基于Logistic回归与决策树模型的结直肠癌术后患者非计划性再入院影响因素分析

doi:10.16460/j.issn1008-9969.2022.02.001

摘要/Abstract

摘要： 目的采用Logistic回归模型与决策树模型分析结直肠癌术后患者非计划性再入院的影响因素。方法回顾性分析2018年3月—2019年12月在胃肠外科接受手术治疗的1 383例结直肠癌患者的临床病例资料,分别建立Logistic回归模型与决策树模型,比较2种模型的分析结果。结果 1 383例结直肠癌术后患者71例非计划性再入院,非计划性再入院率为5.13%。Logistic回归模型分析显示,术后并发症、肿瘤TNM分期≥III期、术前合并症≥2项是结直肠癌术后患者非计划性再入院的独立危险因素。决策树模型分析显示,术后并发症是最主要的危险因素,其后依次为术前合并症≥2项、肿瘤TNM分期≥III期、肠造口、手术方式。Logistic回归模型的ROC曲线下面积为0.773,决策树模型为0.790,2个模型的ROC曲线下面积差异无统计学意义（Z=0.414,P>0.05）。结论术后并发症、肿瘤TNM分期≥III期和术前合并症≥2项是结直肠癌术后患者非计划性再入院的重要影响因素,Logistic回归模型与决策树模型对结直肠癌术后患者非计划性再入院影响因素的分析结果有较高的一致性,临床护士需采取针对性的预防和护理干预措施,降低患者非计划性再入院率。

关键词: Logistic回归, 决策树, 结直肠癌, 非计划性再入院

Abstract: Objective To analyze the risk factors of unplanned readmission in postoperative patients with colorectal cancer by logistic regression model and decision tree. Methods Clinical data of 1,383 patients with colorectal cancer who underwent surgery in department of gastrointestinal surgery from March 2018 to December 2019 were analyzed retrospectively. Logistic regression model and decision tree model were established respectively, and the results of the two models were compared. Results Seventy-one patients were readmitted unplannedly, with an unplanned readmission rate of 5.13%. Logistic regression model showed that postoperative complications, TNM stage≥III and more than 2 preoperative complications were independent risk factors. Decision tree model showed that postoperative complication was the main risk factor, followed by more than 2 preoperative complications, TNM stage≥III, enterostomy and operation methods. The area under the ROC curve of the logistic regression model was 0.773 and that of the decision tree model 0.790. There was no significant difference in the area under the ROC curve between the two models（Z=0.414,P>0.05）. Conclusion Postoperative complications,TNM stage≥III and more than 2 preoperative complications are important influencing factors of unplanned readmission in postoperative patients with colorectal cancer. Logistic regression model and decision tree model have high consistency in the analysis of risk factors. Clinical nurses should take targeted prevention and nursing interventions to reduce the rate of unplanned readmission.

Key words: logistic regression, decision tree, colorectal cancer, unplanned readmission

中图分类号:

R473.6

陈静文, 徐林霞, 吴秀丽, 李显蓉. 基于Logistic回归与决策树模型的结直肠癌术后患者非计划性再入院影响因素分析[J]. 护理学报, 2022, 29(2): 1-6.

CHEN Jing-wen, XU Lin-xia, WU Xiu-li, LI Xian-rong. Risk Factors of Unplanned Readmission in Postoperative Patients with Colorectal Cancer: An Analysis Based on Logistic Regression and Decision Tree[J]. Journal of Nursing, 2022, 29(2): 1-6.

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