Press, New York, pp 297-323 Stothard, KJ, Tennant, PW, Bell, R, Rankin, J. (2009):

Maternal overweight and obesity and the risk of congenital anomalies: a systematic review and meta-analysis. JAMA.; 301:636-650.

Stuebe AM, Oken E, Gillman MW.(2009):

Associations of diet and physical activity during pregnancy with risk for excessive gestational weight gain. Am J Obstet Gynecol.; 201(1):58.e1-8.

-T-

Tabák AG, Tamás G, Péterfalvi A, Bosnyák Z, Madarász E, Rákóczi I, Kerényi Z.(2009):

The effect of paternal and maternal history of diabetes mellitus on the development of gestational diabetes mellitus.J Endocrinol Invest. ; 32(7):606-10.

Tammaro P.(2007):

Neonatal diabetes. Endocr Dev.; 11:70-82.

Teramo KA, Widness JA. (2009):

Increased fetal plasma and amniotic fluid erythropoietin concentrations: markers of intrauterine hypoxia. Neonatology.; 95(2):105-16.

Theodoraki A, Baldeweg SE.(2008):

Gestational diabetes mellitus. Br J Hosp Med (Lond). 69(10):562-7.

References

163

Thureen, P, Reece, M, Rodden, D, et al.(2006):

Increased farnesylation of p21-Ras and neonatal macrosomia in women with gestational diabetes. J Pediatr.; 149:871-873.

Tiribelli C, Ostrow JD.(2005):

Intestinal flora and bilirubin. J Hepatol.; 42(2):170-2.

Toescu V, Nuttall SL, Martin U, Nightingale P, Kendall MJ, Brydon P, Dunne F. (2004):

Changes in plasma lipids and markers of oxidative stress in normal pregnancy and pregnancies complicated by diabetes. Clin Sci (Lond).; 106(1):93-98.

Tok EC, Ertunc D, Bilgin O, Erdal EM, Kaplanoglu M, Dilek S. (2006): PPAR-gamma2 Pro12Ala polymorphism is associated with weight gain in women with gestational diabetes mellitus. Eur J Obstet Gynecol Reprod Biol.; 129(1):25-30.

-U- Uchigata Y. (2006):

Neonatal hypoglycemia Nippon Rinsho. 28; Suppl 3:181-5

Ullmo S, Vial Y, Di Bernardo S, Roth-Kleiner M, Mivelaz Y, Sekarski N, Ruiz J, Meijboom.(2007):

Pathologic ventricular hypertrophy in the offspring of diabetic mothers: a retrospective study. Eur Heart J.; 28(11):1319-25.

-V-

Van Howe RS, Storms MR.(2006):

Hypoglycemia in infants of diabetic mothers: experience in a rural hospital. Am J Perinatol.; 23(2):105-10.

References

164

Van Raalte DH, Li M, Pritchard PH, Wasan KM.(2004):

Peroxisome proliferator-activated receptor (PPAR) -alpha: a pharmacological target with a promising future. Pharm Res; 21:1531–1538.

Vela-Huerta MM, San Vicente-Santoscoy EU, Guizar-Mendoza JM, Amador-Licona N, Aldana-Valenzuela C, Hernnández J.(2008):

Leptin, insulin, and glucose serum levels in large-for-gestational-age infants of diabetic and non-diabetic mothers. J Pediatr Endocrinol Metab.; 21(1):17-22.

Verner AM, Manderson J, Lappin TR, McCance DR, Halliday HL, Sweet DG. (2007):

Influence of maternal diabetes mellitus on fetal iron status.Arch Dis Child Fetal Neonatal Ed. ; 92:399-401.

Victory R, Penava D, Da Silva O, Natale R, Richardson B.(2004):

Umbilical cord pH and base excess values in relation to adverse outcome events for infants delivering at term. Am J Obstet Gynecol. 191(6):2021-8.

Vitoratos N, Deliveliotou A, Vlahos NF, Mastorakos G, Papadias K, Botsis D, Creatsas GK.(2008):

Serum adiponectin during pregnancy and postpartum in women with gestational diabetes and normal controls. Gynecological Endocrinology; 24:614 – 619.

von Versen-Hoeynck FM, Powers RW.(2007):

Maternal-fetal metabolism in normal pregnancy and preeclampsia. Front Biosci. ; 12:2457-70.

-W-

Walkinshaw SA.(2005):

Pregnancy in women with pre-existing diabetes: management issues. Semin Fetal Neonatal Med; 10:307-15.

References

165

Wallace JM, Aitken RP, Milne JS.(2005):

Nutritionally-mediated placental growth restriction in the growing adolescent: consequences for the fetus. Biology of Reproduction ;71(4):1055-62.

Walsh BK, Brooks TM, Grenier BM.(2009):

Oxygen therapy in the neonatal care environment. Respir Care.; 54(9):1193-202.

Wang X, Roy Chowdhury J, Roy Chowdhury N.(2006):

Bilirubin metabolism: Applied physiology. Current Paediatrics; 16:70-74.

Waters TP, Schultz BA, Mercer BM, Catalano PM.(2009):

Effect of 17alpha-hydroxyprogesterone caproate on glucose intolerance in pregnancy. Obstet Gynecol. ;114:45-49.

Wells PG, Mackenzie PI, Chowdhury JR, Guillemette C, Gregory PA, Ishii Y, Hansen AJ, Kessler FK, Kim PM, Chowdhury NR, Ritter JK.(2004):

Glucuronidation and the UDP-glucuronosyltransferases in health and disease. Drug Metab Dispos.; 32(3):281-90.

Wendland EM, Pinto ME, Duncan BB, Belizán JM, Schmidt MI.(2008):

Cigarette smoking and risk of gestational diabetes: a systematic review of observational studies. BMC Pregnancy Childbirth; 16; 8:53.

Westgate JA, Lindsay RS, Beattie J, Pattison NS, Gamble G, Mildenhall LF, Breier BH, Johnstone FD.(2006):

Hyperinsulinemia in cord blood in mothers with type 2 diabetes and gestational diabetes mellitus in New Zealand. Diabetes Care.; 29(6):1345-50.

Williams MA, Qiu C, Muy-Rivera M, et al.(2004) :

Plasma adiponectins concentrations in early pregnancy and subsequent risk of gestational diabetes mellitus. J Clin Endocrinol Metab; 89: 2306–2311.

References

166

Winkler C, Hummel S, Pflüger M, Ziegler AG, Geppert J, Demmelmair H, Koletzko B. (2008):

The effect of maternal T1DM on the fatty acid composition of erythrocyte phosphatidylcholine and phosphatidylethanolamine in infants during early life. Eur J Nutr. ; 47(3):145-52.

-X-

Xu Q, Wells CC, Garman JH, Asico L, Escano CS, Maric C.(2008):

Imbalance in sex hormone levels exacerbates diabetic renal disease..Hypertension.; 51:1218-1224.

-Z- Zhang, C, Qiu, C, Hu, FB, et al.(2008):

Maternal plasma 25-hydroxyvitamin d concentrations and the risk for gestational diabetes mellitus. PLoS ONE; 3:3753.

Zhang, X, Decker, A, Platt, RW, Kramer, MS.(2008):

How big is too big? The perinatal consequences of fetal macrosomia. Am J Obstet Gynecol.; 198:517.

الملخص العربى

اطفال . ان االصابة بمرض السكرى اثناء الحمل يزيد معدالت االعتالل والوفيات لكل من االم و الطفل

دة ازي,نمو غير طبيعى,هات المريضات بالسكرى يكونون اآثر عرضه لالصابة بصعوبة فى التنفسماال

النمو العصبي على نتائج سلبية ,بالدم نقص فى ترآيز السكر ,لبيليروبينزيادة فى نسبة ا,ى لزوجة الدمف

.و تشوهات القلب واألوعية الدموية,نقص فى ترآيز الكالسيوم و الما غنسيوم بالدم,عيوب خلقية,

التى تحدث فى في هذا البحث تم دراسة تاثير اصابة االم بمرض السكرى على حدوث بعض التغيرات

و تأثير العالج بوحدة نلدى ابنائه المذابة فى البالزماالكيميائية عناصر الدم و آذلك ترآيز العناصر

.ثى الوالدة على هذه التغيراتالرعاية المرآزة لالطفال حدي

تم ,اسبوع 41الى 32العمر الحملي لهم يتراوح من , تم اجراء البحث على ستين طفل حديث الوالدة

:تقسيمهم الى ثالثة مجموعات

من اى نوال تعانى امهاته و تتكون من عشرين طفل طبيعي):طةبالمجموعة الضا(:المجموعة االولى

.قبل او اثناء الحمل امراض

آال (بمرض السكرى قبل حدوث الحمل اتمصاب نتهتتكون من عشرين طفل امها: المجموعة الثانية

.)االول و الثانى,النوعين

.الحمل اثناءبمرض السكرى ن اصبنتتكون من عشرين طفل امهاته :المجموعة الثالثة

بالدم مع عمل و البيكربوناتبيليروبينلسيوم و الوالكافى الثالث مجموعات تم قياس مستوى الجلوآوز

. )الضغط الجزئى لكل من االآسجين و ثانى اآسيد الكربون(صورة دم آاملة و قياس الغازات بالدم

فى المجموعة الثانية . الدة مباشرة بعد الو,فى المجموعة الضابطة تم قياس المتغيرات السابقة مرة واحدة

و الثالثة تم قياس المتغيرات مرتين عند دخول وحدة الرعاية المرآزة لالطفال و قبل الخروج من الوحدة

.بعد العالج الالزم للمضاعفات الناتجة عن اصابة االم بمرض البول السكرى

:اظهرت النتائج االتى

آل من ( فى نفس المجموعة من اطفال االمهات المريضات بالسكرى الدم جلوآوز معدل زيادة فى

فى معدل وجد نقص .قبل الخروج من الوحدة مقارنة بالقياس عند الدخول ) المجموعة الثانية والثالثة

مع المجموعة الضابطةمقارنة ب عند الدخول لوحدة الرعاية الثانية والثالثة المجموعتين الدم فى جلوآوز

مقارنةن الثانية والثالثة عند الخروج من الوحدة يبالمجموعت الدم جلوآوز ارق فى معدلغياب الف

. بالمجموعة الضابطة

معدل الكالسيوم بالدم اوضحت الدراسة وجود زيادة فى معدل الكالسيوم فى الدم فى نفس لبالنسبة

لوحدة بالقياس عند الدخولمقارنة قبل الخروج ) الثانية والثالثة تينمن المجموع آال( المجموعة

ن الثانية والثالثة عند دخول وحدة يبالمجموعت ملكالسيوم بالدمعدل ا فىنقص ملحوظ وجد . الرعاية

المجموعة ب مقارنة ن الثانية والثالثةيبالمجموعتنقص المجموعة الضابطة مع استمرار الب مقارنة الرعاية

.الضابطة قبل الخروج من الوحدة

قبل ملحوظ بين نسبة البيليروبن الكلى والمباشر فى الدم فى نفس المجموعة وجود اختالفآما لوحظ عدم

فى زيادة ملحوظةآان هناك .ن الثانية والثالثة لمجموعتيالرعاية لكل من االخروج و عند دخول

الرعاية ن الثانية والثالثة عند الدخول وقبل الخروج من وحدةيالمجموعت البيليروبين الكلى فى الدم بين

اختالف ملحوظ بين البيليروبين المباشر فى فى حين انة اليوجدالضابطة المجموعةب مقارنة المرآزة

عند الدخول او الخروج من وحدةالعناية المجموعة الضابطة ب مقارنة ن الثانية والثالثةيبالمجموعتالدم

.المرآزة

عند الخروج من الهيموجلوببن فى المجموعة الثانيةفى ترآيز نقص ملحوظ اثبتت الدراسة وجود

فى حين انه لم يالحظ اختالف فى قياس نسبة .الوحدة عند دخول مقارنة بالقياس الرعاية المرآزةوحدة

وبالرغم من عدم وجود اختالف . دخول الرعاية فى المجموعة الثالثة عند قبل الخروج و الهيموجلوبين

المجموعة ب مقارنة عند دخول وحدة الرعاية بالمجموعتن الثانية والثالثة الهيموجلوبينملحوظ فى نسبة

عند الخروج المجموعتن الثانية والثالثة فى الهيموجلوبينفى ترآيز نقص ملحوظ اال انه يوجد الضابطة

.المجموعة الضابطة ب مقارنة من العناية المرآزة

لكل من ا الحمراء المكدسة فى الدم فى نفس المجموعة اليوجد اختالف ملحوظ بين حجم الخالي

ايضا لم يالحظ وجود اختالف فى ,وحدة الرعايةلخول دعند ال و قبل الخروج لثالثةاالمجموعتان الثانية و

و عند الدخول لوحدة الرعاية ن الثانية والثالثةيبالمجموعت حجم الخاليا الحمراء المكدسة فى الدم بين

حجم الخاليا الحمراء المكدسة فى الدم بين فىنقص ملحوظ المجموعة الضابطة ولكن آان هناك

. موعة الضابطة المجون الثانية والثالثة قبل الخروج من وحدة الرعاية المرآزة يالمجموعت

ومتوسط سط حجم آرات الدم الحمراء شرات الدم لم يكن هناك اختالف ملحوظ فى متووأبالنسبة الى م

الهيموجلوبين فى آل آرة من آرات الدم الحمراء وذلك فى نفس ترآيز ومتوسط الهيموجلوبين ترآيز

خول وحدة الرعاية المرآزة ولكن د عند و قبل الخروج المجموعة لكل من المجموعتان الثانية والثالثة

ومتوسط الهيموجلوبين ترآيز فى متوسط حجم آرات الدم الحمراء ومتوسطنقص ملحوظ آان هناك

عند الدخول وقبل بالمجموعتن الثانية والثالثة الهيموجلوبين فى آل آرة من آرات الدم الحمراء ترآيز

.المجموعة الضابطةب مقارنة الخروج من وحدة الرعاية المرآزة

آال ىف خولدوعند قبل الخروج اختالف ملحوظ فى نفس المجموعة هناك بالنسبة للخاليا الشبكية لم يكن

خول دعند ال ن الثانية والثالثةيالمجموعت فى زيادة ملحوظة كن الثانية والثالثة ولكن آان هنايمن المجموعت

بط ايجابى بين مؤشر الخاليا اوآان هناك ر. المجموعة الضابطةب مقارنة وقبل الخروج من الرعاية

.المرآزة الشبكية والعمر الحملى فى المجموعة الثانية عند دخول الرعاية

وجود اختالف ملحوظ فى المجموعة الثانيةعدم بالنسبة لمعامل توزيع الكرات الحمراء على الرغم من

فى معاملنقص ملحوظ آان هناك مجموعة الثالثةال فىاال انه ,خول الرعاية دعند و قبل الخروج

فى زيادة ملحوظة و آان هناك .خول الرعاية د بالقياس عندمقارنة الخروج توزيع الكرات الحمراء عند

مقارنة وحدة الرعاية المرآزةل عند الدخول ن الثانية والثالثةيالمجموعت فىمعامل توزيع الكرات الحمراء

ن يالمجموعت معامل توزيع الكرات الحمراء فىايضا لم يالحظ وجود اختالف فى . المجموعة الضابطةب

.المجموعة الضابطةبمقارنة قبل الخروج من الرعاية الثانية والثالثة

عند الدخول ن الثانية والثالثةيالمجموعت فى خاليا الدم البيضاء االولية فى زيادة ملحوظة و آان هناك

ن الثانية والثالثةيالمجموعت وال يوجد اختالف بين المجموعة الضابطةبلوحدة الرعاية المرآزة مقارنة

.المجموعة الضابطة وقبل الخروج من وحدة الرعاية المرآزة

من عند الدخول و قبل الخروج نفس المجموعة فى عدد الصفائح الدموية لم يظهر اى اختالف ملحوظ

فى فى عدد الصفائح الدموية نقص ملحوظمع وجود , ن الثانية والثالثةيالرعاية فى آل من المجموعت

. المجموعة الضابطةبمقارنة الرعايةخول وقبل الخروج من دعند ال ن الثانية والثالثةيالمجموعت

الغازات بالدم فى اطفال االمهات المريضات بالسكرى وجود تغيرات فى االتزان ضغط أظهر قياس

.الحمضى القاعدى من نوع الحموضة التنفسية

خفاض نمثل ا بالسكرىونستنتج من ذلك أن بعض التغيرات الكيميائية فى اطفال االمهات المريضات

ليروبين يتحسنت مع العالج بوحدة الرعاية المرآزة فى حين ان ارتفاع الب قدالكالسيوم والدم جلوآوز

المجموعة الضابطة آان التحسن بمقارنة على الجانب األخر . ن الثانية والثالثةيالمجموعت استمر فى نفس

. الدم انخفاض جلوآوز ليروبن أبطأ من التحسن فى يالكالسيوم وزيادة الب انخفاضفى

حتى خروج األطفال من وحدة الزيادة فى معامل الخاليا الشبكية و النقص فى مؤشرات الدم استمر

.الرعاية المرآزة

معامل توزيع الكرات الحمراء الذى يشير الى اختالف حجم الخاليا فى المجموعة الثانيةاستمر فترة اطول

. من المجموعة الثالثة

ح الدموية استمر حتى ئاالولية تحسنت فى حين ان النقص فى عدد الصفاالزيادة فى خاليا الدم البيضاء

.قبل الخروج من وحدة الرعاية المرآزة

-:التوصيات

توى الكالسيوم حيث ان التدخل االآتشاف المبكر فى الساعات االولى بعد الوالدة الجاوآوز بالدم ة مس- 1

. اطفال االمهات المريضات بالسكرىمهم النقاذ حياة

.التغيرات التى تحدث فى االتزان الحمضى القاعدى هى من النوع التنفسى - 2

معامل توزيع الكرات الحمراء وارتباطها بالية الخلل فى وظيفة عضلة القلب يمكن استخدامه الختيار - 3

.من بين اطفال االمهات المريضات بالبول السكرى بحاجة الى موجات صوتية على القلب

الزمة للمتغيرات التى لم تتحسن لتعود الى لدراسات اخرى للوصول الى الفترات ا ينصح باجراء - 4

.القيمة الطبيعية

my thesis

Documents

study of diabetes

pregestational diabetes

newborn infants

latent autoimmune diabetes

effect of maternal diabetes

faculty of medicine

cairo university

neonates group