Understanding Post-Acute Sequelae of SARS-CoV-2 Infection through Data-Driven Analysis with the Longitudinal Electronic Health Records: Findings from the RECOVER Initiative
Understanding Post-Acute Sequelae of SARS-CoV-2 Infection through Data-Driven Analysis with the Longitudinal Electronic Health Records: Findings from the RECOVER Initiative
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通过纵向电子健康记录的数据驱动分析了解 SARS-CoV-2 感染的急性后遗症：RECOVER Initiative 的发现
DOI：
10.1101/2022.05.21.22275420
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发表时间：
2022
期刊：
影响因子：
4
通讯作者：
R. Kaushal
中科院分区：
文献类型：
--
作者：
C. Zang;Y. Zhang;J. Xu;J. Bian;D. Morozyuk;E. Schenck;D. Khullar;A. Nordvig;E. Shenkman;R. L. Rothman;J. Block;K. Lyman;M. Weiner;T. Carton;F. Wang;R. Kaushal
最近的研究利用电子健康记录 (EHR) 等真实患者数据调查了 SARS-CoV-2 感染 (PASC) 的急性后遗症。先前的研究通常是针对样本量较小的患者队列1或特定的患者群体2、3进行的，这限制了普遍性。本研究旨在使用来自两个大型国家以患者为中心的临床研究网络 (PCORnet) INSIGHT 和 OneFlorida+ 的 EHR 数据仓库来描述 PASC 的特征，其中分别包括纽约市 (NYC) 的 1100 万患者和佛罗里达州的 1680 万患者。通过使用高维逆倾向评分调整的高通量因果推理流程，我们确定了一系列广泛的诊断和药物治疗，与未感染的患者相比，实验室确诊的 SARS-CoV-2 感染后 30-180 天的发病率明显更高。我们发现纽约市的 PASC 诊断数量比佛罗里达州多，PASC 的风险也较高，这凸显了不同人群中 PASC 的异质性。
Recent studies have investigated post-acute sequelae of SARS-CoV-2 infection (PASC) using real-world patient data such as electronic health records (EHR). Prior studies have typically been conducted on patient cohorts with small sample sizes1 or specific patient populations2,3 limiting generalizability. This study aims to characterize PASC using the EHR data warehouses from two large national patient-centered clinical research networks (PCORnet), INSIGHT and OneFlorida+, which include 11 million patients in New York City (NYC) and 16.8 million patients in Florida respectively. With a high-throughput causal inference pipeline using high-dimensional inverse propensity score adjustment, we identified a broad list of diagnoses and medications with significantly higher incidence 30-180 days after the laboratory-confirmed SARS-CoV-2 infection compared to non-infected patients. We found more PASC diagnoses and a higher risk of PASC in NYC than in Florida, which highlights the heterogeneity of PASC in different populations.
影响因子：
5
作者：
Hernan, Miguel A.;Robins, James M.
通讯作者：
Robins, James M.