| Objective To analyze the risk factors of pulmonary infection after cardiac surgery and construct a nomogram prediction model, so as to provide reference for early screening of high-risk groups and targeted prevention and control measures.Methods Case data of 1 188 patients undergoing cardiac surgery from January 2019 to December 2023 were collected, and the training group and validation group were randomly divided in a ratio of 7∶3. Based on logistic regression to analyze the predictors of pulmonary infection after cardiac surgery, the risk prediction model was established and validated. The model was evaluated by area under the receiver operating characteristic curve (AUC), calibration curve and decision curve analysis.Results Of the 1 188 patients, 148 (12.5%) had pulmonary infections. Independent risk factors for pulmonary infection after cardiac surgery were emergency department admission, history of smoking, chronic obstructive pulmonary disease, postoperative renal insufficiency, reintubation, intraoperative blood transfusion volume and tracheal intubation time. The AUC value was 0.923, and the specificity and sensitivity was 0.804 and 0.885, respectively; in the validation group, the AUC value was 0.946, the specificity and sensitivity was 0.788 and 0.977, respectively. The model showed good discrimination, high calibration and net benefit.Conclusion The constructed predictive model has certain predictive value, which can be used for risk assessment and individualized treatment of pulmonary infection in patients after cardiac surgery. |
