- Email: [email protected]
Effects of nutrition on length of stay and survival for burned patients
252 Burns, 7.252-257
Printedin
GreatBritain
Effects of nutrition on length of stay and survival for burned patients* Hal G. Bingham, Engelmann
Jeffrey
P. Krischer, Jonathan
J. Shuster
and
Irma
A.
Colleges of Medicine and Liberal Arts and Sciences and the J. Hills Miller Health Center, University of Florida and Health Services Research, the Veterans Administration Center, Gainesville Summary
From a clinical series of 49 patients, statistical models are developed to predict length of hospital stay and survival based on the extent of the injury (total body surface area and third degree bum), dietary intake and age. Models predicting length of hospital stay among survivors were significant, explaining 70 per cent of the variation in observed stay. For all patients the predictability was much less. A logit model developed for survival analysis correctly predicted 94 per cent of patient outcomes (97 per cent of the survivors, 80 per cent of the deaths). An analysis of recommended ideal caloric intake, based on total bum size and patient weight, could not be shown to be significantly related to patient outcomes. It appears from this analysis that the relationship between outcome and diet would be strengthened if the amount of third degree bum was also included in calculations ofthe ideal caloric intake. INTRODUCTION PREDICTING outcomes
associated with burn injuries can yield important insights into the organization and delivery of patient care services. For example, predictions of mortality risk, as a proxy for burn severity, could help decide policies governing admission into a specialized burn unit. Length of hospital stay predictions could aid in management planning to scale the needed size for such units, their occupancy rates and ultimately their cost-effectiveness. *This project was supported, in part, by Grant Number lR18 HSO3090-01Al from the National Center for Health Services Research, OASH.
Medical
Several studies have been reported in which mortality risk is estimated through analytic models using such descriptive variables as patient’s age, percentage of body surface burned, percentage of full thickness burn, sex, race, pre-existing illness and the time elapsed from injury to hospital admission (Flora et al., 1978; Gustafson and Holloway, 1975; Moores et al., 1975). Location of burn, burn type and whether or not tracheotomy was performed have also been considered important in determining mortality risk (Roi et al., 1978). However, statistical analyses have not been consistent in establishing the relationship between these variables and survival. Length of stay predictions have been reported in statistical models utilizing many of the same variables that have been used to predict survival. Interestingly, none of these analyses considers dietary intake in relation to outpatient outcomes although the literature (Feller et al., 1976; Wilmore et al., 1971; Curreri et al., 1974; Curreri, 1978) has described their importance in survival and wound healing. This investigation details an analysis of average daily caloric and protein intake in relation to survival and length of stay. The primary motivating factor is the recognition that thermal injuries impose severe metabolic demands. This is due to the combination of greatly increased caloric expenditure necessary for healing and the accompanying disruption in intake due to the trauma and its sequelae. Also other investigators, notably Wilmore (197 I), have pointed out the salutary effects
Bingham
253
et al.: Effects of Nutrition
Tab/e 1. Distribution of patients by severity of burn Severity of burn (%)
Body surface area burned Survivors Deaths
Full thickness burn Survivors Deaths
_ >lO >20 >30 >40 >50 >60 >70 >80 >90
,
Total
4 8 9 5 5 4 1 0 3 0
0 0 0 1 3 1 1 2 1 1
29 6 2 1 0 1 0 0 0 0
1 0 2 3 1 1 1 0 1 0
39
10
39
10
Tab/e/l. Distribution of patients by age
Age (vr)
Survivors
AND
1 1
>10,<20 >20 g30 >30 640 >40 ,<50 >50 660 >60
11 13 7 z 3
: 1 4
Total
39
10
of high caloric feedings and, more recently Curreri (1974, 1978) has demonstrated an enhanced immune defense mechanism withhigh caloric and protein feedings. This suggests that adequate nutritional support may have an effect on wound healing and some degree of protection against infection, which would have an impact on survival and length of hospital stay. This protection has given rise to a recommended level of daily nutritional support for the thermally injured patient of25 kcal/kg of body weight plus 40 kcal/% of body surface burned to minimize weight loss during the acute post-burn period (Curreri et al., 1974). PATIENTS
Deaths
METHODS
Forty-nine consecutive adult patients admitted to the Burn Intensive Care Unit of the Shands Teaching Hospital at the University of Florida from June 1975 to April 1977, were included in the study. For each patient, daily caloric and protein intake were tabulated. Pre-burn weight, height and age were also recorded. The injury
was described in terms of the percentage of body surface area involved and the percentage of full thickness burn. Survival and length of stay were recorded on discharge. Average protein and caloric intakes were computed for days in which patients ingested food enterally only. RESULTS
Distribution of this series of patients by age and severity of burn is displayed in Tables I and Il. Thirty-nine of the 49 patients survived and the mean length of hospital stay was 29 days. As might be expected, correlations among several of the independent variables and between independent and dependent variables were significant (Table ZZIJ. For example, percentage of body surface area is significantly (P
-0.41993t
-0.16347 0.35196’
Caloric intake
Length of stay
‘0.01
Death
-0.35601
0.2445
Full thickness burn
Protein intake
0.07687
-0.01261
Total burn
-0.29994’
Height
Weight
Age
1
??
-0.13119
0.01881
0.13866
0.16356
-0.19565
0.05806
0.68072$
Height
Table///. Correlations among study variables
-0.21
127
-0.02795
0.2 1 1 14
0.19673
-0.32059’
0.05974
Weight
1
0.49544%
0.17667
0~12900
0.0736
0.59 1931)
Total burn
0.67554+
0.23567
-0.33997’
-0.38013t
Fllll thickness burn
-0.44104t
0.30642’
097306$
Protein intake
-0.33262’
0.27 198
Caloric intake
-0.07493
Length ofstay
Death
255
Blngham et al.: Effects of Nutrition Tab/e IV. Comparison
of variables
Variable
Mean for survivors
Age Full burn (%) Protein Calories
30.8 9.3 104.2 2209
Significance of differences,
?? o’b5
of survivors
Mean for deaths 47.9 44.5 61.5 1627
and nonsurvivors
Difference -17.1t -35.2% 42.7 582’
S.I. of difference 7.7 8.2 15.4 344
from 2 sample t-test:
protein intake patient outcomes. and Interestingly, both calories and protein were negatively correlated with death but positively correlated with length of stay (caloric intake was not quite significant). A resealing of calories to take into account body weight (Cal/kg) yielded little significant change in the univariate analysis. Length of stay analysis
A stepwise linear regression model was used in a multivariate analysis to identify which of the independent variables could best predict length of stay. The results of this analysis yielded a regression line of the form: Length of stay= -2.70 +0.433 (o/o full thickness burn) + 0.262 (protein intake) + E. None of the other variables entered signiftcantly into the model, which is equivalent to saying that when length of stay is adjusted for both protein intake and the percentage of full thickness burn, none of the other variables demonstrate a significant correlation. This is consistent with Table III in that the variables describing the burn itself, for example, are themselves highly correlated. The above statistical model based on the two variables explain 24 per cent of the variation in length of stay (RZ = 0.24) which is indicative of a large inherent variation in this dependent variable. The relationship is, however, statistically significant (F = 7.2. degrees of freedom 2 and46, P ~0.01). When only survivors are considered, the resultant regression model yielded: Length of stay = 23.03 + 1. I 1 (O/ofull thickness burn) +0.21 (O/o body surface area -0.01 (average daily caloric burned) intake).
Where we note a slight protecting effect of caloric intake suggesting that higher average intakes are associated with shorter length of stay. However, this variable entered the regression at a significant level, P= 0.06, where the percentage of full thickness burn and percentage of total body surface area burned were significant Of at P=O.OOOl and P=O.O4, respectively. particular note, is that among survivors the regression model explains more than 70 per cent of the variance in length of stay (R* =0.72) which makes it a highly significant predictor (F= 27.36, degrees of freedom 4 and 34, P <0~0001).
Survival analysis
Table IV contains a comparison of survivors with nonsurvivors for the variables age, percentage of full thickness burn, average protein and average caloric intake. Differences between the other variables were not significant, as shown in Table III. Using these variables, a multivariate analysis by logit regression was used to give an estimate of the probability of death given by PLY
1 +eY where y=-6.93+0*051 (age)+0’14 (full -0.0585 (protein) + thickness burn) 0.00241 (calories). Based on this model, if we were to predict a death whenever the estimated probability is greater than 50 per cent (i.e. y >O) then the actual v. predicted survival would correctly classify 46 of the 49 (94 per cent) cases as illustrated in Table V. That is, of the 39 survivors, the model would correctly identify 38 (97 per cent) and of the 10 deaths, 8 (80 per cent) would
256
Burns Vol. ~/NO. 4 Tab/e V. Predicted versus actual survival from a discriminant analysis of age, percentage fullthickness burn, average daily protein and caloric intake Predicted D s Actual
S D Total
38 2 40
1 8 9
Total 39 10 49
S, survivors; D, deaths.
have been predicted. Hence, the logit regression model based on these four variables is quite good in predicting survival for this series of burn patients. Survival and length of hospital stay relative to caloric requirements
Curreri et al. (1974) describe caloric requirements of patients with major burns based on weight and the percentage of body surface area burned. The formula was developed by regression analysis of a series of nine patients such that it could be expected to minimize weight loss during a 20 day post-burn period. The formula is given to be: Ideal caloric intake = 25 kcal/kg + 40 kcal/% burn. Applying this formula to our series of patients reveals that 8 received at least the ideal caloric intake on average and 41 received less. The average length of hospital stay for those receiving the ideal or better was 26.25 days, while those receiving less stayed an average of 30.1 days. This difference was not statistically significant (P >0.6) suggesting that while the ideal caloric intake may protect against weight 10~s as Curreri et al. stated, its association with a reduced length of stay could not be demonstrated in this series of patients. Also, the mortality experience of those receiving the ideal caloric intake did not differ significantly (P = 0.275) from those who received a lesser diet, even though none of the 10 deaths were among the 8 receiving an adequate diet. DISCUSSION
Certainly the considered as retrospective patient series. tent with the
results of this analysis must be suggestive only as they reflect the analysis of a relatively small However, the results are consisfindings of others, suggesting the
beneficial association of protein and caloric intake with survival and length of stay. While higher levels of protein intake seem to be associated with longer lengths of stay, they also protect against (reduce the likelihood of) mortality. The association between caloric intake and mortality is opposite in direction of what would be expected, however the very high correlation (r = 0.87) between caloric and protein intakes may explain its small, but positive coefficient in the statistical model. The analysis relative to the formula developed by Curreri et al. (1974) for ideal caloric intake could not support the notion that an adequate diet is beneficial in terms of patient outcomes. However, the small number ofcases receiving an adequate intake according to the Curreri formula, prevented the detection of a statistically significant difference in mortality. That none of the patients who succumbed to their injuries were among those receiving in excess of the standard suggests that additional studies with a larger patient series should be conducted. The logit regression of age, percentage of full thickness burn and dietary intake demonstrated a much stronger relationship to mortality (as did the regression analysis of length of stay) than did the association between dietary formulas and outcomes. This indicates that dietary intake, even though adjusted for the body surface area burned, is not a powerful predictor of outcome but it does, ‘in concert’ with the other variables (importantly, the extent of third degree burn) have a significant relationship with outcome. This poses the question of whether the ideal caloric intake should be adjusted to include the extent of third degree burn. Data from this series is not available to fully answer this question, except to say that the probability of death and the expected length of hospital stay can be quite accurately predicted from the models developed in this paper.
257
Bingham et al.: Effects of Nutrition REFERENCES Curreri P. W. (1978) Nutritional patients. World J. Surg. 2,2 15.
support
of burn
Curreri P. W., Richmond, D., Maven J. et al. (1974) Dietary requirements of patients with major bums. Am. Diet. Assoc. 65,4
15.
Feller I., Flora J. D. and Bawal R. (1976) Baseline results of therapy for burned patients. JAMA 236, 1943.
Flora J. D., Davis T. M. and Roi L. D. (1978) Length of stay and survival time for burned patients. Burns. 5,36. Gustafson D. H. and Holloway J. C. (1975) A decision theory approach to measuring severity In Illness. Health Serv. Rex 10,97.
R~w.~kbr
Moores, B., Rolemon, M. M., Settle J. A. D. et al. (1975) On the predictability of length of patient stay in burns unit. Burns. 1,29 I. Roi L. D., Flora J. D. and Schaeffer R. L. (1978) A model to predict burn patient survival, Paper presented at the 5th International Congress on Burn Injury,
Stockholm.
Sweden.
Wilmore D. W., et al. (1971) Supranormal dietary intake in thermally injured hypermetabolic patients. Surg. Gynecol. Ohster. 132,88
I.
Paper accepted 29 September 1980.
rc’~nnf.s shdd he addressed m: Dr Hal G. Bingham, Department Medicine. University of Florida, Gainesville, 32610 USA.
of Plastic and Reconstructive
Surgery, College of
Printedin
GreatBritain
Effects of nutrition on length of stay and survival for burned patients* Hal G. Bingham, Engelmann
Jeffrey
P. Krischer, Jonathan
J. Shuster
and
Irma
A.
Colleges of Medicine and Liberal Arts and Sciences and the J. Hills Miller Health Center, University of Florida and Health Services Research, the Veterans Administration Center, Gainesville Summary
From a clinical series of 49 patients, statistical models are developed to predict length of hospital stay and survival based on the extent of the injury (total body surface area and third degree bum), dietary intake and age. Models predicting length of hospital stay among survivors were significant, explaining 70 per cent of the variation in observed stay. For all patients the predictability was much less. A logit model developed for survival analysis correctly predicted 94 per cent of patient outcomes (97 per cent of the survivors, 80 per cent of the deaths). An analysis of recommended ideal caloric intake, based on total bum size and patient weight, could not be shown to be significantly related to patient outcomes. It appears from this analysis that the relationship between outcome and diet would be strengthened if the amount of third degree bum was also included in calculations ofthe ideal caloric intake. INTRODUCTION PREDICTING outcomes
associated with burn injuries can yield important insights into the organization and delivery of patient care services. For example, predictions of mortality risk, as a proxy for burn severity, could help decide policies governing admission into a specialized burn unit. Length of hospital stay predictions could aid in management planning to scale the needed size for such units, their occupancy rates and ultimately their cost-effectiveness. *This project was supported, in part, by Grant Number lR18 HSO3090-01Al from the National Center for Health Services Research, OASH.
Medical
Several studies have been reported in which mortality risk is estimated through analytic models using such descriptive variables as patient’s age, percentage of body surface burned, percentage of full thickness burn, sex, race, pre-existing illness and the time elapsed from injury to hospital admission (Flora et al., 1978; Gustafson and Holloway, 1975; Moores et al., 1975). Location of burn, burn type and whether or not tracheotomy was performed have also been considered important in determining mortality risk (Roi et al., 1978). However, statistical analyses have not been consistent in establishing the relationship between these variables and survival. Length of stay predictions have been reported in statistical models utilizing many of the same variables that have been used to predict survival. Interestingly, none of these analyses considers dietary intake in relation to outpatient outcomes although the literature (Feller et al., 1976; Wilmore et al., 1971; Curreri et al., 1974; Curreri, 1978) has described their importance in survival and wound healing. This investigation details an analysis of average daily caloric and protein intake in relation to survival and length of stay. The primary motivating factor is the recognition that thermal injuries impose severe metabolic demands. This is due to the combination of greatly increased caloric expenditure necessary for healing and the accompanying disruption in intake due to the trauma and its sequelae. Also other investigators, notably Wilmore (197 I), have pointed out the salutary effects
Bingham
253
et al.: Effects of Nutrition
Tab/e 1. Distribution of patients by severity of burn Severity of burn (%)
Body surface area burned Survivors Deaths
Full thickness burn Survivors Deaths
_ >lO >20 >30 >40 >50 >60 >70 >80 >90
,
Total
4 8 9 5 5 4 1 0 3 0
0 0 0 1 3 1 1 2 1 1
29 6 2 1 0 1 0 0 0 0
1 0 2 3 1 1 1 0 1 0
39
10
39
10
Tab/e/l. Distribution of patients by age
Age (vr)
Survivors
AND
1 1
>10,<20 >20 g30 >30 640 >40 ,<50 >50 660 >60
11 13 7 z 3
: 1 4
Total
39
10
of high caloric feedings and, more recently Curreri (1974, 1978) has demonstrated an enhanced immune defense mechanism withhigh caloric and protein feedings. This suggests that adequate nutritional support may have an effect on wound healing and some degree of protection against infection, which would have an impact on survival and length of hospital stay. This protection has given rise to a recommended level of daily nutritional support for the thermally injured patient of25 kcal/kg of body weight plus 40 kcal/% of body surface burned to minimize weight loss during the acute post-burn period (Curreri et al., 1974). PATIENTS
Deaths
METHODS
Forty-nine consecutive adult patients admitted to the Burn Intensive Care Unit of the Shands Teaching Hospital at the University of Florida from June 1975 to April 1977, were included in the study. For each patient, daily caloric and protein intake were tabulated. Pre-burn weight, height and age were also recorded. The injury
was described in terms of the percentage of body surface area involved and the percentage of full thickness burn. Survival and length of stay were recorded on discharge. Average protein and caloric intakes were computed for days in which patients ingested food enterally only. RESULTS
Distribution of this series of patients by age and severity of burn is displayed in Tables I and Il. Thirty-nine of the 49 patients survived and the mean length of hospital stay was 29 days. As might be expected, correlations among several of the independent variables and between independent and dependent variables were significant (Table ZZIJ. For example, percentage of body surface area is significantly (P
-0.41993t
-0.16347 0.35196’
Caloric intake
Length of stay
‘0.01
Death
-0.35601
0.2445
Full thickness burn
Protein intake
0.07687
-0.01261
Total burn
-0.29994’
Height
Weight
Age
1
??
-0.13119
0.01881
0.13866
0.16356
-0.19565
0.05806
0.68072$
Height
Table///. Correlations among study variables
-0.21
127
-0.02795
0.2 1 1 14
0.19673
-0.32059’
0.05974
Weight
1
0.49544%
0.17667
0~12900
0.0736
0.59 1931)
Total burn
0.67554+
0.23567
-0.33997’
-0.38013t
Fllll thickness burn
-0.44104t
0.30642’
097306$
Protein intake
-0.33262’
0.27 198
Caloric intake
-0.07493
Length ofstay
Death
255
Blngham et al.: Effects of Nutrition Tab/e IV. Comparison
of variables
Variable
Mean for survivors
Age Full burn (%) Protein Calories
30.8 9.3 104.2 2209
Significance of differences,
?? o’b5
of survivors
Mean for deaths 47.9 44.5 61.5 1627
and nonsurvivors
Difference -17.1t -35.2% 42.7 582’
S.I. of difference 7.7 8.2 15.4 344
from 2 sample t-test:
protein intake patient outcomes. and Interestingly, both calories and protein were negatively correlated with death but positively correlated with length of stay (caloric intake was not quite significant). A resealing of calories to take into account body weight (Cal/kg) yielded little significant change in the univariate analysis. Length of stay analysis
A stepwise linear regression model was used in a multivariate analysis to identify which of the independent variables could best predict length of stay. The results of this analysis yielded a regression line of the form: Length of stay= -2.70 +0.433 (o/o full thickness burn) + 0.262 (protein intake) + E. None of the other variables entered signiftcantly into the model, which is equivalent to saying that when length of stay is adjusted for both protein intake and the percentage of full thickness burn, none of the other variables demonstrate a significant correlation. This is consistent with Table III in that the variables describing the burn itself, for example, are themselves highly correlated. The above statistical model based on the two variables explain 24 per cent of the variation in length of stay (RZ = 0.24) which is indicative of a large inherent variation in this dependent variable. The relationship is, however, statistically significant (F = 7.2. degrees of freedom 2 and46, P ~0.01). When only survivors are considered, the resultant regression model yielded: Length of stay = 23.03 + 1. I 1 (O/ofull thickness burn) +0.21 (O/o body surface area -0.01 (average daily caloric burned) intake).
Where we note a slight protecting effect of caloric intake suggesting that higher average intakes are associated with shorter length of stay. However, this variable entered the regression at a significant level, P= 0.06, where the percentage of full thickness burn and percentage of total body surface area burned were significant Of at P=O.OOOl and P=O.O4, respectively. particular note, is that among survivors the regression model explains more than 70 per cent of the variance in length of stay (R* =0.72) which makes it a highly significant predictor (F= 27.36, degrees of freedom 4 and 34, P <0~0001).
Survival analysis
Table IV contains a comparison of survivors with nonsurvivors for the variables age, percentage of full thickness burn, average protein and average caloric intake. Differences between the other variables were not significant, as shown in Table III. Using these variables, a multivariate analysis by logit regression was used to give an estimate of the probability of death given by PLY
1 +eY where y=-6.93+0*051 (age)+0’14 (full -0.0585 (protein) + thickness burn) 0.00241 (calories). Based on this model, if we were to predict a death whenever the estimated probability is greater than 50 per cent (i.e. y >O) then the actual v. predicted survival would correctly classify 46 of the 49 (94 per cent) cases as illustrated in Table V. That is, of the 39 survivors, the model would correctly identify 38 (97 per cent) and of the 10 deaths, 8 (80 per cent) would
256
Burns Vol. ~/NO. 4 Tab/e V. Predicted versus actual survival from a discriminant analysis of age, percentage fullthickness burn, average daily protein and caloric intake Predicted D s Actual
S D Total
38 2 40
1 8 9
Total 39 10 49
S, survivors; D, deaths.
have been predicted. Hence, the logit regression model based on these four variables is quite good in predicting survival for this series of burn patients. Survival and length of hospital stay relative to caloric requirements
Curreri et al. (1974) describe caloric requirements of patients with major burns based on weight and the percentage of body surface area burned. The formula was developed by regression analysis of a series of nine patients such that it could be expected to minimize weight loss during a 20 day post-burn period. The formula is given to be: Ideal caloric intake = 25 kcal/kg + 40 kcal/% burn. Applying this formula to our series of patients reveals that 8 received at least the ideal caloric intake on average and 41 received less. The average length of hospital stay for those receiving the ideal or better was 26.25 days, while those receiving less stayed an average of 30.1 days. This difference was not statistically significant (P >0.6) suggesting that while the ideal caloric intake may protect against weight 10~s as Curreri et al. stated, its association with a reduced length of stay could not be demonstrated in this series of patients. Also, the mortality experience of those receiving the ideal caloric intake did not differ significantly (P = 0.275) from those who received a lesser diet, even though none of the 10 deaths were among the 8 receiving an adequate diet. DISCUSSION
Certainly the considered as retrospective patient series. tent with the
results of this analysis must be suggestive only as they reflect the analysis of a relatively small However, the results are consisfindings of others, suggesting the
beneficial association of protein and caloric intake with survival and length of stay. While higher levels of protein intake seem to be associated with longer lengths of stay, they also protect against (reduce the likelihood of) mortality. The association between caloric intake and mortality is opposite in direction of what would be expected, however the very high correlation (r = 0.87) between caloric and protein intakes may explain its small, but positive coefficient in the statistical model. The analysis relative to the formula developed by Curreri et al. (1974) for ideal caloric intake could not support the notion that an adequate diet is beneficial in terms of patient outcomes. However, the small number ofcases receiving an adequate intake according to the Curreri formula, prevented the detection of a statistically significant difference in mortality. That none of the patients who succumbed to their injuries were among those receiving in excess of the standard suggests that additional studies with a larger patient series should be conducted. The logit regression of age, percentage of full thickness burn and dietary intake demonstrated a much stronger relationship to mortality (as did the regression analysis of length of stay) than did the association between dietary formulas and outcomes. This indicates that dietary intake, even though adjusted for the body surface area burned, is not a powerful predictor of outcome but it does, ‘in concert’ with the other variables (importantly, the extent of third degree burn) have a significant relationship with outcome. This poses the question of whether the ideal caloric intake should be adjusted to include the extent of third degree burn. Data from this series is not available to fully answer this question, except to say that the probability of death and the expected length of hospital stay can be quite accurately predicted from the models developed in this paper.
257
Bingham et al.: Effects of Nutrition REFERENCES Curreri P. W. (1978) Nutritional patients. World J. Surg. 2,2 15.
support
of burn
Curreri P. W., Richmond, D., Maven J. et al. (1974) Dietary requirements of patients with major bums. Am. Diet. Assoc. 65,4
15.
Feller I., Flora J. D. and Bawal R. (1976) Baseline results of therapy for burned patients. JAMA 236, 1943.
Flora J. D., Davis T. M. and Roi L. D. (1978) Length of stay and survival time for burned patients. Burns. 5,36. Gustafson D. H. and Holloway J. C. (1975) A decision theory approach to measuring severity In Illness. Health Serv. Rex 10,97.
R~w.~kbr
Moores, B., Rolemon, M. M., Settle J. A. D. et al. (1975) On the predictability of length of patient stay in burns unit. Burns. 1,29 I. Roi L. D., Flora J. D. and Schaeffer R. L. (1978) A model to predict burn patient survival, Paper presented at the 5th International Congress on Burn Injury,
Stockholm.
Sweden.
Wilmore D. W., et al. (1971) Supranormal dietary intake in thermally injured hypermetabolic patients. Surg. Gynecol. Ohster. 132,88
I.
Paper accepted 29 September 1980.
rc’~nnf.s shdd he addressed m: Dr Hal G. Bingham, Department Medicine. University of Florida, Gainesville, 32610 USA.
of Plastic and Reconstructive
Surgery, College of