Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, NC, USA.
Department of Population Health Sciences, Duke University, Durham, NC, USA.
BMC Med Res Methodol. 2023 Apr 4;23(1):81. doi: 10.1186/s12874-023-01882-z.
Understanding how SARS-CoV-2 infection impacts long-term patient outcomes requires identification of comparable persons with and without infection. We report the design and implementation of a matching strategy employed by the Department of Veterans Affairs' (VA) COVID-19 Observational Research Collaboratory (CORC) to develop comparable cohorts of SARS-CoV-2 infected and uninfected persons for the purpose of inferring potential causative long-term adverse effects of SARS-CoV-2 infection in the Veteran population.
In a retrospective cohort study, we identified VA health care system patients who were and were not infected with SARS-CoV-2 on a rolling monthly basis. We generated matched cohorts within each month utilizing a combination of exact and time-varying propensity score matching based on electronic health record (EHR)-derived covariates that can be confounders or risk factors across a range of outcomes.
From an initial pool of 126,689,864 person-months of observation, we generated final matched cohorts of 208,536 Veterans infected between March 2020-April 2021 and 3,014,091 uninfected Veterans. Matched cohorts were well-balanced on all 39 covariates used in matching after excluding patients for: no VA health care utilization; implausible age, weight, or height; living outside of the 50 states or Washington, D.C.; prior SARS-CoV-2 diagnosis per Medicare claims; or lack of a suitable match. Most Veterans in the matched cohort were male (88.3%), non-Hispanic (87.1%), white (67.2%), and living in urban areas (71.5%), with a mean age of 60.6, BMI of 31.3, Gagne comorbidity score of 1.4 and a mean of 2.3 CDC high-risk conditions. The most common diagnoses were hypertension (61.4%), diabetes (34.3%), major depression (32.2%), coronary heart disease (28.5%), PTSD (25.5%), anxiety (22.5%), and chronic kidney disease (22.5%).
This successful creation of matched SARS-CoV-2 infected and uninfected patient cohorts from the largest integrated health system in the United States will support cohort studies of outcomes derived from EHRs and sample selection for qualitative interviews and patient surveys. These studies will increase our understanding of the long-term outcomes of Veterans who were infected with SARS-CoV-2.
了解 SARS-CoV-2 感染如何影响患者的长期预后，需要确定感染和未感染 SARS-CoV-2 的可比人群。我们报告了美国退伍军人事务部 (VA) COVID-19 观察性研究协作组 (CORC) 采用的匹配策略的设计和实施情况，该策略旨在为退伍军人人群中 SARS-CoV-2 感染的潜在因果性长期不良后果推断开发可比的 SARS-CoV-2 感染和未感染人群队列。
在一项回顾性队列研究中，我们逐月确定 VA 医疗保健系统中 SARS-CoV-2 感染和未感染的患者。我们使用基于电子健康记录 (EHR) 衍生的协变量的精确和时变倾向评分匹配相结合，生成了每个月内的匹配队列，这些协变量可以是一系列结果的混杂因素或风险因素。
从最初的 126,689,864 人月观察期内，我们生成了 208,536 名 2020 年 3 月至 2021 年 4 月期间感染 SARS-CoV-2 的退伍军人和 3,014,091 名未感染退伍军人的最终匹配队列。在排除没有 VA 医疗保健利用、年龄、体重或身高不合理、居住在 50 个州或华盛顿特区以外、根据医疗保险索赔记录有既往 SARS-CoV-2 诊断、或缺乏合适匹配的患者后，匹配队列在使用的 39 个协变量上均达到了很好的平衡。匹配队列中的大多数退伍军人是男性 (88.3%)、非西班牙裔 (87.1%)、白人 (67.2%)、居住在城市地区 (71.5%)，平均年龄为 60.6 岁，BMI 为 31.3，Gagne 合并症评分为 1.4，平均有 2.3 项 CDC 高危条件。最常见的诊断是高血压 (61.4%)、糖尿病 (34.3%)、重度抑郁症 (32.2%)、冠心病 (28.5%)、创伤后应激障碍 (25.5%)、焦虑症 (22.5%)和慢性肾脏病 (22.5%)。
从美国最大的综合医疗系统成功创建了可比的 SARS-CoV-2 感染和未感染患者队列，这将支持从 EHR 中提取结局的队列研究，并为定性访谈和患者调查选择样本。这些研究将增加我们对感染 SARS-CoV-2 的退伍军人的长期预后的理解。
