ObjectiveDeep 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.MethodsBetween 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.ResultsThe 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.ConclusionThis 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.