A Simple Protein–Energy Wasting Score Predicts Survival in Maintenance Hemodialysis Patients

ORIGINAL RESEARCH

A Simple Protein–Energy Wasting Score PredictsSurvival in Maintenance Hemodialysis PatientsXavier Moreau-Gaudry, MD,*Guillaume Jean, MD,† Leslie Genet, MSc,‡Dominique Lataillade, MD,§

Eric Legrand, MD,{ Francois Kuentz, MD,** and Denis Fouque, MD, PhD‡

Objective: Nutritional status is a powerful predictor of survival in maintenance hemodialysis patients but remains challenging to

assess. We defined a new Protein Energy Wasting (PEW) score based on the nomenclature proposed by the International Society of

Renal Nutrition and Metabolism in 2008.

Design andMethods: This score, graded from 0 (worse) to 4 (best) was derived from 4 body nutrition compartments: serum albumin,

body mass index, a normalized serum creatinine value, and protein intake as assessed by nPNA.

Subjects: We applied this score to 1443 patients from the ARNOS prospective dialysis cohort and provide survival data from 2005

until 2008.

Main Outcome Measure: Patients survival at 3.5 year.

Results: Survival ranged from 84%-69% according to the protein-energy wasting score. There was a clear-cut reduction in survival

(5%-7%; P , 0.01) for each unit decrement in the score grade. There was a 99% survival at 1 year for patients with the score of 4. In

addition, the 6-month variation of this PEW score also strongly predicted patients’ survival (P , 0.01).

Conclusion: A new simple and easy-to-get PEW score predicts survival in maintenance hemodialysis patients. Furthermore, increase

of this nutritional score over time also indicates survival improvement, and may help to better identify subgroups of patients with a high

mortality rate, in which nutrition support should be enforced.

� 2014 by the National Kidney Foundation, Inc. All rights reserved.

Introduction

LIFE EXPECTANCY OF maintenance hemodialysispatients (MHD) is severely reduced as compared

with the general population1 and nutritional status remainsa powerful predictor of morbidity and mortality.2-4

Protein–energy wasting (PEW) is the consequence ofa combination of insufficient intake, uremic toxins,inflammation, and superimposed catabolism.5,6 Severalstudies have confirmed the importance of clinical assess-ment, body composition measurement, and laboratoryanalyses for diagnosing and quantifying malnutrition,7-9

however routinely, physicians are left without easy-to-usetools. As recently underlined by Kovesdy et al.,10 the lackof a gold standard test to establish PEW renders diagnosis

*Centre de dialyse Porte de Provence, AGDUC, Mont�elimar, France.†Centre du Rein Artificiel – Nephrocare, Ste Foy les Lyon, France.‡Department of Nephrology, CarMeN, CENS, Centre Hospitalier Lyon-

Sud, Universit�e de Lyon F-69622, France.§Service de n�ephrologie et h�emodialyse, Centre Hospitalier – Avitum,

Sallanches, France.{Service de n�ephrologie et h�emodialyse, Centre hospitalier, Annonay, France.**Centre de dialyse des Eaux Claires, AGDUC, Grenoble, France.

Financial Disclosure: See Acknowledgments on page XXX.

Address correspondence to Denis Fouque, MD, PhD, Service de N�ephrologie,Dialyse, Nutrition, Centre Hospitalier Lyon Sud, 69495 Pierre-B�enite, France.E-mail: [email protected]

� 2014 by the National Kidney Foundation, Inc. All rights reserved.

1051-2276/$36.00

http://dx.doi.org/10.1053/j.jrn.2014.06.008

Journal of Renal Nutrition, Vol -, No - (-), 2014: pp 1-6

accuracy of malnutrition impossible, and using a combinedscore of nutritional parameters that encompasses variousaspects of nutrition, an accurate diagnosis of PEWis more likely to be done. The International Society ofRenal Nutrition and Metabolism proposed a uniformednomenclature.11 However, whether this new classificationpredicts mortality has not yet been validated in MHD.In this study, we developed a new easy-to-use PEW

score, based on various clinical and biological values, allbeing readily available at bedside. We hypothesizedthat this score will predict survival in MHD patients. TheARNOS prospective dialysis cohort was used to validatethis hypothesis.

Subjects and MethodsStudy Population and Data CollectionThe ARNOS prospective study merged 25 dialysis units

located in theRhone-Alpes area in France and Switzerland.A total of 2,180 cases were collected during the study fromJune 1, 2005 to June 1, 2008 (Fig. 1). Each patient wasevaluated every 6 months and values recorded until January1, 2009. A total of 1,349 MHDwere enrolled starting June1, 2005. Starting January 1, 2006 until June 1, 2008, 831incident patients were additionally enrolled. Exclusioncriteria were age less than 18 year, patients receiving aweekly number of dialysis sessions different from 3(n 5 288, Fig. 1). One patient was excluded because of alost file. Because of missing data to calculate the score,458 patients were excluded, leaving 1,433 patients for the

1

Figure 1. Fluxogram of the ARNOS study. A total of 2,180 patients were recorded. One thousand four hundred thirty three pa-tients were eligible for the score analyses (1,206 prevalent patients and 685 incident patients minus patients with missing data),and of these, 1,068 patients were available for the score variation over time analysis.

MOREAU-GAUDRY ET AL2

final score analysis. Hemodialfiltration was performed in193 of them, e.g., 13.5%.

Score ValuesWe defined the PEW score as the grading of 1 selected

item in each of the 4 categories of the wasting syndrome11:(1) serum albumin (for biochemistry), (2) BMI (for anthro-pometry), (3) predialysis serum creatinine normalized bybody surface area (SCr/BSA; for muscle mass), and (4)normalized protein nitrogen appearance (nPNA; forprotein intake). The threshold values were (Table 1)serum albumin: 3.8 g/dL; BMI: 23 kg/m2; SCr/BSA:380 mmol/L/m2, and nPNA: 0.8 g/kg/day. nPNA wascalculated with the Garred formula.12 BSA was estimatedby the Boyd formula13,14 as follows:

Body surface ðcm2Þ50:00032073ðweightÞ0:728520:01883logðweightÞ3ðheightÞ0:3

whereweight, collected after theHD session, is in gram andheight in centimeter. For the SCr/BSA variable, the

Table 1. Definition of the Protein–Energy Wasting Score

Serum albumin (g/dL) #3.8

Body mass index (kg/m2) #23

SCr/BSA (mmol/L/m2) #380nPNA (g/kg/day) #0.8

nPNA, normalized protein nitrogen appearance; Scr/BSA, predial-

ysis serum creatinine/body surface area (using postdialysis body

weight).

380 mmol/L/m2 threshold value was obtained by aReceiver operating characteristics (ROC) curve analysis.

Score Calculation and Follow-UpIf a patient had a value strictly greater than threshold, he

received 1; if below threshold, the grade was 0 (seeTable 1). The individual score was therefore comprised be-tween 4 (normal nutritional status) and 0 (severe wasting).Because therewas only 1 patientwith a score of 0, for survivalanalyseswe pooled the 0 and1 grades in a single group (group1) andfinally analyzed survival for 4 categories of PEWscoresfrom group 1 (severe wasting) to group 4 (normal). We alsofollowed the score change after 6-month of follow-up andanalyzed how an improvement/impairment in this scoreaffected patients survival.

Statistical AnalysesThe different statistical analyses were computed using ‘‘R’’

softwareversion2.12.1.15Continuous variableswere reportedas mean 6 standard deviation or mean (confidence interval[CI], P value) and compared by the Student t-test. Qualitativevariableswere reported as percentage andcomparedusing chi-squared test. Cox proportional hazard models were used toestimate the hazard ratios (HRs). The Kaplan–Meier methodwas used to plot survival curves that were compared using thelog-rank test. To test the robustness of the score in ourpopulation, we used a bootstrapping technique to obtainthe mean log rank. CIs were obtained by the bootstrap

Table 2. Patients Characteristics According to Their Score at Study Entry

Clinical and Laboratory

Parameters All

Score 0-1 Score 2 Score 3 Score 4

Severe Wasting Moderate Wasting Slight Wasting Normal Nutritional Status

Number of patients 1,433 276 529 460 168Number of deaths 299 74 124 81 20

Age (y) 66.7 6 14.5 72.1 6 12.1* 69.3 6 13.0* 63.0 6 15.6† 60.0 6 14.6

Male (%) 61.7 63.0† 56.4* 62.6† 74.4

Dry weight (kg) 68.3 6 14.9 62.9 6 13.9* 68.3 6 16.1* 68.7 6 13.1* 76.2 6 13.7BSA, m2 1.78 6 0.23 1.71 6 0.21* 1.78 6 0.24* 1.79 6 0.20* 1.90 6 0.20

Dialysis vintage (y) 4.2 6 6.0 4.2 6 7.4* 3.7 6 5.4* 4.7 6 5.7 4.8 6 6.2

C-reactive protein (mg/L) 13.5 6 26.9 23.1 6 42.6* 13.7 6 24.8* 9.3 6 16.3 7.5 6 13.5

Serum albumin (g/dL) 36.0 6 5.1 32.5 6 4.7* 34.4 6 4.2* 38.0 6 4.5* 41.4 6 2.4SCr (mmol/L) 692 6 258 509 6 337* 630 6 172* 791 6 207* 918 6 162

SCr/BSA (mmol/L/m2) 392 6 167 304 6 272* 361 6 113* 446 6 120* 484 6 77

sp KT/V 1.60 6 0.52 1.57 6 0.58 1.63 6 0.55 1.59 6 0.49 1.54 6 0.42nPNA (g protein/kg/d) 1.12 6 0.31 0.90 6 0.33* 1.14 6 0.28* 1.18 6 0.27† 1.23 6 0.26

BSA, body surface area; nPNA, normalized protein nitrogen appearance; SCr, serum creatinine.

*P , .001 versus score 4.

†P , .05 versus score 4.

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

0.6

0.7

0.8

0.9

1.0

Time (years)

Sur

viva

l

Score = 1Score = 2Score = 3Score = 4

Figure 2. Patients survival according to the protein–energywasting score. One thousand four hundred thirty three pa-tients were analyzed including prevalent patients followedfrom June 2005 to December 2008 and incident patientswho initiated maintenance hemodialysis from January 2006to June 2008. Patients with a score of 0 or 1 were pooledtogether because of limited effective. Group 1 (score of0 or 1) had severe wasting, group 2 (score of 2) hadmoderatewasting, group 3 (score of 3) had slight wasting, and group 4(score of 4) had a normal nutritional status.

PROTEIN-ENERGY WASTING SCORE 3

bias–corrected accelerated method because the likelihood ra-tio distributionwas not gaussian (q-q plot analysis). C-statisticswere used to compare scores and variables used by the score.

ResultsStudy duration was 3.5 years. A total of 1,433 patients

were retained for analysis (Fig. 1) and their mean follow-upwas 2.3 6 4.1 year (Table 2). Mean age was 67 years anddialysis vintage was 4.2 years. Themajor causes of morbidityremained hypertension and diabetes: hypertension waspresent in 78% and diabetes was reported in 34%. Chroniccardiac disease, stroke, or transient attacks was present in23%, 10%, and 6%, respectively. Peripheral vascular diseaseoccurred in 32%. Dialysis access was an arteriovenous fistula(81%) and 19% of patients had a permanent central venouscatheter. BMI was 24.96 4.9 kg/m2. Residual renal func-tion (diuresis. 500mL/day) was present in 31% of patients.Mild chronic inflammationwas present inmore than 50% ofpatients, with a mean C-reactive protein of 14.0 mg/L(Table 2). Dialysis dose was considered adequate (singlepool Kt/Vof 1.6) as well as protein intake (1.1 g/kg/day).Table 2 details clinical and biological parameters accordingto the score grade. The moderately and severely wastedgroups (Gr 1 and 2) included 805 patients, e.g., 56% ofthe cohort. All parameters were significantly more severeor impaired in group 1 compared with group 4, exceptfor Kt/V.Figure 2 shows patients’ survival according to the PEW

score. The HR was 0.80 (CI 0.60-1.07, P 5 .14) betweenthe severely malnourished group (Gr1) and the moderatelymalnourished group (Gr2), 0.61 (0.45-0.84, P , .005)between Gr1 and the slightly malnourished group (Gr3)and 0.38 (0.24-0.64, P , .001) between Gr1 and thenormal nutritional status group (Gr4). In multivariateanalysis, HRs were respectively 0.80 (CI 0.59-1.09,P 5 .16) between Gr1 and Gr2, 0.60 (CI, 0.42-0.85,

P , .005) between Gr1 and Gr3 and 0.33 (CI, 0.19-0.59,P , .001) between Gr1 and Gr4 (Table 3). It is alsoimportant to note that in the 4-score subgroup, whichindicates a normal nutritional status, only 1 over 168 ptsdied during the first year of the study (Fig. 2). Finally, toget a score prediction in a shorter time, we tested its powerat 1 year and found it also significantly predictive ofmortality, with a HR of 0.63 (score 2 vs. 0-1, P , .001),0.41 (score 3 vs. 0-1, P , .001), and 0.04 (score 4 vs. 0-1,P , .001).

Table 3. Three-and-a-Half Year Survival Predictive Factorsin 1,433 Maintenance Hemodialysis Patients

Patients Characteristicsand Score HR CI min CI max P value

Gender (M/F) 1.04 0.80 1.36

Diabetes 1.04 0.80 1.36

Congestive heart failure 1.91 1.45 2.50 , .001

Peripheral vascular disease 1.20 0.97 1.50Stroke 1.30 0.90 1.89

Fistula 0.83 0.61 1.13

C-reactive protein 1.01 1.00 1.01 , .005Sp KT/V 0.84 0.65 1.08

Score 2 versus 0-1 0.80 0.59 1.09

Score 3 versus 0-1 0.60 0.42 0.85 , .005

Score 4 versus 0-1 0.33 0.19 0.59 , .001

CI, confidence interval; HR, hazard ratio; sp KT/V, single pool KT/V.

The normal nutritional status group (score of 4) and the slightly pro-

tein–energy wasted group (score of 3) show an independent signifi-

cant protective effect on patients survival (multivariate Cox model).

MOREAU-GAUDRY ET AL4

We also asked the questionwhether a change in this scoreafter 6 months could predict survival (Fig. 3). This indeedwas the case as there was a significant difference in survivalbetween different score changes (P , .01, log-rank test).Compared with the patients who had their nutritionalstatus impaired (D score , 0), patients who maintainedtheir score after 6 months had a 30% improvement insurvival (P , .05) at 3.5 years and patients who improvedtheir score (D score . 0) reduced mortality by 53%(P , .005).

To validate the robustness of the score in our population,we used a bootstrap analysis at 1 year and 3.5 year. Mean log

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

0.6

0.7

0.8

0.9

1.0

Time (years)

Sur

viva

l

Delta Score < 0Delta Score = 0Delta Score > 0

Figure 3. Patients survival according to a 6-month change(D score) in protein–energy wasting score (n 5 1,068, log-rank test, P, .01). Patients with no change in 6-month scorehad a better survival than those with a score impairment(D score, 0),P, .05, and patients who improved their score(D score . 0), P , .005; 47 deaths were recorded in 181 pa-tients (negative D score); 114 deaths in 606 patients (nullD score), and 41 deaths in 281 patients (positive D score).

ranks were highly significant, being 31.6 (CI, 15.8-54.1),P , .001 at 1 year and 19.3 (CI, 5.8-35.6), P , .001 at3.5 year, respectively, confirming that each subgroup signif-icantly differed by survival, and thus, the validity of thescore in our population. Finally, to test the superiority ofour score, we analyzed the predictive power of each param-eter (albumin, creatinine/SC, nPNA, and BMI) comparedwith the global score by doing a backward stepwise regres-sion analysis. Serum albumin brought the most importantpredictive power, and when albumin was present in themodel, the score was not retained, and creatinine andBMI were also lost. Thus, most nutritional informationgenerally used by clinicians was lost. When albumin wastaken out of the model, the score remained significantversus corrected creatinine, versus nPNA and versus BMItaken individually as continuous variables. Thus, even ifthe weight of each parameter we selected in the score wasnot strictly equal, the score has by itself a clinical relevanceand brings more information than each parameter aloneexcept albumin. We verified this point by performing 2multivariate Cox analyses, one with serum albumin only,and the other with serum albumin, BMI, correctedcreatinine and nPNA. The last model was significantlyimproved at 1 year and 3.5 year compared with the singlealbumin model (P 5 .018 and .048, respectively). Thus,these analyses confirm that the present PEW score usesreliable predictive nutritional information and improvessurvival prediction compared with the use of albuminalone.

DiscussionWe identified a new nutritional score based on simple

readily available parameters and show that it can predictsurvival in MHD patients with acceptable accuracy.Although an altered nutritional status is frequently reportedinMHD, physicians are left without simple tools to identifyand treat PEW because there is no single nutritionparameter, which can predict wasting.16-19 It is everyone’shope to take advantage of a simple nutrition equation toimplement recommendations and improve patients’status.20 The score we developed here includes 1 parameterfrom each major group generally identified to interfere inCKD patients’ nutritional status: (1) biological parameters,(2) body composition, (3) muscle mass, and (4) nutrientintake. It seems indeed important to add to laboratory in-formation (e.g., serum albumin, prealbumin, cholesterol,and lymphocyte count) to other more clinical informationsuch as BMI, body weight, and fat mass.21,22 Muscle mass,which is the major part of the body strongly associated withsurvival, is nevertheless difficult to assess. Here, we chose touse predialysis serum creatinine that we normalized bybody surface area. Indeed, SCr/BSA gave a better fit inthe Cox model than raw serum creatinine. Normalizingserum creatinine seems of interest because it may allowusing this score more widely in populations that differ by

PROTEIN-ENERGY WASTING SCORE 5

creatinine intake and metabolism (Afro-American,Caucasian, and Hispanic or Asian patients). This may bethe reason why creatinine is not used routinely, althoughmany studies have shown its nutritional interest.16,23-26 Itshould be noted that, creatinine prediction power beinglinear,25,27 it is arbitrary to set a threshold, howevernecessary to make discrete statistical analyses and clinicalrecommendations. Finally, we also added information onnutrient intake by entering in the score the protein intakeas estimated by nPNA. This value, although not alwaysrecorded in dialysis facilities, belongs to all currentinternational recommendations and can be obtainedeasily through the dialysis generator software. Added tothe model, it improved survival prediction comparedwith albumin alone. It should be noted that the score byitself was not better than the 4 parameters added into themodel as separate variables. This was not unexpectedbecause information given by the score is already broughtby all variables included into the score. However, webelieve that this is the interest of this score to encouragethe dialysis staff to pay attention to all these variablestaken together. The present score could be obtainedwithin minutes at bedside, with no additional equipment,at no expense and therefore be added to the arsenal ofpatient’ general record and follow-up. The final patientsclassification we obtained (Table 2) corresponds well tothe published literature on the prevalence of nutritionaldisorders in dialysis patients: 37% of patients presentwith moderate and 19% with severe impairment in theirnutritional status.11,28

Is this pragmatic score useful? Patients with a grading of0 to 1 (severe PEW) presented amortality of 27% at 3.5 year(Fig. 2). At 2 years, only 6.5% with a normal nutritionalstatus died, whereas 26.5% died if they were severelywasted, which represents a 4 time greater mortality. Ofnote is the fact that, only 1 patient with a normal nutritionalstatus died during the first year of follow-up (Fig. 2). Inter-estingly, intermediate score values discriminate from eachother to predict survival. This should be underlinedbecause a given score may be obtained with differentbody composition alterations and not only relies on a singlemeasurement of serum albumin or BMI, as it is often donein routine practice. In addition, as shown in the Cox multi-variate analyses, the power of the score appeared greaterthan the single use of albumin or creatinine taken separately.It is uneasy to predict if an obese dialysis patient, theoret-

ically having a better survival, who presents with a lowalbumin level will have a PEW: adding serum creatinine,as a muscle information, and protein intake may directthe patient up- or down-ward on the score scale, and allowa better refining of his/her nutritional risk and survival. Anexample taken from the present cohort highlights the inter-est of the score at enrollment, 2 patients had the same serumalbumin of 3.5 g/dL and same BMI of 23.8 kg/m2; patientA had an adjusted serum creatinine of 300 mmol/L/m2 and

a nPNA of 0.57 g/kg/day, whereas patient B presentedwith an adjusted serum creatinine of 520 mmol/L/m2 anda protein intake of 1.28 g/kg/day. Patient A had a scoreof 1 and died during the study, whereas patient B with ascore of 3 survived the study. From information of serumalbumin and BMI only, the 2 mostly used nutritional in-dexes, it would not have been possible to predict a differentsurvival for these patients. Looking at serum albumin alone,a common attitude could be even more misleading. Twopatients presented with a serum albumin of 3.5 g/dL; thefirst had a BMI of 33 kg/m2, a corrected serum creatinineof 530 mmol/L/m2 and a nPNA of 1.08 g protein/kg/day(e.g., a score of 3) survived the study; the second one had aBMI of 26 kg/m2, a corrected serum creatinine of360 mmol/L/m2 and a nPNA of 0.76 g protein/kg/day(e.g., a score of 1) and died during the study.Finally, this score has another interesting property. It

allows a longitudinal follow-up of patients to predict animprovement/impairment of survival. Indeed, a positivescore increment after 6 months of follow-up was associatedwith a 35% reduction in mortality at 3.5 year (Fig. 3).Conversely, moving downward the PEW score wasassociated with a 43% increase in mortality. This observa-tion indicates that an improvement in the wastingsyndrome is associated with an increased survival.However, the use of this score as a surrogate for survivalstudies is questionable, because the present findings areonly from epidemiologic nature. Further interventionalstudies should be designed to test this hypothesis.In conclusion, the routine use of this easy and robust

score may help to identify malnutrition, now termedPEW, and therefore may call for aggressive renutritionprograms. Follow-up of the score predicts survival, as itsimprovement is associated with reduced mortality.Further studies may be needed to verify the robustnessof the PEW score in non-Western populations becauseof the differences in body composition and clinicalpractice.

Practical ApplicationNo single parameter allows to define protein energy

wasting (PEW) during chronic kidney disease. We presenthere a simple and easy-to-get PEW scoring system from0-4, based on 4 indicators of body composition, musclemass, food intake, and nutritional biology. The lowest isthe score, the more severe is the wasting syndrome. ThePEW score predicts survival, and improving PEW scoreat 6-month interval is associated with extended survival.The PEW score may allow identifying patients at high-risk of wasting and target specific nutritional strategies.

AcknowledgmentsThe ARNOS project was partially funded by an educational grant

from AMGEN France. None of the authors received honoraria, travel

grants, or other financial support for this study.

MOREAU-GAUDRY ET AL6

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