Development and external validation of a perioperative clinical model for predicting myocardial injury after major abdominal surgery: A retrospective cohort study.

PURPOSE

We aimed to develop and validate a predictive model for myocardial injury in individuals undergoing major abdominal surgery.

METHODS

This multicenter retrospective cohort analysis included 3546 patients aged ≥45 years who underwent major abdominal surgeries at two Chinese tertiary hospitals. The primary outcome was myocardial injury after noncardiac surgery (MINS), defined as prognostically relevant myocardial injury due to ischemia that occurs during or within 30 days after noncardiac surgery. The LASSO algorithm and logistic regression were used to construct a predictive model for postoperative MINS in the development cohort, and the performance of this prediction model was validated in an external independent cohort.

RESULTS

A total of 3546 patients were included in our study. MINS manifested in 338 (9.53 %) patients after surgery. The definitive predictive model for MINS was developed by incorporating age, American Society of Anesthesiologists (ASA) classification, preoperative hemoglobin concentration, preoperative serum ALB concentration, blood loss, total infusion volume, and operation time. The area under the curve (AUC) of our model was 0.838 and 0.821 in the derivation and validation cohorts, respectively.

CONCLUSIONS

Preoperative hemoglobin levels, preoperative serum ALB concentrations, infusion volume, and blood loss are independent predictors of MINS. Our predictive model can prove valuable in identifying patients at moderate-to-high risk prior to non-cardiac surgery.