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. Bootstrap 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.