影响达芬奇机器人手术系统胃癌根治术手术时间延长预测模型的构建及其应用价值  

Construction and application value of a predictive model for prolonged surgical duration in Da Vinci robotic radical gastrectomy for gastric cancer

作　　者：薛震 郑华龙 林嘉 陆俊[1] 李平[1] 谢建伟[1] 王家镔[1] 林建贤[1] 陈起跃[1] 郑朝辉[1] 黄昌明[1] Xue Zhen;Zheng Hualong;Lin Jia;Lu Jun;Li Ping;Xie Jianwei;Wang Jiabin;Lin Jianxian;Chen Qiyue;Zheng Chaohui;Huang Changming(Department of Gastric Surgery,Key Laboratory of Gastrointestinal Cancer of Ministry of Education,Fujian Medical University Union Hospital,Fuzhou 350004,China)

机构地区：[1]福建医科大学附属协和医院胃外科、消化道恶性肿瘤教育部重点实验室,福州350004

出　　处：《中华消化外科杂志》2023年第12期1456-1466,共11页Chinese Journal of Digestive Surgery

基　　金：“福建省医疗“创双高”建设经费资助”(闽卫医政〔2021〕76号)。

摘　　要：目的探讨影响达芬奇机器人手术系统胃癌根治术手术时间延长预测模型的构建及其应用价值。方法采用回顾性队列研究方法。收集2016年8月至2021年8月福建医科大学附属协和医院收治的534例行达芬奇机器人手术系统胃癌根治术患者的临床病理资料;男389例,女145例;年龄为(60±11)岁。534例患者通过SPSS 25.0软件按随机数法以7∶3比例随机分为训练集374例和验证集160例。观察指标:(1)患者手术时间延长情况。(2)手术时间延长和未延长患者术中及术后情况。(3)手术时间延长和未延长患者并发症发生情况。(4)影响患者手术时间延长危险因素分析。(5)手术时间延长人工神经网络预测模型的构建及其预测效能评价。正态分布的计量资料以x±s表示,组间比较采用独立样本t检验。偏态分布的计量资料以M(Q1,Q3)表示,组间比较采用Mann-WhitneyU检验。计数资料以绝对数和百分比表示,组间比较采用χ^(2)检验或Fisher确切概率法。等级资料比较采用非参数检验。单因素和多因素分析采用Logistic回归模型。基于单因素分析结果,采用多层感知器训练手术时间延长人工神经网络预测模型,绘制受试者工作特征(ROC)曲线,以曲线下面积(AUC)、准确率、灵敏度、特异度、阳性预测值、阴性预测值评价预测模型的效能。结果(1)患者手术时间延长情况。534例患者中,行全胃切除术和远端胃切除术分别为284、250例,手术时间分别为(206±42)min、(187±36)min。行全胃切除术手术时间延长和未延长患者分别为41、243例,行远端胃切除术手术时间延长和未延长患者分别为40、210例。81例手术时间延长患者性别(男、女),年龄,体质量指数(BMI),肿瘤长径,肿瘤位置(胃上部、胃中部、胃下部、混合型),新辅助治疗,术前美国麻醉医师协会(ASA)评分(1分、2分、3分),临床T分期(T1期、T2期、T3期、T4a期),临床N分期(N0期、N1期Objective To investigate the construction and application value of a predictive model for prolonged surgical duration in Da Vinci robotic radical gastrectomy for gastric cancer.Methods The retrospective cohort study was conducted.The clinicopathological data of 534 patients who underwent Da Vinci robotic radical gastrectomy for gastric cancer in the Fujian Medical University Union Hospital from August 2016 to August 2021 were collected.There were 389 males and 145 females,aged(60±11)years.All 534 patients were randomly divided into the training dataset of 374 cases and the validation dataset of 160 cases with a ratio of 7∶3 based on random number method in the SPSS 25.0 software.Observation indicators:(1)incidence of prolonged surgical duration;(2)intraoperative and postoperative conditions in patients with prolonged surgical duration and without prolonged surgical duration;(3)complications in patients with prolonged surgical duration and without prolonged surgical duration;(4)analysis of risk factors influencing prolonged surgical duration;(5)construction and evaluation of an artificial neural network predictive model for prolonged surgical duration.Measurement data with normal distribution were represented as Mean±SD,and comparison between groups was conducted using the independent sample t test.Measurement data with skewed distribution were represented as M(Q1,Q3),and comparison between groups was conducted using the Mann-Whitney U test.Count data were described as absolute numbers or percentages,and comparison between groups was conducted using the chi-square test or Fisher exact probability.Comparison of ordinal data was analyzed using the nonparametric test.Univariate and multivariate analyses were conducted using the Logistic regression model.Based on the results of univariate analysis,a multilayer perceptron was employed to train an artificial neural network predictive model for prolonged surgical duration.The receiver operating characteristic(ROC)curve was drawn,and the area under curve(AUC),the accu

关 键 词：胃肿瘤 外科手术 根治性切除 达芬奇机器人手术系统 手术时间延长 预测模型 应用价值 

分 类 号：R735.2[医药卫生—肿瘤]