Assessing the Effect of Selective Serotonin Reuptake Inhibitors in the Prevention of Post-Acute Sequelae of COVID-19
PhD Hythem Sidky, MD David K Sahner, PhD Andrew T Girvin, PhD Nathan Hotaling, Sam G Michael, MD Ken Gersing
doi:10.1101/2022.11.09.22282142
Findings: In this retrospective study leveraging real-world clinical data that included 17 933 patients, a 28% reduction in risk of PASC was observed for S1R agonist SSRIs and a 25% reduction in risk of PASC was observed for non-S1R agonist SSRIs, both versus controls, using a computable phenotype to define PASC. Meaning: SSRIs may play a role in managing the long term disease burden of COVID-19. Future prospective studies are warranted to confirm these findings and evaluate potential mechanisms of action.
Authors' contributions Authorship was determined using ICMJE recommendations. The authors hereby declare no conflicting interests pertaining to the material in this manuscript.
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'date-time': '2022-11-11T05:52:47Z',
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'abstract': '<jats:p>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 have been hypothesized to be '
'of potential benefit in patients with PASC, although clinical 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 x 10-4) was seen among patients who received an '
'S1R agonist SSRI compared to SSRI unexposed patients and a 25% reduction in the RR of PASC '
'was seen among those receiving an SSRI without S1R agonist activity (0.75 [95% CI, 0.62 - '
'0.90]; P = 0.003) compared to SSRI unexposed patients. 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.</jats:p>',
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'title': 'Assessing the Effect of Selective Serotonin Reuptake Inhibitors in the Prevention of Post-Acute '
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