Predicting cardiac surgical site infection: development and validation of the Barts Surgical Infection Risk tool

Objectives: The objective of this study was to develop and validate a new risk tool (Barts Surgical Infection Risk (B-SIR)) to predict surgical site infection (SSI) risk after all types of adult cardiac surgery, and compare its predictive ability against existing (but procedure-specific) tools: Brompton-Harefield Infection Score (BHIS), Australian Clinical Risk Index (ACRI), National Nosocomial Infection Surveillance (NNIS). Study Design and Setting: Single-center retrospective analysis of prospectively collected data including 2,449 patients undergoing cardiac surgery between January 2016 and December 2017 in a European tertiary hospital. Thirty-four variables associated with SSI risk after cardiac surgery were collated from three local databases. Independent predictors were identified using stepwise multivariable logistic regression. Boot-strap resampling was conducted to validate the model. Hosmer-Lemeshow goodness-of-fit test was performed to assess calibration of scores. Results: The B-SIR model was constructed from six independent predictors female gender, body mass index >30, diabetes, left ventricular ejection fraction <45%, peripheral vascular disease and operation type, and the risk estimates were derived. The receiver operating characteristics curve for B-SIR was 0.682, vs. 0.603 for BHIS, 0.618 for ACRI, and 0.482 for the NNIS tool. Conclusion: B-SIR provides greater predictive power of SSI risk after cardiac surgery compared with existing tools in our population. (C) 2020 Elsevier Inc. All rights reserved.