机器人辅助腹腔镜肝切除术后谵妄危险因素分析及定量预警模型建立与验证分析  

Analysis of risk factors for delirium after robot-assisted laparoscopic liver resection and establishment of a quantitative warning model for validation

作　　者：冉君 马红梅[1] 肖彬彬 RAN Jun;MA Hongmei;XIAO Binbin(Department of Geriatrics,Renmin Hospital of Wuhan University,Wuhan 430060,China;Tongji Hospital,Tongji Medical College,Huazhong University of Science and Technology,Wuhan 430030,China)

机构地区：[1]武汉大学人民医院老年科,湖北武汉430060 [2]华中科技大学同济医学院附属同济医院,湖北武汉430030

出　　处：《机器人外科学杂志（中英文）》2024年第5期932-938,共7页Chinese Journal of Robotic Surgery

基　　金：国家自然科学基金(81401187)。

摘　　要：目的:分析机器人辅助腹腔镜肝切除术后谵妄危险因素并建立与验证分析其定量预警模型。方法:选取2021年3月—2023年9月武汉大学人民医院收治的行机器人辅助腹腔镜肝切除术治疗的82例患者作为研究对象,采用二元Logistic回归分析机器人辅助腹腔镜肝切除术后谵妄的独立危险因素,构建定量预警模型,并用ROC分析模型的预测价值。结果:82例患者中发生术后谵妄17例(术后谵妄组),未发生术后谵妄65例(非术后谵妄组)。年龄≥60岁、体质指数<18 kg/m^(2)、术后疼痛程度为中度及以上均是机器人辅助腹腔镜肝切除术后谵妄的独立危险因素(P<0.05)。定量预警模型的AUC为0.820,灵敏度为0.706,特异度为0.800,修正偏差后的预测曲线趋于理想曲线,在阈值概率范围0.10至0.80之间表现出净收益率大于0的特点,超过了两条无效线,模型的预测能力和实用价值均较高。结论:年龄、体质指数、术后疼痛程度均是机器人辅助腹腔镜肝切除术后谵妄的独立危险因素。基于这些因素构建的定量预警模型的预测能力和实用价值均较高,有助于评估机器人辅助腹腔镜肝切除术后谵妄的风险并为其制定相应的干预措施。Objective:To analyze the risk factors for delirium after robot-assisted laparoscopic liver resection,and to establish a quantitative warning model for validating.Methods:82 patients who underwent robot-assisted laparoscopic liver resection in Renmin Hospital of Wuhan University from March 2021 to September 2023 were selected.Binary Logistic regression analysis was used to identify independent risk factors for delirium after robot-assisted laparoscopic liver resection.A quantitative warning model was constructed,and the ROC analysis model was used to predict its value.Results:Among the 82 patients,postoperative delirium occurred in 17 patients were divided into the postoperative delirium group,while 65 patients without postoperative delirium were divided into the non-postoperative delirium group.Age≥60 years old,BMI<18 kg/m^(2),and postoperative pain level of moderate or above were independent risk factors for delirium after robot-assisted laparoscopic liver resection(P<0.05).The AUC of the quantitative warning model was 0.820,with the sensitivity of 0.706 and the specificity of 0.800.After bias being corrected,the prediction curve turned to be an ideal curve,with a net benefit greater than 0 within the threshold probability range of 0.10 to 0.80 and exceeding two invalid lines,indicating that the model had high predictive ability and practical value.Conclusion:Age,BMI,and postoperative pain level are independent risk factors for postoperative delirium after robot-assisted laparoscopic liver resection.The quantitative warning model constructed based on these factors has high predictive ability and practical value,which can be used to evaluate the risk of delirium after robot-assisted laparoscopic liver resection effectively and develop corresponding intervention measures.

关 键 词：机器人辅助手术 腹腔镜肝切除术 术后谵妄 危险因素 定量预警模型 

分 类 号：R657.3[医药卫生—外科学]