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Original Research Article| Volume 225, ISSUE 4, P793-799, April 2023

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The predictive probability of mortality in the presence of full-thickness burns

Published:October 07, 2022DOI:https://doi.org/10.1016/j.amjsurg.2022.10.006

      Highlights

      • Prognostication of burn injury mortality is challenging.
      • Recent mortality prognostication tools have incorporated percent of full-thickness surface area.
      • Patients with and without full-thickness burns have a mortality of 29.1 vs 1.3%, respectively.
      • When controlling for TBSA the presence of a full-thickness burn had a relative risk of in-hospital mortality of 1.35.
      • The predicted probability of mortality was 100% at FTSA between 30 and 40%.

      Abstract

      Introduction

      Prognostication of burn injury mortality is challenging. Recent mortality prognostication tools have incorporated the percent of full-thickness surface area (FTSA). We hypothesize that the presence of full-thickness burn injury independently increases in-hospital mortality.

      Methods

      We performed a retrospective review of the National Trauma Data Bank (NTDB) from 2007 to 2019 of adults (≥16 years old) with burn injuries. Variables evaluated included basic demographics, presence of inhalation injury, percent TBSA, and percent FTSA burned. The primary outcome was in-hospital mortality. We performed modified Poisson regression modeling adjusting for significant variables to estimate the relative mortality risk.

      Results

      75,816 patients met inclusion criteria. When controlling for TBSA, the presence of a full-thickness burn had a relative risk of in-hospital mortality of 1.42 (95% CI 1.09–1.85, p = 0.008). The predicted probability of mortality was 100% at 50% FTSA.

      Conclusion

      The presence of full-thickness burns and the proportion of full-thickness burns independently and significantly increased in-hospital mortality. Therefore, clinicians should utilize prognostication models incorporating percent full-thickness burn area to predict mortality more accurately.
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