Abstract
OBJECTIVE: Deep sternal wound infection following coronary artery bypass grafting is a serious complication associated with significant morbidity and mortality. Despite the substantial impact of deep sternal wound infection, there is a lack of specific risk stratification tools to predict this complication after coronary artery bypass grafting. This study was undertaken to develop a specific prognostic scoring system for the development of deep sternal wound infection that could risk-stratify patients undergoing coronary artery bypass grafting and be applied right after the surgical procedure. METHODS: Between March 2007 and August 2016, continuous, prospective surveillance data on deep sternal wound infection and a set of 27 variables of 1500 patients were collected. Using binary logistic regression analysis, we identified independent predictors of deep sternal wound infection. Initially we developed a predictive model in a subset of 500 patients. Dataset was expanded to other 1000 consecutive cases and a final model and risk score were derived. Calibration of the scores was performed using the Hosmer-Lemeshow test. RESULTS: The model had area under Receiver Operating Characteristic (ROC) curve of 0.729 (0.821 for preliminary dataset). Baseline risk score incorporated independent predictors of deep sternal wound infection: obesity (P=0.046; OR 2.58; 95% CI 1.11-6.68), diabetes (P=0.046; OR 2.61; 95% CI 1.12-6.63), smoking (P=0.008; OR 2.10; 95% CI 1.12-4.67), pedicled internal thoracic artery (P=0.012; OR 5.11; 95% CI 1.42-18.40), and on-pump coronary artery bypass grafting (P=0.042; OR 2.20; 95% CI 1.13-5.81). A risk stratification system was, then, developed. CONCLUSION: This tool effectively predicts deep sternal wound infection risk at our center and may help with risk stratification in relation to public reporting and targeted prevention strategies in patients undergoing coronary artery bypass grafting.