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Abstract Background Postoperative pulmonary complications (PPCs) remain a prevalent concern among elderly surgical patients, with a notably higher incidence observed in the elderly undergoing thoracic surgery. This study aimed to construct a nomogram to predict the risk of PPCs in this population. Methods A total of 2963 elderly patients who underwent thoracic surgery were randomly enrolled and divided into a training cohort (80%, n = 2369) and a validation cohort (20%, n = 593). Univariate and multivariate logistic regression analyses were conducted to identify risk factors for PPCs, and a nomogram was developed based on the findings from the training cohort. The validation cohort was used to validate the model. The predictive accuracy of the model was evaluated by receiver operating characteristic curve (ROC), area under ROC (AUC), calibration curve and decision curve analysis (DCA). Results A total of 918 (31.0%) patients reported PPCs. Nine independent risk factors for PPCs were identified: preoperative presence of chronic obstructive pulmonary disease (COPD), elevated leukocyte count, higher partial pressure of arterial carbon dioxide (PaCO2) levels, location of surgery, thoracotomy, intraoperative hypotension, blood loss > 100 mL, surgery duration > 180 min and malignant tumor. The AUC value for the training cohort was 0.739 (95% CI: 0.719–0.762), and that for the validation cohort was 0.703 (95% CI: 0.657–0.749). The P values for the Hosmer-Lemeshow test were 0.633 and 0.144 for the training and validation cohorts, respectively, indicating good calibration curve fit. The DCA curve showed that the nomogram could be applied clinically if the risk threshold was between 12% and 84%, which was found to be between 8% and 82% in the validation cohort. Conclusions This study underscores the pressing need for early detection of PPCs in elderly patients undergoing thoracic surgery. The nomogram exhibited promising predictive efficacy for PPCs in elderly individuals undergoing thoracic surgery, enabling the identification of high-risk patients and consequently aiding in the implementation of preventive interventions.
Liu et al. (Thu,) studied this question.