Epidemiology and risk prediction of patients with severe burns admitted to a burn intensive care unit in a burn center in beijing: A 5-year retrospective study

Abstract

ObjectiveThis study was performed to describe the epidemiology of patients with severe burns hospitalized in a burn intensive care unit (BICU), explore the risk factors associated with the patients’ outcomes and evaluate the ability of prognostic scoring systems as risk prediction of mortality. MethodsThe data for this study were derived from patients with severe burns in the BICU of Beijing Jishuitan Hospital from 2015 to 2019. The following epidemiological information and outcomes were collected for retrospective analysis: sex, age, date of injury, etiology of burn, admission time after injury, extent of burn, inhalation injury, length of stay, and outcome. Abbreviated Burn Severity Index (ABSI), prognostic burn index (PBI), the burn index (BI), Belgian Outcome in Burn Injury (BOBI) scores and the revised Baux (rBaux) scores were calculated. ResultsOf the 243 patients included in this study, the median age was 41.00 (22.00) years and the male: female ratio was 4.28:1.00. Most of the burns had occurred from March to July. Flame was the main cause of the burns (77.37%), followed by electricity (14.40%). In total, 78.19% of all patients sustained third-degree burns, and the median burn area and third-degree burn area of patients were 40% (53%) and 15.0% (43.0%) of the total body surface area, respectively. The incidence of inhalation injury was 69.14%. Tracheotomy was performed in 53.89% of the patients with inhalation injuries, and the rate of tracheostomy showing a rising trend. The median length of stay was 37 (40) days, and the case fatality rate was 8.64%. Multivariable logistic regression model indicated that age and third-degree burn area were risk factors for death, and the area under the receiver operating characteristic curve for the full prediction model was 0.921 (95% CI = 0.874–0.967). ConclusionsThe majority of severe burns are flame-related accidents in middle-aged men. Risk prediction model combining age and third-degree burn area has better mortality predictive value.