Burns mortality and hospitalization time--a prospective statistical study of 352 patients in an Asian National Burn Centre.
A prospective study of 352 patients in an Asian National Burn Centre has been used to develop statistical predictive models for mortality and hospitalization time. The patients are largely of Asian origin. Total burn surface area (% TBSA) and presence of respiratory burns are significant independent predictors of mortality in the multiple logistic regression analysis with an accuracy of 98.3 per cent. Age is not a significant predictor of mortality in our patients. Age, % TBSA, full thickness % TBSA and respiratory burns are significant independent predictors of length of stay in hospital with a R2 value of 0.57 in the multiple linear regression analysis. There were 16 deaths, many of whom had developed multiple complications, common causes of which were sepsis, bronchopneumonia, DIVC and multiorgan failure. The final causes of death were septicaemic shock in 10 patients, extensive burns in four patients, ARDS in one patient and bleeding peptic ulcer in one patient. The development of these two mortality and morbidity predictive models is the first step in the evaluation of our results. These models have to be tested against a future set of patients. After confirmation they will aid in patient management, clinical audit, patient and family counselling. They will also serve as baseline standards for evaluation of new therapies, assist us in the allocation of resources and identifying the at-risk population for improvements in therapy.
Wong
M K
MK
Department of Plastic and Reconstructive Surgery, Singapore General Hospital.
Ngim
R C
RC
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002053:Burn Units / Q000706:statistics & numerical data*; D002056:Burns / Q000453:epidemiology / Q000401:mortality*; D002648:Child; D002675:Child, Preschool; D005260:Female; D017052:Hospital Mortality; D006801:Humans; D007223:Infant; D007902:Length of Stay / Q000706:statistics & numerical data*; D016014:Linear Models; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009017:Morbidity; D015999:Multivariate Analysis; D011446:Prospective Studies; D012680:Sensitivity and Specificity; D012846:Singapore / Q000453:epidemiology; D016019:Survival Analysis