预测 HIV 感染晚期患者的 COVID-19 结局:基于模型的方法

Anna E. Tsygankova, V. Chulanov, A. Gerasimov, E. Volchkova, Anton A. Privalenko, Viktoriya A. Bakhtina, Vladimir A. Habudaev, D. Baimukhambetova
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摘要

摘要 背景:如今,临床医生及其决策广泛依赖于特定的治疗算法。这些算法包括预后模型,用于识别需要入院治疗和临床监测的高危患者。考虑到晚期艾滋病患者出现不良预后的风险较高,需要采用专门的方法,我们的论文提出了一种预测 COVID-19 预后的模型[2]。目的:目的是建立一个预后模型,将晚期艾滋病患者 COVID-19 不利结局的预测因素结合起来。材料和方法:研究基于莫斯科传染病医院自 2020 年 3 月 1 日至 2022 年 12 月 31 日期间因确诊 COVID-19 而住院治疗的 500 名晚期艾滋病患者的病历。结果:对这500名患者中的每一位进行了167项COVID-19不良预后预测指标的评估,列出了50项指标,这些指标在COVID-19晚期HIV病患者的不同亚组中有显著差异,取决于预后好坏。氧疗是与 COVID-19 晚期艾滋病患者不良预后密切相关的最重要因素。随后,为了通过增加更多因素来提高模型的预测准确性,对预测因子进行了逐步筛选。最后得出的模型包括 7 个因素,如氧疗需求、CD4+ 细胞计数低于 50 cells/μL、以肺损伤为特征的明显 CMV 感染、乳酸脱氢酶、尿素和纤维蛋白原水平升高以及不明脑炎。ROC 曲线下的面积为 90.9%,从而证实了该模型的预测准确性和整体实用意义。结论所建议的预后模型可用于评估艾滋病病毒和 COVID-19 合并感染晚期入院患者的潜在预后,并根据所获得的结果制定适当的治疗方案。关键词HIV、COVID-19、SARS-CoV-2
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting COVID-19 Outcomes in Patients at Advanced Stages of HIV Infection: A Model-based Approach
Abstract Background: Today clinicians and their decisions extensively rely on specific treatment algorithms. These algorithms include prognostic models to identify high-risk patients requiring hospital admission and clinical monitoring. Our paper suggests a prognostic model to forecast COVID-19 outcomes in patients with advanced HIV disease, considering the high risk for unfavorable outcome and the need of a specialized approach [2]. Objective: The objective is to develop a prognostic model combining predictors of unfavorable COVID-19 outcome in patients with advanced HIV disease. Materials and methods: The study is based on 500 medical records of patients with advanced HIV disease admitted for confirmed COVID-19 from March 1, 2020 through December 31, 2022 for inpatient treatment at the Infectious Diseases Hospital in Moscow. Results: Each of the 500 patients was evaluated for 167 predictive markers for unfavorable COVID-19 outcome, outlining 50 indicators that varied significantly across the subgroups of advanced HIV disease patients with COVID-19 depending on favorable or poor outcome. Oxygen therapy was the most significant factor showing strong correlation with poor outcome in advanced HIV patients with COVID-19. Subsequently, predictors were selected stepwise in order to enhance predictive accuracy of the resulting model by adding more factors. The resulting model included 7 factors, e.g. oxygen therapy requirements, CD4+ count under 50 cells/μL, manifest CMV infection characterized by lung damage, elevated lactate dehydrogenase, urea, and fibrinogen levels, as well as unspecified encephalitis. using available data in calculations, a prognostic scenario and a ROC curve were built to assess practical significance of the obtained prognostic model. The area under the ROC curve was 90.9%, thus confirming prediction accuracy and overall practical significance of the model. Conclusions: The suggested prognostic model enables to assess potential outcomes in patients with HIV and COVID-19 co-infection admitted to hospital at advanced stages of disease, as well as to plan adequate therapies based on the obtained results. Keywords: HIV, COVID-19, SARS-CoV-2
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