Abstract
马晓格,张立杰,高汉青,包城,吴越,吴思慧,刘梦晗,刘宇红,李亮.基于多因素logistic回归模型和决策树模型的肺结核患者就诊延迟及确诊延迟影响因素分析[J].Chinese journal of Epidemiology,2024,45(5):721-729
基于多因素logistic回归模型和决策树模型的肺结核患者就诊延迟及确诊延迟影响因素分析
Analysis on influencing factors of medical care seeking delay and diagnosis delay of pulmonary tuberculosis patients based on logistic regression model and decision tree model
Received:February 24, 2024  
DOI:10.3760/cma.j.cn112338-20240224-00080
KeyWord: 结核,肺  就诊延迟  确诊延迟  多因素logistic回归模型  决策树模型
English Key Word: Tuberculosis, pulmonary  Medical care seeking delay  Diagnosis delay  Multivariate logistic regression model  Decision tree model
FundProject:北京结核病综合防控关键技术研究(D181100000418005);北京市卫生健康委员会高层次公共卫生技术人才项目(学科带头人-01-11)
Author NameAffiliationE-mail
Ma Xiaoge Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China  
Zhang Lijie Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Clinical Center for Tuberculosis, Chinese Center for Disease Control and Prevention, Beijing 101149, China  
Gao Hanqing Institute for Tuberculosis Prevention and Control, Tongzhou District Center for Disease Prevention and Control, Beijing 101149, China  
Bao Cheng Changping Institute for Tuberculosis Prevention and Treatment, Beijing 102200, China  
Wu Yue Institute for Tuberculosis Prevention and Control, Tongzhou District Center for Disease Prevention and Control, Beijing 101149, China  
Wu Sihui Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China  
Liu Menghan Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China  
Liu Yuhong Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Clinical Center for Tuberculosis, Chinese Center for Disease Control and Prevention, Beijing 101149, China  
Li Liang Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Clinical Center for Tuberculosis, Chinese Center for Disease Control and Prevention, Beijing 101149, China liliang69@vip.sina.com 
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Abstract:
      目的 了解北京市通州区及昌平区肺结核患者就诊延迟及确诊延迟情况并分析其影响因素,为早期发现及科学管理肺结核患者提供有效建议。方法 采用回顾性流行病学调查方法,利用全国结核病管理信息系统收集北京市通州区及昌平区于2021年1月1日至12月31日登记的肺结核患者个案资料,采用电话访谈对部分信息进行补充,采用多因素logistic回归模型及决策树模型分析肺结核患者就诊延迟及确诊延迟的影响因素。结果 2021年北京市通州区及昌平区肺结核患者就诊延迟时间MQ1Q3)为11(5,26)d,就诊延迟率为41.71%。多因素分析结果显示,健康体检(OR=0.033,95%CI:0.008~0.147)、就诊前咳嗽咳痰<2周,且有任一结核病症状(OR=0.378,95%CI:0.215~0.665)、就诊前有其他症状(OR=2.791,95%CI:1.710~4.555)及就诊期间无需上班或上学(OR=2.990,95%CI:1.419~6.298)为就诊延迟的影响因素;肺结核患者确诊延迟时间MQ1Q3)为8(0,18)d,确诊延迟率为35.20%。多因素分析结果显示,确诊单位为结核病专科医院(OR=0.426,95%CI:0.236~0.767)和结核病防治所(OR=1.843,95%CI:1.061~3.202)以及患者来源为追踪(OR=2.632,95%CI:1.062~6.521)为确诊延迟的影响因素。多因素logistic回归模型与决策树模型的整体效能相当,决策树模型的灵敏度高于多因素logistic回归模型、特异度低于多因素logistic回归模型。结论 2021年北京市通州区及昌平区肺结核患者就诊延迟及确诊延迟处于较低水平,但仍需加强宣传教育并积极开展主动筛查,提高市民对结核病的防治意识,同时进一步提升医疗服务水平和改善就医可及性,减少患者就医及诊断延迟现象。
English Abstract:
      Objective To investigate the status of medical care seeking delay and diagnosis delay of pulmonary tuberculosis (PTB) patients in Tongzhou District and Changping District of Beijing, analyze the related factors and put forward suggestions for early detection and scientific management of PTB patients. Methods A retrospective epidemiological survey was conducted to collect the incidence data of PTB registered in Tongzhou and Changping from January 1 to December 31, 2021 by using the Chinese Tuberculosis Information Management System, and telephone interview were used for information supplement. Multivariate logistic regression model and decision tree model were used to analyze the influencing factors of medical care seeking delay and diagnosis delay of PTB patients. Results In 2021, the medical care seeking delay time M(Q1Q3) in the PTB patients in Tongzhou and Changping was 11 (5, 26) days, with a delay rate of 41.71%. Results from multivariate logistic regression model analysis revealed that factors influencing the medical care seeking delay included regular health check-up (OR=0.033, 95%CI: 0.008-0.147), coughing for less than 2 weeks or showing any symptom of PTB before medical care seeking (OR=0.378, 95%CI: 0.215-0.665), showing other symptoms before medical care seeking(OR=2.791, 95%CI: 1.710-4.555), no work or school in medical care seeking (OR=2.990, 95%CI: 1.419-6.298). The diagnosis delay time M(Q1Q3) in the PTB patients was 8 (0, 18) days, with a delay rate of 35.20%. Multivariate logistic regression model analysis revealed that the factors influencing the diagnosis delay of PTB included being diagnosed at a specialized tuberculosis hospital (OR=0.426, 95%CI: 0.236-0.767) or a tuberculosis prevention and control institution (OR=1.843, 95%CI: 1.061-3.202) and being traced as a source of infection (OR=2.632, 95%CI: 1.062-6.521). The overall performance of the multivariate logistic regression model was comparable to that of the decision tree model, with the decision tree model exhibiting higher sensitivity but lower specificity. Conclusions The medical care seeking delay rate and diagnosis delay rate of tuberculosis in Tongzhou and Changping were at low levels in 2021. However, it is still necessary to strengthen the health education and active screening, improve the public awareness of PTB prevention and control, and further improve the level of medical services and medical access to reduce the medical care seeking delay and diagnosis delay of PTB patients.
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