{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,1,17]],"date-time":"2026-01-17T11:38:45Z","timestamp":1768649925193,"version":"3.49.0"},"posted":{"date-parts":[[2024,2,6]]},"group-title":"Epidemiology","reference-count":42,"publisher":"openRxiv","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2024,2,6]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                <jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>Long COVID, also known as post-acute sequelae of COVID-19 (PASC), is a poorly understood condition with symptoms across a range of biological domains that often have debilitating consequences. Some have recently suggested that lingering SARS-CoV-2 virus in the gut may impede serotonin production and that low serotonin may drive many Long COVID symptoms across a range of biological systems. Therefore, selective serotonin reuptake inhibitors (SSRIs), which increase synaptic serotonin availability, may prevent or treat Long COVID. SSRIs are commonly prescribed for depression, therefore restricting a study sample to only include patients with depression can reduce the concern of confounding by indication.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>In an observational sample of electronic health records from patients in the National COVID Cohort Collaborative (N3C) with a COVID-19 diagnosis between September 1, 2021, and December 1, 2022, and pre-existing major depressive disorder, the leading indication for SSRI use, we evaluated the relationship between SSRI use at the time of COVID-19 infection and subsequent 12-month risk of Long COVID (defined by ICD-10 code U09.9). We defined SSRI use as a prescription for SSRI medication beginning at least 30 days before COVID-19 infection and not ending before COVID-19 infection. To minimize bias, we estimated the causal associations of interest using a nonparametric approach, targeted maximum likelihood estimation, to aggressively adjust for high-dimensional covariates.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>\n                    We analyzed a sample (\n                    <jats:italic>n<\/jats:italic>\n                    = 506,903) of patients with a diagnosis of major depressive disorder before COVID-19 diagnosis, where 124,928 (25%) were using an SSRI. We found that SSRI users had a significantly lower risk of Long COVID compared to nonusers (adjusted causal relative risk 0.90, 95% CI (0.86, 0.94)).\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>These findings suggest that SSRI use during COVID-19 infection may be protective against Long COVID, supporting the hypothesis that serotonin may be a key mechanistic biomarker of Long COVID.<\/jats:p>\n                <\/jats:sec>","DOI":"10.1101\/2024.02.05.24302352","type":"posted-content","created":{"date-parts":[[2024,2,6]],"date-time":"2024-02-06T19:45:12Z","timestamp":1707248712000},"source":"Crossref","is-referenced-by-count":2,"title":["SSRI Use During Acute COVID-19 Infection Associated with Lower Risk of Long COVID Among Patients with Depression"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6419-0008","authenticated-orcid":false,"given":"Zachary","family":"Butzin-Dozier","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunwen","family":"Ji","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sarang","family":"Deshpande","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eric","family":"Hurwitz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeremy","family":"Coyle","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junming (Seraphina)","family":"Shi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1050-6721","authenticated-orcid":false,"given":"Andrew","family":"Mertens","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mark J.","family":"van der Laan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"suffix":"Jr.","given":"John M.","family":"Colford","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rena C.","family":"Patel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3769-0127","authenticated-orcid":false,"given":"Alan E.","family":"Hubbard","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"name":"the National COVID Cohort Collaborative (N3C) Consortium","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"54368","reference":[{"key":"2024020803401073000_2024.02.05.24302352v1.1","doi-asserted-by":"publisher","DOI":"10.1093\/cid\/ciac961"},{"issue":"3","key":"2024020803401073000_2024.02.05.24302352v1.2","doi-asserted-by":"crossref","first-page":"869","DOI":"10.1016\/j.dsx.2021.04.007","article-title":"Long COVID: an overview","volume":"15","year":"2021","journal-title":"Diabetes & Metabolic Syndrome: Clinical Research & Reviews"},{"key":"2024020803401073000_2024.02.05.24302352v1.3","doi-asserted-by":"publisher","DOI":"10.1038\/s41579-022-00846-2"},{"key":"2024020803401073000_2024.02.05.24302352v1.4","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2023.09.013"},{"key":"2024020803401073000_2024.02.05.24302352v1.5","unstructured":"Belluck P. 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