{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T11:07:21Z","timestamp":1740136041277,"version":"3.37.3"},"reference-count":49,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2022,8,25]],"date-time":"2022-08-25T00:00:00Z","timestamp":1661385600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["NIH T15 LM007450","NIH K01 HL157755-01","NIH U01 HG01166-01S1","NIH R01 GM139891-01"],"award-info":[{"award-number":["NIH T15 LM007450","NIH K01 HL157755-01","NIH U01 HG01166-01S1","NIH R01 GM139891-01"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100001465","name":"American Thoracic Society","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100001465","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100005834","name":"Francis Family Foundation","doi-asserted-by":"publisher","award":["UL1 TR002243"],"award-info":[{"award-number":["UL1 TR002243"]}],"id":[{"id":"10.13039\/100005834","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,1,18]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>COVID-19 survivors are at risk for long-term health effects, but assessing the sequelae of COVID-19 at large scales is challenging. High-throughput methods to efficiently identify new medical problems arising after acute medical events using the electronic health record (EHR) could improve surveillance for long-term consequences of acute medical problems like COVID-19.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Materials and Methods<\/jats:title>\n                  <jats:p>We augmented an existing high-throughput phenotyping method (PheWAS) to identify new diagnoses occurring after an acute temporal event in the EHR. We then used the temporal-informed phenotypes to assess development of new medical problems among COVID-19 survivors enrolled in an EHR cohort of adults tested for COVID-19 at Vanderbilt University Medical Center.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>The study cohort included 186\u200a105 adults tested for COVID-19 from March 5, 2020 to November 1, 2021; of which 30\u200a088 (16.2%) tested positive. Median follow-up after testing was 412\u2009days (IQR 274\u2013528). Our temporal-informed phenotyping was able to distinguish phenotype chapters based on chronicity of their constituent diagnoses. PheWAS with temporal-informed phenotypes identified increased risk for 43 diagnoses among COVID-19 survivors during outpatient follow-up, including multiple new respiratory, cardiovascular, neurological, and pregnancy-related conditions. Findings were robust to sensitivity analyses, and several phenotypic associations were supported by changes in outpatient vital signs or laboratory tests from the pretesting to postrecovery period.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>Temporal-informed PheWAS identified new diagnoses affecting multiple organ systems among COVID-19 survivors. These findings can inform future efforts to enable longitudinal health surveillance for survivors of COVID-19 and other acute medical conditions using the EHR.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/jamia\/ocac159","type":"journal-article","created":{"date-parts":[[2022,8,25]],"date-time":"2022-08-25T13:20:29Z","timestamp":1661433629000},"page":"233-244","source":"Crossref","is-referenced-by-count":4,"title":["Scanning the medical phenome to identify new diagnoses after recovery from COVID-19 in a US cohort"],"prefix":"10.1093","volume":"30","author":[{"given":"Vern Eric","family":"Kerchberger","sequence":"first","affiliation":[{"name":"Department of Biomedical Informatics, Vanderbilt University Medical Center , Nashville, Tennessee, USA"},{"name":"Department of Medicine, Vanderbilt University Medical Center , Nashville, Tennessee, USA"}]},{"given":"Josh F","family":"Peterson","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Vanderbilt University Medical Center , Nashville, Tennessee, USA"},{"name":"Department of Medicine, Vanderbilt University Medical Center , Nashville, Tennessee, USA"}]},{"given":"Wei-Qi","family":"Wei","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Vanderbilt University Medical Center , Nashville, Tennessee, USA"}]}],"member":"286","published-online":{"date-parts":[[2022,8,25]]},"reference":[{"issue":"5","key":"2023011811045903500_ocac159-B1","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1016\/S1473-3099(20)30120-1","article-title":"An interactive web-based dashboard to track COVID-19 in real time","volume":"20","author":"Dong","year":"2020","journal-title":"Lancet Infect Dis"},{"issue":"4","key":"2023011811045903500_ocac159-B2","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1038\/s41591-021-01283-z","article-title":"Post-acute COVID-19 syndrome","volume":"27","author":"Nalbandian","year":"2021","journal-title":"Nat 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