Abstract
Burn outcomes can be improved by reducing mortality and hospital admission duration. This increases patient quality of life and reduces hospital-associated complications and costs. This study aimed to develop a model with which to predict burns inpatient mortality and admission duration. Multiple logistic and linear regression were used to investigate mortality and admission duration by age, total body surface area, sex, delay to presentation, the use of surgery, discharge distance and period. One thousand four hundred and seventynine patients (747 pre-COVID and 732 during COVID) were admitted between the study dates. Using multiple logistic regression, age and total body surface area predicted mortality LR X2 (5), P< 0.001, pseudo R2 = 0.57. Using multiple linear regression, age, total body surface area and the use of surgery predicted admission duration F (7, 1455)=161.42, P< 0.001, R2 = 0.44. Sex, delay to presentation, period and discharge distance did not predict mortality or admission duration. In our institution, mortality was increased by 8.6% for each additional year of age and by 11.3% for each additional percentage total body surface area. Likewise, admission duration was prolonged by 1 day for every 7 years of increased age, by 1 day for each additional percentage total body surface area or by 7 days if surgery was required. These models have been incorporated into a set of prediction tables for mortality and admission duration for use in our institute that can guide patient and family discussions.
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