International Journal of Clinical Research

Objective To explore the risk factors for delayed extubation after thoracoscopic radical resection of esophageal cancer and to construct a predictive model. Methods The clinical data of 285 patients who underwent thoracoscopic radical resection of esophageal cancer in our hospital from January 2023 to October 2024 were selected. The patients were divided into two groups based on the extubation time after surgery: the delayed extubation group (>1 hour, n=111) and the non-delayed extubation group (≤1 hour, n=174). Univariate analysis was used to identify the factors related to delayed extubation, and multivariate Logistic regression analysis was conducted to screen the independent risk factors for delayed extubation and establish a predictive model. The receiver operating characteristic (ROC) curve was drawn to evaluate the performance of the model. Results Multivariate analysis showed that age, ASA grade ≥ III, operation time, intraoperative urine output, and intraoperative use of nerve block were predictive factors for delayed extubation (P < 0.05). The AUC of the predictive model was 0.784 (95% CI 0.727 - 0.841, P < 0.05), indicating that the predictive model has significant clinical value in predicting delayed extubation after thoracoscopic radical resection of esophageal cancer. Conclusion Age, ASA grade ≥ III, operation time, intraoperative urine output, and intraoperative use of nerve block are independent predictive factors for delayed extubation in patients undergoing thoracoscopic radical resection of esophageal cancer (P < 0.05). The model established based on these factors has good predictive value.

Esophageal cancer; Thoracoscopic surgery; Delayed extubation; Predictive model