ESTABLISHMENT OF A PREDICTIVE MODEL FOR POSTOPERATIVE PULMONARY COMPLICATIONS AFTER TOTAL GASTRECTOMY FOR UPPER GASTRIC CANCER

Objective To establish a nomogram risk predictive model by analyzing the risk factors for postoperative pulmonary complications (PPCs) after total gastrectomy for upper gastric cancer. Methods A retrospective analysis was performed for the clinical data of 197 patients who underwent total gastrectomy for upper gastric cancer in our hospital from June 1, 2020 to September 30, 2021. Univariate and multivariate Logistic regression analyses were used to investigate the risk factors for PPCs, and a nomogram predictive model for PPCs was established. Index of concordance, the receiver operating characteristic (ROC) curve, and the calibration curve were used to evaluate the performance of the predictive model, and the DCA curve was used to evaluate the clinical benefit of the model. Results Among the 197 patients included in the analysis, 71 experienced PPCs, with an incidence rate of 36%.The multivariate Logistic regression analysis showed that age, diabetes mellitus, smoking history, preoperative serum albumin 26 kg/m2 were independent risk factors for PPCs after total gastrectomy for upper gastric cancer. The nomogram prediction model established had an area under the ROC curve of 0.806, suggesting that the model had good prediction performance. The calibration curve showed that the predictive model showed good consistency with the actual incidence rate of complications, and the DCA curve showed obvious positive net benefits, indicating that the predictive model had good clinical benefits. Conclusion The nomogram prediction model established based on independent risk factors has good prediction performance and can provide a basis for predicting PPCs in patients undergoing total gastrectomy for upper gastric cancer.