Prediction of mortality from catastrophic burns in children.
BACKGROUND
We previously developed a model to predict survival in massive paediatric burns (>80% total body surface area [TBSA]). This model included not only demographic variables, but also variables obtained throughout the hospital course. We aimed to prospectively validate our model for accuracy of outcome prediction.


METHODS
We admitted 33 paediatric burn patients with burns greater than 80% TBSA. We recorded age, burn size, inhalation injury, resuscitation, packed-cell volume at admission, base deficit, serum osmolarity, sepsis, inotropic support, platelet count, creatinine, and ventilator dependency. We entered these data into our previous models.


RESULTS
20 male and 13 female children with mean age 7.6 (SD 1) years with TBSA burns of 88% (SD 1; full thickness 86% [SD 1]) were admitted. Mortality was 39.4% (13 of 30). When all variables were integrated into our final model, we predicted outcome with 97% accuracy. When we used a model based only on demographic characteristics of age, burn size, and presence of inhalation injury, outcome was correctly predicted in only 51% of patients.


CONCLUSIONS
We show prospectively that mortality in severely burned children can be reliably estimated at a burn centre, and that outcome cannot be reliably predicted on the basis of demographic and injury characteristics alone. These data suggest that all severely burned children should be given a course of treatment before consideration of treatment futility.
Spies
Marcus
M
Shriners Hospitals for Children and Department of Surgery, The University of Texas Medical Branch, Galveston, TX 77550, USA.
Herndon
David N
DN
Rosenblatt
Judah I
JI
Sanford
Arthur P
AP
Wolf
Steven E
SE
D000293:Adolescent; D002053:Burn Units; D002056:Burns / Q000401:mortality / Q000503:physiopathology / Q000628:therapy; D002059:Burns, Inhalation / Q000401:mortality; D002648:Child; D005260:Female; D006801:Humans; D008297:Male; D011237:Predictive Value of Tests; D011446:Prospective Studies; D016019:Survival Analysis