Prediction of maximal aerobic capacity in severely burned children

Prediction of Maximal Aerobic Capacity in Severely BurnedChildren

Laura Porro, MDa,b, Haidy G. Rivero, MDa,b, Dante Gonzalez, BSc, Alai Tan, PhDd, DavidN. Herndon, MDa,b, and Oscar E. Suman, PhDaShriners Hospitals for Children, Galveston TX 77550bDepartment of Surgery, The University of Texas Medical Branch, Galveston TX 77555cSt Mary’s University in San Antonio, Summer Research Student at UTMBdOffice of Biostatistics, The University of Texas Medical Branch, Galveston TX 77555

AbstractIntroduction—Maximal oxygen uptake (VO2 peak) is an indicator of cardiorespiratory fitness,but requires expensive equipment and a relatively high technical skill level.

Purpose—The aim of this study is to provide a formula for estimating VO2 peak in burnedchildren, using information obtained without expensive equipment.

Methods—Children, with ≥40% total surface area burned (TBSA), underwent a modified Brucetreadmill test to asses VO2 peak at 6 months after injury. We recorded gender, age, %TBSA, %3rd

degree burn, height, weight, treadmill time, maximal speed, maximal grade, and peak heart rate,and applied McHenry’s select algorithm to extract important independent variables and Robustmultiple regression to establish prediction equations.

Results—42 children; 7 to 17 years old were tested. Robust multiple regression model providedthe equation: VO2=10.33 – 0.62 *Age (years) + 1.88 * Treadmill Time (min) + 2.3 (gender;Females = 0, Males = 1). The correlation between measured and estimated VO2 peak was R=0.80.We then validated the equation with a group of 33 burned children, which yielded a correlationbetween measured and estimated VO2 peak of R=0.79.

Conclusions—Using only a treadmill and easily gathered information, VO2 peak can beestimated in children with burns.

Keywordsburns; cardiopulmonary fitness; maximal oxygen consumption

© 2011 Elsevier Ltd and ISBI. All rights reserved.Corresponding Author: Oscar E. Suman, PhD, Professor, Department of Surgery, The University of Texas Medical Branch, ShrinersHospitals for Children-Galveston, 815 Market St., Galveston, TX 77550, PH 409-770-6557, Fax 409-770-6919, [email protected]'s Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to ourcustomers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review ofthe resulting proof before it is published in its final citable form. Please note that during the production process errors may bediscovered which could affect the content, and all legal disclaimers that apply to the journal pertain.There are no potential conflicts of interest pertaining to this manuscript for any authors. In addition, no authors have any financialdisclosures related to this manuscript.

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Published in final edited form as:Burns. 2011 June ; 37(4): 682–686. doi:10.1016/j.burns.2010.12.021.

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IntroductionThe survival rate of children with severe burns has dramatically increased as a result ofadvances in resuscitation and critical care, use of broad-spectrum antimicrobials,improvements in nutrition, alongside with an early excision and prompt wound closure. [1–2]. As patients survive the acute phase long-term burn-related complications and extensivephysical and functional limitations are present.

One long term functional limitation in burned children is a decrease in cardiopulmonaryfunction that lasts up to two years after the initial burn injury. [3] Maximal or peak oxygenuptake (VO2 peak), which reflects cardiopulmonary function, is typically considered anindex of cardiorespiratory fitness. VO2 peak is defined as the maximum volume of oxygenper unit of time that the body can consume during intense, whole-body exercise. It istypically, expressed as a rate, either as liters per minute (L/min) or as milliliters perkilograms body weight per minute (ml/kg/min). VO2 peak is useful in determining theintensity of exercise training needed to induce beneficial cardiovascular and training effect,as well as allows tracking of progress during rehabilitation programs[4] [5]. However,measurement of VO2 peak using indirect calorimetry is costly and often requires technicaltraining. Consequently, there is probable need to explore methods for estimating the VO2peak in burned children and most likely it could be helpful in children with other pathologiesor in locations with limited economical resources.

Therefore, the aim of this study is to provide a simple formula for predicting VO2 peakusing information acquired clinically without the need for expensive equipment. It isenvisioned that such information can then be used in the exercise rehabilitation of burnedchildren.

MethodsSubjects

This study was conducted at Shriners Hospitals for Children, Galveston, Texas. Forty twochildren with an age range 7 to 17 years old, and who were admitted to our burn unit foracute care and had an exercise tolerance test at 6 month post burn were included in thisanalyses. These children also had 40% or greater total body surface area burn (TBSA) asevaluated by the "rule of nines" method [6] during excisional surgery in the acute phase ofinjury. Patients were excluded if they had one or more of the following: leg amputation,anoxic brain injury, psychological disorders, quadriplegia, or severe behavior or cognitivedisorders. Additionally, another group of 33 burned children with the same previouscharacteristics were randomly selected as the validation group to correlate the results. Thestudy was reviewed and approved by the Institutional Review Board, of the UniversityTexas Medical Branch, Galveston, Texas. Before the study each subject (if applicable), andparent or child’s legal guardian had to sign a written informed consent form. All patientsreceived similar standard medical care and treatment from the time of emergency admissionand acute care of the burn injury until time of discharge.

Exercise testingAt 6 months post-burn injury, all patients in this study returned to Shriners Hospitals forChildren for exercise testing, and underwent a standardized treadmill exercise test, using themodified Bruce protocol, this test is a widely adopted protocol that has been well validatedto evaluate and asses cardiovascular fitness and for testing maximal aerobic endurance timein children. This test was chosen as it is well tolerated by the patients. Briefly, this test startsby walking on the treadmill at speed of 1.7 miles/hour and zero grade of elevation, with thepatient breathing through a 2-way valve system. Subsequently, at three minute intervals,

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stages two and three are performed at a 1.7 miles/hour and 5% grade and 1.7 miles/hour and10% grade respectively. From this point on, the incline of the treadmill increases by 2%grade and by a set speed increments (2.5, 3.4, 4.2 miles/hour) at regular intervals of 3minutes. Subjects were continuously encouraged to complete 3 minutes stages, and the testwas completed once peak volitional effort was achieved, and the respiratory exchange ratio(R) of ≥ 1.10 was achieved, at this point treadmill time was recorded to be used in theequation. Air that was expired, passed through sensors that quantified both volume andoxygen concentration, and were analyzed by a computer.

Heart rate and oxygen consumption (VO2) were monitored and analyzed by using methodspreviously described [7–8]. Briefly, breath-by-breath analysis was continuously made ofinspired and expired gases, flow, and volume by using a Medgraphics CardiO2 combinedVO2/ECG exercise system (St. Paul, MN) indirect oxygen calorimeter, and PreVentTMPneumotach and a mouth piece.

Heart rate was measured continuously with Precor USA heart rate monitor. The piece ofequipment has a lightweight transmitter, which was held on the chest by a strap, with dryelectrodes on the inner surface and a watch-like device attached to the wrist. Heart rate wasrecorded every 5 second and then averaged over 30 second.

Statistical analysesWe measured the following variables: gender, age, %TBSA, %3rd degree burn, height,weight, treadmill time, maximal speed, maximal grade, and peak heart rate and consideredthem as independent variables and VO2 peak was considered the dependent variable. Nextwe performed one portion of a regression analysis to obtain a subset of independentvariables, and finally we proceed to conduct a multiple regression procedure to fit the modelbased on the selected variable.

We applied variable selection routine which uses McHenry’s select algorithm [9] to find thebest subset from independent variables providing maximum R-Squared to predict VO2 peak.It is an extremely fast statistical method which uses the algorithm that seeks a subset ofparameters that provides a maximum value of R-Squared (or a minimum Wilks’ lambda inthe multivariate case). This algorithm seems to find the best (or very near best) subset inmost situations. It first finds the best single variable. To find the best pair of variables, ittries each of the remaining variables and selects the one that adds the most, then omits thefirst variable and determines if any other variable would add more. If a better variable isfound, it is kept and the worst variable is removed. Another search is now made through theremaining variables. This switching process continues until no switching will result in abetter subset. Once the optimal pair of variables is found, the best three variables aresearched for in much the same manner. First, the best third variable is found to add to theoptimal pair of variables from the last step. Next, each of the first two variables is omittedand another, even better, variable is searched for. The algorithm continues until no switchingimproves R-Squared.

We kept those selected variables and ignored the rest of the parameters since they did notsignificantly add to the ability of the equation to predict VO2 peak and were not included inthe final equation because of the multi-co-linearity, or co-linearity, relationships among theindependent variables. We then applied a Robust multiple regression analysis using Huber’smethod [19] to establish our prediction equations (models) for different populations (male,female and all male and female). These analyses were performed using SAS (SAS® InstituteInc., Cary, NC). The model selection and Robust regression analysis were conducted usingSAS PROC REG and PROC ROBUSTREG procedures (SAS® 9.2 User’s Manual, SAS

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Institute, Cary, NC). All tests were two sided with significance accepted at p<0.05. Allresults are means +/− standard error of the mean.

ResultsForty two thermally injured children (27 boys, 15 girls) with an age range 7 to 17 years old(12 ± 0.51) with a 40% or greater total body surface area burn (TBSA) were tested, and formpart of the model development group. Demographic data is presented in Table 1 for both themodel development group and the validation group. We found no significant differenceamong the 2 groups in gender, age, %TBSA, %3rd degree burn, height, weight, treadmilltime, speed, grade, and heart rate.

Based on the subset variable selection algorithm, variables treadmill time and age werecandidate variables, (R2=0.62. P=0.008 and P<0.0001 for age and treadmill time,respectively) (Figure 1) since there was no significant interaction between gender and otherpredictors we decided to use a single model for both boys and girls with the gender as apredictor in the model. We assigned the value of 1 for males and 0 to females. Thecorrelation between measured VO2 peak and estimated VO2 peak was R2 = 0.65 (Figure 2).Robust multiple regression model using Huber’s method provided the following equation:

We then proceed to validate our results by applying the equation obtained to the validationgroup. The correlation between measured VO2 peak and estimated VO2 peak was R2 = 0.63(Figure 3).

DiscussionOur study yielded an equation to predict VO2 peak that may be useful as a practical tool forassessing functional capacity of severely burned children. With R squared values thatrepresent an acceptable approximation of the VO2 peak measured, the application of theequation requires no special training or expensive equipment, and the demographicsnecessary to predict VO2 peak can be gathered fairly simply either at home, clinic, hospital,or fitness center.

Our initial analysis resulted in a prediction equation that took into consideration if thepatient had inhalation injury. Although the R squared value was higher (R2=0.77 versus0.65), we did not select this equation in order to preserve the simplicity that makes thisequation useful in almost any setting. The R-Squares that guided the variable selection wereshown in Figure 1.

The validation group confirmed the correlation between the VO2 peak measured and VO2peak estimated, with an R2=0.63. This group allowed us to identify some patients that wereunder predicted by our equation. We found that 2 of the patients in this group reached agreater VO2 peak than the predicted value. This are considered the lesser of two evils sincethe patient exceeded or had greater VO2 peak than the expected value.

In children with burns assessing VO2 peak can be a valuable piece of information specific toexercise rehabilitation or exercise training. For example, an inactive patient receiving thestandard of care without exercise rehabilitation may present VO2 peak values of 23.2milliliters/minute, 25.9 milliliters/minute and 25 milliliter/minute at discharge, 6 months and12 months after injury respectively. Contrast this with an active patient that participated in acomprehensive rehabilitation and exercise program, and had VO2 peak values of 24.6

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milliliters/minute at discharge 33.2 milliliters/minute at 6 months and 38.8 milliliters/minuteat 12 months after injury.[10–11] These examples underscore the importance of evaluationmethods of physical fitness especially of the cardiopulmonary system, not only as an initialevaluation tool, but also in the evaluation of progress overtime.

There are number of methods that use heart rate alone to predict VO2 peak.[12][5] Okuraand Tanaka established a method to predict VO2 peak from the perceived exertion scale thatcan be applied not only in clinically normal people but also in patients with essentialhypertension, through an easily applied procedure that’s does not require instrumentation.[5] However, the results of this study can be considered subjective rather than objectivesince it relies in the capacity of the patient to recognize general feelings of physical fatigue,cardiopulmonary system symptoms and tension in the exercising muscles and joints. [5]Later in 2003, Sarton-Miller et al developed a non-invasive, and affordable regression-basedmethod that predicts net oxygen consumption from net heart rate along with severalcovariates and is used for estimating net energy expenditure in children performing activitiesat high altitude.[12] However, heart rate can be affected by various drugs as beta- blockingagents and cardiac stimulants, and beta-adrenergic blockade with propranolol has beenrecognized as an efficacious therapy in the modulation of the heart response in burns [13–14], subsequently a method that uses heart rate alone to predict VO2 peak should not beapplied in these patients until further study is done. To our knowledge methods to predictVO2 peak in burn children have not been previously described. However it is important tonote that this formula is specific for pediatric burns patients using the modified Bruceprotocol for the treadmill test.

In summary, using only a treadmill and easily gathered information such as patientdemographics, treadmill speed, and grade, this method of estimating VO2 peak cansignificantly improve the ability of rehabilitation specialists in assessing fitness anddetermining training levels in the initial assessment and while tracking progress of a patientwith severe burns.

AcknowledgmentsWe thank Fatemah Emdad, PhD for her collaboration in the statistical analyses; Serina J. McEntire, PhD for heroutstanding job at the Wellness Center. This study was partially supported by grants from the National Institute forDisabilities and Rehabilitation Research H133A70019 and H133A070026; the National Institutes of Health RO1-HD049471, T32-GM08256 and P50 GM060338-08S1; and Shriners Hospitals for Children grant 8760.

References1. Muller MJ, Herndon DN. The challenge of burns. Lancet. 1994; 343(8891):216–220. [PubMed:

7904672]2. Saffle JR, Davis B, Williams P. Recent outcomes in the treatment of burn injury in the United

States: a report from the American Burn Association Patient Registry. J Burn Care Rehabil. 1995;16(3 Pt 1):219–232. discussion 288’9. [PubMed: 7673300]

3. Desai MH, et al. Does inhalation injury limit exercise endurance in children convalescing fromthermal injury? J Burn Care Rehabil. 1993; 14(1):12–16. [PubMed: 8454658]

4. Wergel-Kolmert U, Wisen A, Wohlfart B. Repeatability of measurements of oxygen consumption,heart rate and Borg's scale in men during ergometer cycling. Clin Physiol Funct Imaging. 2002;22(4):261–265. [PubMed: 12402448]

5. Okura T, Tanaka K. A unique method for predicting cardiorespiratory fitness using rating ofperceived exertion. J Physiol Anthropol Appl Human Sci. 2001; 20(5):255–261.

6. Herndon, DN., et al. Management of Burn Injuries. Pediatric Trauma: Prevention, Acute Care andRehabilitation. Eichelberger, MR., editor. St Louis: Mosby Year Book; 1993. p. 568-590.

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7. Suman OE, Herndon DN. Effects of cessation of a structured and supervised exercise conditioningprogram on lean mass and muscle strength in severely burned children. Arch Phys Med Rehabil.2007; 88 12 Suppl 2:S24–S29. [PubMed: 18036977]

8. Suman OE, et al. Effects of a 12-wk resistance exercise program on skeletal muscle strength inchildren with burn injuries. J Appl Physiol. 2001; 91(3):1168–1175. [PubMed: 11509512]

9. McHenry C. Multivariate subset selection. Journal of the Royal Statistical Society. 1978; Volume27(No. 23):291–296.

10. Alloju SM, et al. Assessment of muscle function in severely burned children. Burns. 2008; 34(4):452–459. [PubMed: 18243565]

11. Suman OE, Mlcak RP, Herndon DN. Effect of exercise training on pulmonary function in childrenwith thermal injury. J Burn Care Rehabil. 2002; 23(4):288–293. discussion 287. [PubMed:12142585]

12. Sarton-Miller I, Holman DJ, Spielvogel H. Regression-based prediction of net energy expenditurein children performing activities at high altitude. Am J Hum Biol. 2003; 15(4):554–565. [PubMed:12820197]

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Figure 1.R-Squares that guide the variable selection using McHenry’s selection algorithm. Lettersdenote the different selection of variable combinations.

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Figure 2.Predicted peak oxygen consumption (VO2 peak) vs measured VO2 peak, based on theprediction equation VO2=10.33 − 0.62 *Age (years) + 1.88 * Treadmill Time (min) + 2.3(gender) for burn children in the model development group. For gender assigned values are1 for males and 0 for females.

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Figure 3.Predicted peak oxygen consumption (VO2 peak) vs measured VO2 peak, based on theprediction equation VO2=10.33 − 0.62 *Age (years) + 1.88 * Treadmill Time (min) + 2.3(gender) for burn children for the validation group. For gender assigned values of 1 formales and 0 for females were assigned[5].

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