Web-based Calculator Predicts Surgical Site Infection after Thoracolumbar Spine Surgery

Abstract Background Surgical site infection (SSI) after spine surgery leads to increased length of stay, reoperation, and worse patient quality of life. We sought to develop a web-based calculator that computes an individual’s risk of a wound infection following thoracolumbar spine surgery Methods We performed a retrospective review of consecutive patients undergoing elective degenerative thoracolumbar spine surgery at a tertiary-care institution between January 2016 and December 2018. Patients who developed SSI requiring reoperation were identified. Regression analysis was performed and model performance was assessed using receiver operating curve (ROC) analysis to derive an area under the curve (AUC). Bootstrapping was performed to check for overfitting and a Hosmer-Lemeshow test was employed to evaluate goodness-of-fit and model calibration. Results 1259 patients were identified; 73% were index operations. The overall infection rate was 2.7%, and significant predictors of SSI included female gender (OR=3.0), higher BMI (OR=1.1), active smoking (OR=2.8), worse ASA physical status (OR=2.1), and higher surgical invasiveness (OR=1.1). The prediction model had an optomism-corrected AUC of 0.81. A web-based calculator was created: https://jhuspine2.shinyapps.io/Wound_Infection_Calculator/ . Conclusion In this pilot study, we developed a model and simple web-based calculator to predict a patient’s individualized risk of SSI after thoracolumbar spine surgery. This tool has a predictive accuracy of 83%. Through further multi-institutional validation studies, this tool has the potential to alert both patients and providers of an individual’s SSI risk to improve informed consent, mitigate risk factors, and ultimately drive down rates of SSIs.