Cai Haoliang, Wu Xiaohui, Chen Xi, Guo Jun, Chen Wenting
Haoliang Cai, Department of Anesthesiology, Shuguang Hospital, Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, P.R. China.
Xiaohui Wu, Department of Anesthesiology, Shuguang Hospital, Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, P.R. China.
Pak J Med Sci. 2024 Oct;40(9):2022-2027. doi: 10.12669/pjms.40.9.10087.
To identify risk factors for complications in patients undergoing gastrointestinal endoscopy under acupuncture anesthesia and to construct a nomogram predictive model.
This retrospective study included 292 patients who underwent gastrointestinal endoscopy under acupuncture anesthesia at the Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from June 2020 to May 2023. Logistic regression analysis was used to identify risk factors for complications in patients undergoing gastrointestinal endoscopy under acupuncture anesthesia. A nomogram prediction model was constructed using the RMS package of R4.1.2 software based on the independent risk factors identified. The predictive performance of the model was assessed using consistency index (C-index), calibration curve, and receiver operating characteristic (ROC) curve.
Seventy-five patients (25.68%) had complications. Body mass index (BMI), history of cardiovascular diseases, fasting time, history of respiratory diseases, and Sedation-Agitation Scale (SAS) score were identified as risk factors for complications. Based on this risk, a nomogram predictive model was constructed. The C-index of the nomogram model was 0.927. Calibration curve showed a good consistency between actual observations and nomogram predictions. The ROC curve area under curve (AUC) was 0.927 (95% CI: 0.895-0.959), indicating a certain predictive value for the occurrence of complications. When the optimal cut-off value was selected, the sensitivity and specificity of the model were 77.0% and 92.0%, respectively, indicating that the predictive model was effective.
BMI, history of cardiovascular disease, fasting time, history of respiratory disease, and SAS score are independent risk factors for complications in patients undergoing gastrointestinal endoscopy under acupuncture anesthesia. The constructed nomogram predictive model has a good performance in predicting the occurrence of complications in patients undergoing gastrointestinal endoscopy with under acupuncture anesthesia.
识别接受针刺麻醉下胃肠内镜检查患者并发症的危险因素，并构建列线图预测模型。
本回顾性研究纳入了2020年6月至2023年5月在上海中医药大学附属曙光医院接受针刺麻醉下胃肠内镜检查的292例患者。采用Logistic回归分析识别接受针刺麻醉下胃肠内镜检查患者并发症的危险因素。基于识别出的独立危险因素，使用R4.1.2软件的RMS包构建列线图预测模型。使用一致性指数（C指数）、校准曲线和受试者工作特征（ROC）曲线评估模型的预测性能。
75例患者（25.68%）发生并发症。体重指数（BMI）、心血管疾病史、禁食时间、呼吸系统疾病史和镇静-躁动评分（SAS）被确定为并发症的危险因素。基于这些风险，构建了列线图预测模型。列线图模型的C指数为0.927。校准曲线显示实际观察值与列线图预测值之间具有良好的一致性。ROC曲线下面积（AUC）为(0.927)（95%CI：0.895 - 0.959），表明对并发症的发生具有一定的预测价值。选择最佳截断值时，模型的敏感性和特异性分别为77.0%和92.0%，表明该预测模型有效。
BMI、心血管疾病史、禁食时间、呼吸系统疾病史和SAS评分是接受针刺麻醉下胃肠内镜检查患者并发症的独立危险因素。构建的列线图预测模型在预测接受针刺麻醉下胃肠内镜检查患者并发症的发生方面具有良好的性能。
