This study aimed to develop and validate a risk prediction model based on real-world data to assess the risk of delayed recovery from anesthesia in elderly lung adenocarcinoma patients underwent video-assisted thoracoscopic (VATS) radical resection. This study is a retrospective study of real-world data. A total of 257 elderly lung adenocarcinoma patients who underwent VATS radical resection from January 2022 to December 2023 in a tertiary hospital in Wuhan were selected. Patients were divided into delayed recovery (n = 42) and non- delayed recovery group (n = 215) according to whether delayed recovery occurred after anesthesia. Lasso regression was used to screen the independent variables. Logistic regression was used to analyze the risk factors of delayed recovery from anesthesia, and a nomogram model was established. Bootstrap method was used to internally verify the nomogram model. Delayed recovery from anesthesia occurred in 42 of 257 elderly lung adenocarcinoma patients underwent VATS radical resection (16.34%). Logistic regression analysis showed that anesthesia duration, intraoperative infusion volume, inhaled desflurane, preoperative respiratory tract infection, intraoperative hypothermia and diagnosed with hypertension were risk factors for delayed recovery from anesthesia in elderly lung adenocarcinoma patients underwent VATS radical resection (P<0.05). The area under receiver operating characteristic curve was 0.869, 95% CI (0.815 ~ 0.923). The optimal cutoff value was 0.198, the sensitivity was 0.738, and the specificity was 0.823. Hosmer-Lemeshow test showed that χ2 = 7.346, P = 0.500. The decision curve analysis results have shown that the threshold probability is between 0.23 and 0.91, and the net benefit rate of the model is good. The risk prediction model constructed in this study can provide reference for medical staff to screen precisely high-risk of delayed recovery from anesthesia in elderly lung adenocarcinoma patients underwent VATS radical resection, which is of great significance.
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