Objective: By analyzing the clinical data of patients with stage I non-small-cell lung cancer (NSCLC) under treatment of video-assisted thoracic surgery (VATS), this study aims to explore the predict value and impacts of the major complications. Methods: A total of 806 patients diagnosed as stage Ⅰ NSCLC and received VATS were enrolled from February 2012 to March 2019 in our hospital. Patients were divided into major complications group (n=51) and non-major-complications group (n=755). Comparing the clinical data between the patients in the two groups, such as age, gender, smoking, pulmonary infection and pulmonary functions by single factor analysis. The multi-factor analysis was performed to explore the risk factors and prediction model of major complications.Results: The primary complications were pulmonary and cardiovascular complications. Gender (χ2=10.861,P=0.001), smoking(χ2=4.351,P=0.037), lung infection before operation (χ2=7.992,P=0.005), complications before operation (χ2=22.909,P<0.001), FEV1(t=3.334, P=0.013), FEV1%(t=5.599, P<0.001), operation time (t=6.687, P=0.007), blood loss(t=5.990, P=0.024) showed significantly differences between the two groups. The multi-factor analysis showed that lung infection before operation(OR=4.302, 95%CI:3.670-5.042), complications before operation(OR=1.863, 95%CI:1.348-2.574), operation time (OR=5.546, 95%CI:4.332-7.099), blood loss (OR=6.098, 95%CI:3.908-9.515)were the independent risk factors of major complications after VATS. The prediction model acquired using the Enter for major complications was P=1/(1+e-y),y=-3.140+1.459×lung infection before operation+0.622×complications before operation+1.713×operation time+1.909×blood looss. The area under ROC curve was 0.973, with the 95%CI being 0.948-0.997, sensitivity being 82.0%, specificity being 84.2%. Conclusion: Lung infection before operation, complications before operation, operation time, blood loss were the independent risk factors of major complications after VATS in elderly patients with stage Ⅰ NSCLC. These factors have the potential to predict major complications.
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