ArticlemedRxiv : the preprint server for health sciences2023
Assessing the Effect of Selective Serotonin Reuptake Inhibitors in the Prevention of Post-Acute Sequelae of COVID-19.
Hythem Sidky, David K Sahner, Andrew T Girvin, Nathan Hotaling, Sam G Michael, Ken Gersing
Open access · greenAbstract readPreprint
In one paragraphArticle in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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0citing papers in PubMed
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1 · What the graph read from itWhat it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registryThe trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
3 · Its place in the literatureWho cites it
0 citing papers in PubMed, 14 citations in OpenAlex.
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4 · The recordCorrections and comments
5 · Who and what moneyAuthors and funding
6 authors at 1 institution in 1 country.
Hythem SidkyNational Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD.
David K SahnerNational Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD.
Andrew T GirvinPalantir Technologies, Denver, CO.
Nathan HotalingNational Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD.
Sam G MichaelNational Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD.
Ken GersingNational Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD.
National Institutes of Health · US
Funding
Vanderbilt Institute for Clinical and Translational Research (VICTR) -Identifying correlates of functional immunity in SARS-CoV-2 convalescent plasmaUL1TR002243 · NCATS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Paul A. Harris, Wesley H Self · 2017 to 2026
$130.7MUCLA Clinical Translational Science InstituteUL1TR001881 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ARLEEN F. BROWN, ARASH NAEIM · 2016 to 2026
$118.1MClinical and Translational Science InstituteUL1TR001872 · NCATS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI COLLARD, HAROLD R, JACOBY, VANESSA · 2016 to 2025
$112.1MProject-005UL1TR001445 · NCATS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI BREDELLA, MIRIAM ANTOINETTE, HOCHMAN, JUDITH S · 2015 to 2025
$103.5MYale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9MPhenotypic Diversity in COVID-19UL1TR001878 · NCATS · UNIVERSITY OF PENNSYLVANIA · PI FITZGERALD, GARRET A · 2016 to 2025
$102.4MTransform Dissemination and Implementation Science in CTSA ProgramsUL1TR002319 · NCATS · UNIVERSITY OF WASHINGTON · PI John K. Amory · 2017 to 2026
$100.0MClinical and Translational Science AwardUL1TR001873 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI REILLY, MUREDACH P · 2016 to 2025
$99.0MWU INSTITUTE OF CLINICAL AND TRANSLATIONAL SCIENCESUL1TR002345 · NCATS · WASHINGTON UNIVERSITY · PI William G. Powderly · 2017 to 2026
$97.8MThe Harvard Clinical and Translational Science CenterUL1TR002541 · NCATS · HARVARD MEDICAL SCHOOL · PI NADLER, LEE MARSHALL · 2018 to 2022
$93.0MImplementing a Maternal health and PRegnancy Outcomes Vision for Everyone (IMPROVE)UL1TR002378 · NCATS · EMORY UNIVERSITY · PI Andres J Garcia, Elizabeth O. Ofili · 2017 to 2026
$92.1MUC San Diego Clinical and Translational Research InstituteUL1TR001442 · NCATS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI FIRESTEIN, GARY S, HOGARTH, MICHAEL · 2015 to 2024
$88.3MNCATS NIH HHS U24 TR002306NCATS NIH HHS UL1 TR001409NCATS NIH HHS UL1 TR001412NCATS NIH HHS UL1 TR001414NCATS NIH HHS UL1 TR001420NCATS NIH HHS UL1 TR001422NCATS NIH HHS UL1 TR001425NCATS NIH HHS UL1 TR001427NCATS NIH HHS UL1 TR001430NCATS NIH HHS UL1 TR001433NCATS NIH HHS UL1 TR001436NCATS NIH HHS UL1 TR001439NCATS NIH HHS UL1 TR001442NCATS NIH HHS UL1 TR001445NCATS NIH HHS UL1 TR001449NCATS NIH HHS UL1 TR001450NCATS NIH HHS UL1 TR001453NCATS NIH HHS UL1 TR001855NCATS NIH HHS UL1 TR001860NCATS NIH HHS UL1 TR001863NCATS NIH HHS UL1 TR001866NCATS NIH HHS UL1 TR001872NCATS NIH HHS UL1 TR001873NCATS NIH HHS UL1 TR001876NCATS NIH HHS UL1 TR001878NCATS NIH HHS UL1 TR001881NCATS NIH HHS UL1 TR001998NCATS NIH HHS UL1 TR002001NCATS NIH HHS UL1 TR002003NCATS NIH HHS UL1 TR002014NCATS NIH HHS UL1 TR002240NCATS NIH HHS UL1 TR002243NCATS NIH HHS UL1 TR002319NCATS NIH HHS UL1 TR002345NCATS NIH HHS UL1 TR002366NCATS NIH HHS UL1 TR002369NCATS NIH HHS UL1 TR002373NCATS NIH HHS UL1 TR002377NCATS NIH HHS UL1 TR002378NCATS NIH HHS UL1 TR002384NCATS NIH HHS UL1 TR002389NCATS NIH HHS UL1 TR002489NCATS NIH HHS UL1 TR002494NCATS NIH HHS UL1 TR002529NCATS NIH HHS UL1 TR002535NCATS NIH HHS UL1 TR002537NCATS NIH HHS UL1 TR002538NCATS NIH HHS UL1 TR002541NCATS NIH HHS UL1 TR002544NCATS NIH HHS UL1 TR002550NCATS NIH HHS UL1 TR002553NCATS NIH HHS UL1 TR002556NCATS NIH HHS UL1 TR002645NCATS NIH HHS UL1 TR002649NCATS NIH HHS UL1 TR002733NCATS NIH HHS UL1 TR002736NCATS NIH HHS UL1 TR003015NCATS NIH HHS UL1 TR003017NCATS NIH HHS UL1 TR003096NCATS NIH HHS UL1 TR003098NCATS NIH HHS UL1 TR003107NCATS NIH HHS UL1 TR003142NCATS NIH HHS UL1 TR003167NIGMS NIH HHS U54 GM104938NIGMS NIH HHS U54 GM104940NIGMS NIH HHS U54 GM104941NIGMS NIH HHS U54 GM104942NIGMS NIH HHS U54 GM115371NIGMS NIH HHS U54 GM115428NIGMS NIH HHS U54 GM115458NIGMS NIH HHS U54 GM115516NIGMS NIH HHS U54 GM115677
6 · The paper itselfAbstract
Importance: Post-acute sequelae of COVID-19 (PASC) produce significant morbidity, prompting evaluation of interventions that might lower risk. Selective serotonin reuptake inhibitors (SSRIs) potentially could modulate risk of PASC via their central, hypothesized immunomodulatory, and/or antiplatelet properties and therefore may be postulated to be of benefit in patients with PASC, although clinical trial data are lacking. Objectives: The main objective was to evaluate whether SSRIs with agonist activity at the sigma-1 receptor lower the risk of PASC, since agonism at this receptor may serve as a mechanism by which SSRIs attenuate an inflammatory response. A secondary objective was to determine whether potential benefit could be traced to sigma-1 agonism by evaluating the risk of PASC among recipients of SSRIs that are not S1R agonists. Design: Retrospective study leveraging real-world clinical data within the National COVID Cohort Collaborative (N3C), a large centralized multi-institutional de-identified EHR database. Presumed PASC was defined based on a computable PASC phenotype trained on the U09.9 ICD-10 diagnosis code to more comprehensively identify patients likely to have the condition, since the ICD code has come into wide-spread use only recently. Setting: Population-based study at US medical centers. Participants: Adults (≥ 18 years of age) with a confirmed COVID-19 diagnosis date between October 1, 2021 and April 7, 2022 and at least one follow up visit 45 days post-diagnosis. Of the 17 933 patients identified, 2021 were exposed at baseline to a S1R agonist SSRI, 1328 to a non-S1R agonist SSRI, and 14 584 to neither. Exposures: Exposure at baseline (at or prior to COVID-19 diagnosis) to an SSRI with documented or presumed agonist activity at the S1R (fluvoxamine, fluoxetine, escitalopram, or citalopram), an SSRI without agonist activity at S1R (sertraline, an antagonist, or paroxetine, which does not appreciably bind to the S1R), or none of these agents. Main Outcome and Measurement: Development of PASC based on a previously validated XGBoost-trained algorithm. Using inverse probability weighting and Poisson regression, relative risk (RR) of PASC was assessed. Results: A 26% reduction in the RR of PASC (0.74 [95% CI, 0.63-0.88]; P = 5 × 10 Conclusions and Relevance: SSRIs with and without reported agonist activity at the S1R were associated with a significant decrease in the risk of PASC. Future prospective studies are warranted.
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