Analysis of risk factors for unplanned reoperation and construction of a prediction model based on propensity score matching
Objective To analyze the risk factors of unplanned reoperation and construct a nomogram-based risk prediction model to identify high-risk patients,so as to provide a basis for perioperative manage-ment to reduce the rate of reoperation.Methods A total of 880 patients with underwent unplanned reopera-tion between 2018 and 2021 were included as the unplanned reoperation group.Using propensity score matc-hing,2640 patients were matched in a 1∶3 ratio to form the control group.Potential risk factor indicators were collected and subjected to univariate analysis.Significant indicators were then selected for multivariable logistic regression analysis to construct the risk prediction model.The predictive value of the model was evalu-ated.Results For unplanned reoperation,The number of complications 3-5 (OR=1.84),the number of complications 6-10 (OR=2.94),combined with maligant tumor (OR=1.75),combined with end-stage renal disease (OR=1.92),major surgery grade 3 (OR=4.27),major surgery grade 4 (OR=7.26),and incision grade Ⅰ,Ⅱ,Ⅲ (OR=2.18,1.97,6.85) were independent factors (P<0.05).The model passed the calibra-tion degree test,and the area under ROC curve (AUC) was 0.715,indicating good model differentiation.Con-clusion A risk prediction model based on risk factors can help identify high-risk populations for unplanned reoperation and suggest corresponding measures for prevention.
万方数据
维普
