Construction of a Risk Prediction Model for the Occurrence of Delirium After Thoracoscopic Radical Esophageal Cancer Surgery Based on the CART Decision Tree Model

SHEN Guanhong; XU Hanli

doi:10.3639/j.issn.2095-3097.2024.09.015

Abstract：Objective To investigate the influencing factors of postoperative delirium(POD)after thoracoscop-ic radical surgery for esophageal cancer(EC),and to construct a decision tree prediction model for POD occurrence using the classification and regression tree(CART)algorithm.Methods A total of 194 patients who underwent thoracoscop-ic radical EC surgery at the Department of Cardiothoracic Surgery,No.904 Hospital of the PLA Logistics Support Unit from January 2023 to January 2024 were enrolled and divided into the POD and non-POD groups based on postopera-tive outcomes.Clinical data,laboratory indices,and surgery-related parameters were collected.Risk factors significant-ly associated with POD were identified through univariate and multivariate analyses,and the CART decision tree mod-el for POD prediction was constructed using SPSS Modeler software.The predictive efficacy of the model was evaluated.Results Among the 194 patients,90(46.39％)developed POD,while 104 did not.Significant differences were observed be-tween the POD and non-POD groups in terms of age,excessive alcohol consumption history,and deep se-dation(P＜0.05).Hemoglobin levels were lower in the POD group compared to the non-POD group(P＜0.05),and postoperative pain scores and the proportion of pa-tients with intraoperative hypotension were higher in the POD group(P＜0.05).Multivariate logistic regression identified advanced age,excessive alcohol consumption history,deep sedation,low hemoglobin levels,postoperative pain scores,and intraoperative hypotension as risk factors for POD(P＜0.05).Six variables showing significant differences in univariate analysis were included in the CART model,which screened five explana-tory variables:hemoglobin,intraoperative hypotension,age,postoperative pain score,and excessive alcohol consumption history.The decision tree model comprised 5 levels and 7 terminal nodes,with hemoglobin being the most critical predictor.The AUC of the CART decision tree model was 0.837(95％CI:0.777-0.886),higher than the AUC of the logistic regression model(0.777,95％CI:0.712-0.834)for predicting POD(P=0.009).Conclusion Advanced age,excessive alcohol consumption history,deep sedation,low hemoglobin levels,postoperative pain scores,and intraoperative hypotension are significant risk factors for POD following thoracoscopic EC radical surgery.The CART-based POD risk prediction model demonstrated good predictive performance,offering valuable guidance for early POD identification,risk assessment,and tailored interventions.