{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,5]],"date-time":"2026-09-05T05:38:10Z","timestamp":1788586690323,"version":"build-2803163510"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,5,28]],"date-time":"2025-05-28T00:00:00Z","timestamp":1748390400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,5,28]],"date-time":"2025-05-28T00:00:00Z","timestamp":1748390400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100000051","name":"National Human Genome Research Institute","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100000051","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Electronic health records (EHRs) contain rich temporal data about respiratory viral infections, but methods to identify these infections from EHR data vary widely and lack robust validation. We developed computable phenotypes by integrating virus-specific International Classification of Diseases (ICD) billing codes, prescriptions, and laboratory results within 90-day episodes. Analysis of 265,222 participants with EHR data from the\n                    <jats:italic>All of Us<\/jats:italic>\n                    Research Program yielded national cohorts of varied size: large cohorts for SARS-CoV-2 (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u200928,729) and influenza (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u200919,784); medium cohorts for rhinovirus, human coronavirus, and respiratory syncytial virus (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u20091,161-1,620); and smaller cohorts for the other viruses (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u2009238\u2013486). Using laboratory results as a reference standard, phenotypes using virus-specific ICD codes and medications had variable sensitivity (8\u201367%) but high positive predictive value (PPV, 90\u201397%) for most viruses, while influenza virus and SARS-CoV-2 phenotypes had lower PPV (69\u201370%) that improved with the inclusion of additional ICD codes. Identified infections exhibited expected seasonal patterns matching CDC data. This integrated approach identified infections more effectively than individual components alone and demonstrated utility for severe infections in hospital settings. This method enables large-scale studies of host genetics, health disparities, and clinical outcomes across episodic diseases, with flexibility to optimize sensitivity or PPV depending on the specific research question.\n                  <\/jats:p>","DOI":"10.1038\/s41598-025-02183-9","type":"journal-article","created":{"date-parts":[[2025,5,28]],"date-time":"2025-05-28T07:48:56Z","timestamp":1748418536000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Computable phenotypes to identify respiratory viral infections in the All of Us research program"],"prefix":"10.1038","volume":"15","author":[{"given":"Bennett J.","family":"Waxse","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fausto Andres","family":"Bustos Carrillo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tam C.","family":"Tran","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huan","family":"Mo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emily E.","family":"Ricotta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joshua C.","family":"Denny","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,5,28]]},"reference":[{"key":"2183_CR1","doi-asserted-by":"publisher","first-page":"563","DOI":"10.1093\/infdis\/jiy662","volume":"222","author":"T Shi","year":"2019","unstructured":"Shi, T. et al. The etiological role of common respiratory viruses in acute respiratory infections in older adults: A systematic review and Meta-analysis. J. Infect. Dis. 222, 563\u2013569 (2019).","journal-title":"J. Infect. Dis."},{"key":"2183_CR2","doi-asserted-by":"publisher","first-page":"e13237","DOI":"10.1111\/irv.13237","volume":"18","author":"H Boon","year":"2024","unstructured":"Boon, H., Meinders, A., van Hannen, E. J., Tersmette, M. & Schaftenaar, E. Comparative analysis of mortality in patients admitted with an infection with influenza A\/B virus, respiratory syncytial virus, rhinovirus, metapneumovirus or SARS-CoV\u20102. Influ Other Respir Viruses. 18, e13237 (2024).","journal-title":"Influ Other Respir Viruses"},{"key":"2183_CR3","doi-asserted-by":"publisher","first-page":"E439","DOI":"10.1503\/cmaj.201748","volume":"193","author":"N Lee","year":"2021","unstructured":"Lee, N. et al. Burden of noninfluenza respiratory viral infections in adults admitted to hospital: analysis of a multiyear Canadian surveillance cohort from 2 centres. CMAJ 193, E439\u2013E446 (2021).","journal-title":"CMAJ"},{"key":"2183_CR4","doi-asserted-by":"publisher","first-page":"2002688","DOI":"10.1183\/13993003.02688-2020","volume":"57","author":"K Korsten","year":"2021","unstructured":"Korsten, K. et al. Burden of respiratory syncytial virus infection in community-dwelling older adults in Europe (RESCEU): an international prospective cohort study. Eur. Respir J. 57, 2002688 (2021).","journal-title":"Eur. Respir J."},{"key":"2183_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1136\/thoraxjnl-2021-216949","volume":"77","author":"P Hedberg","year":"2022","unstructured":"Hedberg, P. et al. Clinical phenotypes and outcomes of SARS-CoV-2, influenza, RSV and seven other respiratory viruses: a retrospective study using complete hospital data. 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