ABSTRACT
Objective:To predict the influencing factors of postoperative pulmonary complications(PPCs)in patients with lung cancer after video-assisted thoracic surgery by using the cardiopulmonary exercise test(CPET)combined with clini-cal indicators,and to draw a nomogram model to make the prediction results more intuitive and visualized. Method:The relevant data in patients with lung cancer who underwent video-assisted thoracic surgery in the thoracic surgery department of our hospital was retrospectively collected.Single factor analysis and multivariate logistic stepwise analysis were used to find out the independent influencing factors of PPCs.The nomograph model of PPCs risk was drawn and internal verification was done to get the calibration curve.Finally,the ar-ea under the curve(AUC)and 95％confidence interval(CI)were calculated by the receiver operating charac-teristic(ROC)curve. Result:There were 168 patients in total,including 45 patients in the complication group(26.8％)and 123 pa-tients in the non-complication group(73.2％).Unifactor analysis results showed that the occurrence of PPCs was significantly correlated with age,stage,smoking history,intraoperative blood loss,coronary heart dis-ease,VO2peak,VENCO2 slope,AT and PetCO2(P＜0.05),but not with other factors(P＞0.05),and the length of postoperative hospital stay in the complication group was significantly higher than that in the non-complica-tion group(P＜0.05).Multivariate analysis results showed that age(OR=6.51,95％CI:1.89-22.45,P＜0.05),intraoperative blood loss(OR=5.16,95％CI:0.93-1.00,P＜0.05)and VENCO2 slope(OR=0.96,95％CI:1.64-16.25,P＜0.05)were independent influencing factors for PPCs occurrence in VATS pneumonectomy.Af-ter constructing the nomogram model topredict the occurrence of PPCs,the ROC curve was used to analyze the discrimination of the nomogram prediction model.The results of the nomogram model with the ROC curve showed that AUC was 0.792(95％CI:0.71-0.87),and the sensitivity and specificity of PPCs prediction were 76.4％and 77.8％.Hosmer-lemesho x2=11.595,P=0.170,indicating that the difference between the predicted value of the model and the actual observed value was not statistically significant,and the prediction model had good calibration ability. Conclusion:The CPET combined with clinical indicators to make the prediction of PPCs more comprehensive and reliable.The nomogram model can be more intuitive,objective and individual to assess the risk of PPCs in lung cancer patients.