Predicting wound healing rates and survival with the use of automated serial evaluations of burn wounds

Burns. 2019 Feb;45(1):48-53. doi: 10.1016/j.burns.2018.10.018. Epub 2018 Nov 22.

Abstract

Healing of burn wounds is necessary for survival; however tracking progression or healing of burns is an inexact science. Recently, the relationship of mortality and wound healing has been documented with a software termed WoundFlow. The objective of the current study was to confirm various factors that impact burn wound healing, as well as to establish a timeline and rate of successful healing. A retrospective analysis was performed on adults (n=115) with at least 20% TBSA burn that had at least two computer-based wound mappings. The % open wound (%OW) was calculated over time to document healing trajectory until successful healing or death. Only 2% of patients in the group with successful wound healing died. A decrease in the %OW of 0.8 (IQR: 0.7-1.1) was associated with survival. Disparities in wound healing trajectories between survivors and non-survivors were distinguishable by 2weeks post-injury (P<0.05). When %TBSA was stratified by decile, the 40-49% TBSA group had the highest healing rate. Taken together, the data indicate that wound healing trajectory (%OW) varies with injury severity and survival. As such, automated mapping of wound healing trajectory may provide valuable information concerning patient/prognosis, and may recommend early interventions to optimize wound healing.

Keywords: Burns; Decision-support; Open wound size; Wound healing.

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Automation
  • Body Surface Area
  • Burns / mortality
  • Burns / pathology
  • Burns / therapy*
  • Female
  • Humans
  • Linear Models
  • Logistic Models
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Prognosis
  • Renal Replacement Therapy / statistics & numerical data
  • Retrospective Studies
  • Skin Transplantation
  • Software*
  • Survival Rate*
  • Wound Healing*