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Analysis of the impact of antidepressants and other medications on COVID-19 infection risk in a chronic psychiatric in-patient cohort

Published online by Cambridge University Press:  03 December 2021

Catherine L. Clelland
Affiliation:
Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, USA; Department of Pathology and Cell Biology, Columbia University Irving Medical Center, USA; and Department of Psychiatry, Columbia University Irving Medical Center, USA
Krista Ramiah
Affiliation:
Clinical Research Department, The Nathan S. Kline Institute for Psychiatric Research, USA
Louisa Steinberg
Affiliation:
Clinical Research Department, The Nathan S. Kline Institute for Psychiatric Research, USA; and Department of Psychiatry, NYU Grossman School of Medicine, USA
James D. Clelland*
Affiliation:
Clinical Research Department, The Nathan S. Kline Institute for Psychiatric Research, USA
*
Correspondence: James Clelland. Email: clelland@nki.rfmh.org
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Abstract

Background

During the first wave of the coronavirus disease 2019 (COVID-19) pandemic, patients with confirmed cases in New York State accounted for roughly 25% of total US cases, with psychiatric hospital in-patients at particularly high risk for COVID-19 infection.

Aims

The beneficial effects of mental health medications, such as selective serotonin reuptake inhibitors (SSRIs), on the severity of COVID-19 disease outcomes have been documented. Protective effects against infection have also been suggested for these medications. We therefore tested the hypothesis that medication use modifies the risk of COVID-19 infection in a long-stay, chronic in-patient psychiatry setting, where the potential for exposure was likely uniform across the facility, and where these medications were routinely prescribed.

Method

This was a retrospective cohort study of an adult psychiatric facility operated by the New York State Office of Mental Health. Current medication information and COVID-19 status was collected from electronic medical records for 165 people who were in-patients during the period January to July 2020, and logistic regression was employed to model the main effects of medication use on COVID-19 infection.

Results

A significant protective association was observed between antidepressant use and COVID-19 infection (odds ratio (OR) = 0.33, 95% CI 0.15–0.70, adjusted P < 0.05). Analysis of individual antidepressant classes showed that SSRI, serotonin-norepinephrine reuptake inhibitor and the serotonin-2 antagonist reuptake inhibitor classes of antidepressants, drove this protective effect. Exploratory analyses of individual antidepressants demonstrated an association between lower risk of infection and fluoxetine use (P = 0.023), as well as trazodone use (P = 0.001).

Conclusions

The novel finding of reduced COVID-19 infection risk for psychiatric in-patients taking antidepressants, suggests that antidepressants may be an important weapon in the continued fight against COVID-19 disease. This finding may become particularly salient for in-patient settings if vaccine-resistant strains of the virus appear.

Information

Type
Papers
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Royal College of Psychiatrists
Figure 0

Table 1 Demographic and clinical characteristics of the RPC sample (n = 165)

Figure 1

Table 2 Odds ratios with 95% CIs of the unadjusted and adjusted medication models of COVID-19 infection

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