Abstract

Abstract Introduction Depression symptoms following burn injury are common, however a tool to risk stratify the likelihood of development of these symptoms does not exist. This study aims to examine the demographic and clinical factors associated with depression symptoms at 12 months post-injury. This data will be used to develop a depression risk scoring system. Methods Data from the Burn Model System National Database (2015–2019) were analyzed. Depression subscale scores of the PROMIS-29 were examined at 12 months and those with scores greater than 60 were considered to have depression symptoms. Demographic and clinical characteristics of the study population were compared between those with and without depression symptoms. Predictors of depression symptoms at 12 months post-injury were determined using multivariate logistic regression. Results The analysis included 298 individuals (52 with and 246 without depression symptoms). Those with depression symptoms at 12 months post-injury were more likely to be female, have had psychological treatment in the year prior to injury, and have sustained a suspected self-inflicted burn injury. Those with depression symptoms were less likely to be married or working at the time of injury compared to those without depression symptoms. No differences in age, burn size, race/ethnicity, etiology of injury, or education level were observed between groups (Table 1). Psychological therapy or counseling in the year prior to injury was the only significant predictor of depression symptoms at 12 months post-injury (p= 0.016). Age and female gender approached significance (p=0.092 and p= 0.086, respectively). Conclusions A history of recent pre-injury psychological treatment was the only significant predictor of depressive symptoms found one-year post-injury. Applicability of Research to Practice This data will be used to create a depression risk scoring system to be used at time of acute care admission to identify burn survivors who are at high risk of developing depression. Identifying those at high risk of depression will facilitate appropriate utilization of resources and potential treatment prophylaxis.

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