Abstract 117: Prevalence, Independent Risk Factors, And A Model To Predict Chronic Nerve Pain After Burn Injury

Abstract

Purpose: Chronic pain, unrelated to the burn itself, can manifest as a long-term complication in patients sustaining burn injuries. The purpose of this study was to determine the prevalence, independent associated risk factors, and construct a mathematical model predicting a patient’s risk of developing chronic nerve pain (CNP) after burn injury. Methods: A retrospective analysis was conducted from 1880 adults admitted to a single institution’s Burn Unit from 2014-2019. Of the 1880 patients, 113 developed CNP. CNP was defined as patient-described pain evaluated by ≥two clinicians for ≥six months after burn injury, unrelated to a pre-existing illness/medications. Comparisons between patients admitted to the Burn Unit with no pain and patients admitted to the Burn Unit who developed CNP were performed using binary logistic regression. The modified Delphi process was used for selection of 78 potential risk variables. Multivariate regression techniques were used to derive the model, Brier scores assessed model performance, Area-under-the-curve (AUC) assessed model discrimination, Hosmer-Lemeshow goodness-of-fit test assessed model calibration, and stratified K-fold cross-validation assessed model accuracy and generalizability. Follow-up for the model was set to six months. Results: One hundred thirteen (n=113) of the 1880 burn patients developed CNP as a direct result of burn injury over five years with a prevalence of 6%. Independent risk factors associated with developing CNP were substance abuse (OR=3.7, 95%CI [1.6, 8.6]; p=0.003), current everyday smokers (OR=3.9, 95%CI [1.9, 8.3]; p<0.001), intubated on mechanical ventilation (OR=2.7, 95%CI [1.3, 5.7]; p=0.009), greater number of surgeries (OR=7.5, 95%CI [2.9, 19.2]; p<0.001), and longer hospital LOS (OR=86.9, 95%CI [6.1, 1241.5]; p<0.001). Prevalence rates of CNP were similar in the development (6%) and validation (5.4%) cohorts. CNP risk score=-4.1 + 0.34(substance use)+0.45(tobacco use)+0.93(surgical treatment)+1.02(%TBSA). Algorithm=1-1/[1+exp(risk score)] for six months post-burn CNP risk score. The model was calibrated to accurately predict the probability of developing CNP. As the number of risk factors increase, the probability of CNP increases. Conclusions: The prevalence of CNP over five years was 6% in the Burn Center. Substance abuse, current everyday smoking, third degree burns, being intubated on mechanical ventilation, having more surgeries and longer hospital LOS were associated with developing CNP following burn injury. We present a novel model that accurately predicts a patient’s risk of developing CNP after burn injury, with substance use, tobacco use, surgical treatments, and %TBSA representing the greatest predictors.