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Assessing the effect of selective serotonin reuptake inhibitors in the prevention of post-acute sequelae of COVID-19

Sidky, Hythem
Hansen, Kristen A
Girvin, Andrew T
Hotaling, Nathan
Michael, Sam G
Gersing, Ken
Sahner, David K
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Abstract

Background: 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 although clinical trial data are lacking.

Materials and methods: This retrospective study was conducted leveraging real-world clinical data within the National COVID Cohort Collaborative (N3C) to evaluate whether SSRIs with agonist activity at the sigma-1 receptor (S1R) lower the risk of PASC, since agonism at this receptor may serve as a mechanism by which SSRIs attenuate an inflammatory response. Additionally, determine whether the potential benefit could be traced to S1R agonism. Presumed PASC was defined based on a computable PASC phenotype trained on the U09.9 ICD-10 diagnosis code.

Results: Of the 17,908 patients identified, 1521 were exposed at baseline to a S1R agonist SSRI, 1803 to a non-S1R agonist SSRI, and 14,584 to neither. Using inverse probability weighting and Poisson regression, relative risk (RR) of PASC was assessed.A 29% reduction in the RR of PASC (0.704 [95% CI, 0.58-0.85]; P = 4 ×10-4) was seen among patients who received an S1R agonist SSRI compared to SSRI unexposed patients and a 21% reduction in the RR of PASC was seen among those receiving an SSRI without S1R agonist activity (0.79 [95% CI, 0.67 - 0.93]; P = 0.005).Thus, SSRIs with and without reported agonist activity at the S1R were associated with a significant decrease in the risk of PASC.

Source

Sidky H, Hansen KA, Girvin AT, Hotaling N, Michael SG, Gersing K, Sahner DK; N3C consortium. Assessing the effect of selective serotonin reuptake inhibitors in the prevention of post-acute sequelae of COVID-19. Comput Struct Biotechnol J. 2024 Jan 9;24:115-125. doi: 10.1016/j.csbj.2023.12.045. PMID: 38318198; PMCID: PMC10839808.

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DOI
10.1016/j.csbj.2023.12.045
PubMed ID
38318198
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Funding and Acknowledgements
The UMass Center for Clinical and Translational Science (UMCCTS), UL1TR001453, provided data for this study.
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© 2024 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Attribution-NonCommercial-NoDerivatives 4.0 International