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Meta-Analysis
. 2021 Oct 1;78(10):1079-1091.
doi: 10.1001/jamapsychiatry.2021.1818.

Association Between Mood Disorders and Risk of COVID-19 Infection, Hospitalization, and Death: A Systematic Review and Meta-analysis

Felicia Ceban  1   2 , Danica Nogo  2 , Isidro P Carvalho  2 , Yena Lee  2 , Flora Nasri  2 , Jiaqi Xiong  2 , Leanna M W Lui  2 , Mehala Subramaniapillai  2   3 , Hartej Gill  2   3 , Rene N Liu  2 , Prianca Joseph  2 , Kayla M Teopiz  2 , Bing Cao  2 , Rodrigo B Mansur  2   4 , Kangguang Lin  5   6 , Joshua D Rosenblat  2   3   4 , Roger C Ho  7   8 , Roger S McIntyre  2   3   4
Affiliations
Meta-Analysis

Association Between Mood Disorders and Risk of COVID-19 Infection, Hospitalization, and Death: A Systematic Review and Meta-analysis

Felicia Ceban et al. JAMA Psychiatry. .

Abstract

Importance: Preexisting noncommunicable diseases (eg, diabetes) increase the risk of COVID-19 infection, hospitalization, and death. Mood disorders are associated with impaired immune function and social determinants that increase the risk of COVID-19. Determining whether preexisting mood disorders represent a risk of COVID-19 would inform public health priorities.

Objective: To assess whether preexisting mood disorders are associated with a higher risk of COVID-19 susceptibility, hospitalization, severe complications, and death.

Data sources: Systematic searches were conducted for studies reporting data on COVID-19 outcomes in populations with and without mood disorders on PubMed/MEDLINE, The Cochrane Library, PsycInfo, Embase, Web of Science, Google/Google Scholar, LitCovid, and select reference lists. The search timeline was from database inception to February 1, 2021.

Study selection: Primary research articles that reported quantitative COVID-19 outcome data in persons with mood disorders vs persons without mood disorders of any age, sex, and nationality were selected. Of 1950 articles identified through this search strategy, 21 studies were included in the analysis.

Data extraction and synthesis: The modified Newcastle-Ottawa Scale was used to assess methodological quality and risk of bias of component studies. Reported adjusted odds ratios (ORs) were pooled with unadjusted ORs calculated from summary data to generate 4 random-effects summary ORs, each corresponding to a primary outcome.

Main outcomes and measures: The 4 a priori primary outcomes were COVID-19 susceptibility, COVID-19 hospitalization, COVID-19 severe events, and COVID-19 death. The hypothesis was formulated before study search. Outcome measures between individuals with and without mood disorders were compared.

Results: This review included 21 studies that involved more than 91 million individuals. Significantly higher odds of COVID-19 hospitalization (OR, 1.31; 95% CI, 1.12-1.53; P = .001; n = 26 554 397) and death (OR, 1.51; 95% CI, 1.34-1.69; P < .001; n = 25 808 660) were found in persons with preexisting mood disorders compared with those without mood disorders. There was no association between mood disorders and COVID-19 susceptibility (OR, 1.27; 95% CI, 0.73-2.19; n = 65 514 469) or severe events (OR, 0.94; 95% CI, 0.87-1.03; n = 83 240). Visual inspection of the composite funnel plot for asymmetry indicated the presence of publication bias; however, the Egger regression intercept test result was not statistically significant.

Conclusions and relevance: The results of this systematic review and meta-analysis examining the association between preexisting mood disorders and COVID-19 outcomes suggest that individuals with preexisting mood disorders are at higher risk of COVID-19 hospitalization and death and should be categorized as an at-risk group on the basis of a preexisting condition.

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Conflict of interest statement

Conflict of Interest Disclosures: Ms Lee reported receiving personal fees from Braxia Scientific Corp outside the submitted work. Ms Lui is a contractor to Braxia Scientific Corp. Ms Teopiz reported receiving personal fees from Braxia Scientific Corp outside the submitted work. Dr Rosenblat is the medical director of Braxia Health (formally known as the Canadian Rapid Treatment Center of Excellence and is a fully owned subsidiary of Braxia Scientific Corp), which provides ketamine and esketamine treatment for depression, and has received research grant support from the American Psychiatric Association, American Society of Psychopharmacology, Canadian Cancer Society, Canadian Psychiatric Association, Joseph M. West Family Memorial Fund, Timeposters Fellowship, University Health Network Centre for Mental Health, and University of Toronto and speaking, consultation, or research fees from Allergan, COMPASS, Janssen, Lundbeck, and Sunovion. Dr McIntyre reported receiving grant support from Canadian Institutes of Health Research, Global Alliance for Chronic Diseases, and Chinese National Natural Research Foundation and speaker/consultation fees from Lundbeck, Janssen, Purdue, Pfizer, Otsuka, Takeda, Neurocrine, Sunovion, Bausch Health, Novo Nordisk, Kris, Sanofi, Eisai, Intra-Cellular, NewBridge Pharmaceuticals, and AbbVie. Dr McIntyre is a chief executive officer of Braxia Scientific Corp.

Figures

Figure 1.
Figure 1.. Study Selection Flowchart
Figure 2.
Figure 2.. Pooled Odds Ratios for COVID-19 Susceptibility, Hospitalization, Severe Events, and Death in Individuals With vs Without Preexisting Mood Disorders
A, There was no association between COVID-19 susceptibility and preexisting mood disorders (n = 65 514 469). B, The odds of COVID-19 hospitalization were significantly greater for individuals with preexisting mood disorders when compared with those without mood disorders (n = 26 554 397). C, There was no association between COVID-19 severe events or preexisting mood disorders (n = 83 240). D, The odds of COVID-19-related death were significantly greater for individuals with preexisting mood disorders when compared with those without mood disorders (n = 25 808 660). Squares represent effect sizes of individual studies, lines indicate the 95% CIs, and the diamond represents the summary effect size (ie, statistical combination of the effect sizes of component studies via the random-effects model).
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