基于贝叶斯网络病原学阳性肺结核患者治疗转归的影响因素  

Influencing factors of treatment outcomes of etiologically positive pulmonary tuberculosis patients based on Bayesian network

作　　者：张买 杨敬源[1] 余琴 余妙 李进岚[3] 刘勇 ZHANG Mai;YANG Jingyuan;YU Qin;YU Miao;LI Jinlan;LIU Yong(School of Public Health,the Key Laboratory of Environmental Pollution Monitoring and Disease Control,Ministry of Education,Guizhou Medical University,Guiyang,Guizhou 561113,China;Bijie Center for Disease Control and Prevention,Bijie,Guizhou 551700,China;Institute of Tuberculosis Control,Guizhou Center for Disease Control and Prevention,Guiyang,Guizhou 550004,China)

机构地区：[1]贵州医科大学公共卫生与健康学院,环境污染与疾病监控教育部重点实验室,贵州贵阳561113 [2]毕节市疾病预防控制中心,贵州毕节551700 [3]贵州省疾病预防控制中心结防所,贵州贵阳550004

出　　处：《中国热带医学》2025年第2期184-191,共8页China Tropical Medicine

基　　金：贵州省发改委省级基本建设前期工作项目(No.2020-181-131)。

摘　　要：目的 探究毕节市病原学阳性肺结核患者治疗转归的危险因素及影响程度,为肺结核疫情的精准防治工作提供参考依据。方法 从结核病监测报告信息管理系统中导出毕节市2017—2022年病原学阳性肺结核患者登记治疗管理病案,采用χ^(2)检验和二元logistic回归筛选有统计学意义的变量,通过构建贝叶斯网络模型揭示各因素间的相互依存关系及条件概率。结果 2017—2022年毕节市共登记病原阳性肺结核21 662例,病原学阳性率为48.60%,成功治疗率为89.52%,均呈上升趋势(χ^(2)趋势=2 618.15,P<0.001;χ^(2)趋势=102.84,P<0.001)。经多因素分析显示,性别、年龄、民族、职业、患者来源、HIV检测结果、流动人口、治疗分类是成功治疗率的影响因素(P<0.05)。贝叶斯网络模型显示,年龄、治疗分类是影响治疗结局的主要危险因素,性别、职业、患者来源是间接因素。条件概率显示,<20岁、初治的患者成功治疗率最高(96.75%),产生不良结局的概率为3.25%;≥80岁、复治的患者成功治疗率最低(58.70%),产生不良结局的概率为41.30%。进行因果效应推测,当预防60岁及以上的老年人不患肺结核,且其他患者均为初治患者时,成功治疗率从89.50%上升到93.10%,上升了3.60%;减少近50.00%的农民不患肺结核,且其他患者的来源为主动发现(健康体检和主动筛查),成功治疗率从89.50%上升到91.70%,条件概率变化值为2.20%。结论 应加强对毕节地区男性、高龄、农民、复治、HIV阳性肺结核患者的诊疗管理,同时,采用贝叶网络的因果关联效应推理对于精准化防控和治疗疾病有着重要意义。Objective Exploring the risk factors and degree of influence on treatment regression of patients with etiologically positive pulmonary tuberculosis in Bijie city,so as to provide reference for the precise prevention and treatment of pulmonary tuberculosis epidemic.Methods The medical records of registration,treatment and management of pulmonary tuberculosis patients in Bijie City with positive etiology from 2017 to 2022 were derived from the Tuberculosis Monitoring Report Information Management System.Statistically significant variables were screened using binary logistic regression.Revealing interdependencies between factors and conditional probabilities by constructing Bayesian network models.Results A total of 21662 cases of etiologically positive pulmonary tuberculosis were registered in Bijie City from 2017 to 2022,with etiologically positive rate of 48.60%and a successful treatment rate of 89.52%,both of which were on the rise overall(χ^(2)trend=2618.15,P<0.001;χ^(2)trend=102.84,P<0.001).A multifactorial analysis showed that gender,age,ethnicity,occupation,patient origin,HIV test results,migrating population,and treatment classification were influencing factor for the successful treatment rate(P<0.05).The Bayesian network model showed that age and treatment classification were the direct factors affecting the treatment outcome,while gender,occupation and patient origin were the indirect factors.Conditional probability showed that patients<20 years of age and initial treatment had the highest rate of successful treatment(96.75%),with a 3.25%probability of having an adverse outcome;Patients≥80 years of age who were retreated had the lowest rate of successful treatment(58.70%),with a 41.30%probability of having an adverse outcome.Conducting causal effect speculation,when preventing tuberculosis in older persons aged 60 years and over,and the other patients are newly treated patients,the successful treatment rate increased from 89.50%to 93.10%,with an increase of 3.60%;Nearly 50.00%fewer farmers are without

关 键 词：肺结核 病原学阳性 贝叶斯网络 成功治疗率 影响因素 

分 类 号：R521[医药卫生—内科学]