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HIV患者抗逆转录病毒治疗随访失访的预测因素(2018 - 2022年):一项回顾性队列研究

Predictive Factors of ART Follow-Up Loss in HIV Patients (2018-2022): A Retrospective Cohort Study.

作者信息

Li Mengjie, Chen Hang, Xiao Ticheng, Ma Ji, Ding Mingzhe, Huang Fuli, Chen Yanhua, Chen Run, Li Ailing, Fan Song

机构信息

School of Public Health, Southwest Medical University, Luzhou City, 646000, Sichuan Province, China.

Luzhou Center for Disease Control and Prevention, Luzhou, China.

出版信息

AIDS Behav. 2025 Apr;29(4):1205-1215. doi: 10.1007/s10461-024-04595-6. Epub 2024 Dec 30.

Abstract

Loss to follow-up (LTFU) in antiretroviral therapy (ART) poses significant challenges in the management of HIV/AIDS. This study aims to identify socio-demographic and clinical factors influencing LTFU among patients undergoing ART in Luzhou, China, and to develop a predictive model for LTFU using Cox risk regression analysis. In this retrospective cohort study, data from 8,770 patients diagnosed with HIV infection between January 1, 2018 and December 31, 2022 who were enrolled in the national free ART program were analyzed. The primary outcome was the first occurrence of LTFU. Cox proportional risk regression analyses were conducted to identify predictors of LTFU. The study population had a median age of 64.25 years, and 73.2% were male. The overall LTFU rate was 4.14 per 100 person-years. Factors associated with a decreased likelihood of LTFU included female gender, homosexual transmission, absence of HIV-related diseases, negative HBV surface antigen, higher final CD4 count, and an increase in CD4 count from baseline. In contrast, older age, longer time from diagnosis to ART initiation, higher baseline viral load, missed medication doses, and the development of medication side-effects were associated with an increased risk of LTFU. Our prediction model identifying the risk of loss to follow-up demonstrated good predictive performance with a C-index of 0.721. The study highlights the importance of considering a range of socio-demographic and clinical factors in managing LTFU among people living with HIV (PLHIV) on ART. Our prediction model can be a valuable tool for healthcare providers to identify patients at high risk of LTFU, facilitating targeted interventions to improve treatment adherence and outcomes.

摘要

抗逆转录病毒疗法(ART)中的失访(LTFU)给艾滋病毒/艾滋病的管理带来了重大挑战。本研究旨在确定影响中国泸州接受ART治疗患者失访的社会人口学和临床因素,并使用Cox风险回归分析建立失访预测模型。在这项回顾性队列研究中,分析了2018年1月1日至2022年12月31日期间被诊断为艾滋病毒感染并参加国家免费ART项目的8770名患者的数据。主要结局是首次出现失访。进行Cox比例风险回归分析以确定失访的预测因素。研究人群的中位年龄为64.25岁,73.2%为男性。总体失访率为每100人年4.14例。与失访可能性降低相关的因素包括女性性别、同性传播、无艾滋病毒相关疾病、乙肝表面抗原阴性、最终CD4细胞计数较高以及CD4细胞计数较基线增加。相比之下,年龄较大、从诊断到开始ART的时间较长、基线病毒载量较高、漏服药物剂量以及出现药物副作用与失访风险增加相关。我们识别失访风险的预测模型显示出良好的预测性能,C指数为0.721。该研究强调了在管理接受ART治疗的艾滋病毒感染者(PLHIV)失访时考虑一系列社会人口学和临床因素的重要性。我们的预测模型可以成为医疗保健提供者识别失访高风险患者的宝贵工具,有助于采取有针对性的干预措施以改善治疗依从性和治疗结果。

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