摘要
目的:分析肺癌胸腔镜肺段切除术后合并肺不张的危险因素,并构建预测模型。方法:回顾性分析2021年2月—2023年2月在我院行胸腔镜肺段切除手术治疗的585例肺癌病人临床资料,根据术后是否发生肺不张将其分为肺不张组和非肺不张组。采用多因素Logistic回归筛选影响肺癌胸腔镜肺段切除术后合并肺不张的危险因素,运用R软件建立预测肺癌胸腔镜肺段切除术后合并肺不张的随机森林模型,并检测模型效能。结果:585例肺癌病人,术后肺不张发生率为8.55%;多因素结果显示,体质指数≥24 kg/m2、吸烟史、基础疾病、术前肺功能较差、手术时间≥2 h、腺癌均是胸腔镜肺段切除术后发生肺不张的独立危险因素(P<0.05);随机森林预测肺癌胸腔镜肺段切除术后肺不张发生的预测因子重要性排序为术前肺功能、体质指数、吸烟史、手术时间、基础疾病、肿瘤病理类型;受试者工作特征(ROC)曲线分析显示,随机森林算法预测肺不张发生的ROC曲线下面积(0.841)高于多因素Logistic回归模型(0.834)。结论:体质指数≥24 kg/m2、吸烟史、基础疾病、术前肺功能较差、手术时间≥2 h、腺癌均是胸腔镜肺段切除术后病人发生肺不张的独立危险因素,基于上述因素构建的随机森林模型具有良好的预测效能。
Objective:To analyze the risk factors of lung cancer complicated with atelectasis after thoracoscopic segmental resection,and to construct a prediction model.Methods:585 patients with lung cancer who underwent thoracoscopic segmental resection in our hospital from February 2021 to February 2023 were retrospectively selected as the study objects,and they were divided into atelectasis group and non-atelectasis group according to whether they developed atelectasis after surgery.Clinical data of patients with lung cancer were collected,and multi-factor Logistic regression was used to screen the risk factors affecting atelectasis after thoracoscopic segmental resection of lung cancer.R software was used to establish a random forest model for predicting atelectasis,and the effectiveness of the model was verified.Results:The incidence of atelectasis was 8.55%in 585 patients with lung cancer after thoracoscopic segmental resection.Multivariate results showed that BMI≥24 kg/m2,smoking history,underlying diseases,poor preoperative pulmonary function,operative time≥2 h and adenocarcinoma were independent risk factors for atatasis after thoracoscopic lung resection(P<0.05).The relative important predictors of lung atatasis after thoracoscopic segmental resection in random forest were preoperative lung function,BMI,smoking history,operation time,underlying disease,and pathological type of tumor.ROC results showed that the AUC of random forest algorithm in predicting the occurrence of atatasis was slightly higher than that of multivariate Logistic regression model(0.841 vs 0.834).Conclusion:BMI≥24 kg/m2,smoking history,underlying diseases,poor preoperative pulmonary function,operative time≥2 h,and adenocarcarcinoma are independent risk factors for atectasis after thoracoscopic segmental resection.Based on these factors,the random forest model for predicting atectasis has good risk prediction efficacy.
作者
陈倩倩
彭纪芳
刘晗
CHEN Qianqian;PENG Jifang;LIU Han(Jiangsu Provincial People′s Hospital/The First Affiliated Hospital of Nanjing Medical University,Jiangsu 210029 China)
出处
《护理研究》
北大核心
2024年第21期3812-3817,共6页
Chinese Nursing Research
关键词
肺癌
胸腔镜肺段切除术
肺不张
危险因素
预测模型
调查研究
lung cancer
thoracoscopic segmentectomy
atelectasis
risk factors
prediction model
investigation research
