RISK INDEX FOR PREDICTION OF SURGICAL SITE INFECTION AFTER ONCOLOGY OPERATIONS

Introduction: Several studies have shown that surgical site infections represent most hospital-acquired infections, with the major impact be ing on average hospital stay and cost of hospitalization. Methods: To develop a risk model for prediction of surgical site infections in can cer patients undergoing operative procedures and identify those with h igh probability of infection we performed a prospective cohort study i n a tertiary cancer care hospital in Rio de Janeiro, Brazil. Risk fact ors were studied in single and multivariate analyses. Results: Over a 24-month period, 1205 patients underwent operations for malignant dise ase. The overall surgical site infection rate was 17.3%. A multivariat e stepwise logistic regression model identified six independent predic tive risk factors: contaminated and infected operations, surgical dura tion greater than 280 minutes, male sex, prior radiotherapy, American Society of Anesthesiology class III to V, and antimicrobial prophylaxi s not according to protocol. On the basis of individual risk scores, t wo groups of patients were identified: a low-risk (score less than or equal to 8; surgical site infection rate 10%) and a high-risk group (s core greater than or equal to 9; surgical site infection rate 33.6%; r elative risk 3.4; 95% confidence interval 2.6 to 4.4). Conclusion: The oncology risk model allowed for the identification of a high-risk sco re group of patients and implementation of a more efficient and select ive intervention program.