Efficacy and safety of selective serotonin reuptake inhibitors in COVID-19 management: A systematic review and meta-analysis
Jiawen Deng, Daniel Rayner, Harikrishnaa Ba Ramaraju, Umaima Abbas, Cristian Garcia, Kiyan Heybati, Fangwen Zhou, Emma Huang, Ye-Jean Park, Myron Moskalyk
Clinical Microbiology and Infection, doi:10.1016/j.cmi.2023.01.010
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Lastly, we found that fluvoxamine was not associated with reduced hospitalization once we excluded one study with a high risk of bias rating. This was likely due to loss of precision from a reduced sample size given the small number of studies and patients included in this review. The incorporation of larger, betterdesigned RCTs in future meta-analyses can help confirm our findings relating to hospitalization.
CONCLUSION This systematic review and meta-analysis of 6 RCTs and 5 observational studies found that fluvoxamine may reduce mortality and hospitalization based on moderate quality of evidence. Medium
J o u r n a l P r e -p r o o f
CONFLICT OF INTEREST The authors declare no conflicts of interest.
J o u r n a l P r e -p r o o f
GRADE Working Group quality of evidence rating [28] High quality: We are very confident that the true effect lies close to that of the estimate of the effect Moderate quality: We are moderately confident in the effect estimate; the true effect is likely to be close to the estimate of the effect, but there is a possibility that it is substantially different Low quality: Our confidence in the effect estimate is limited; the true effect may be substantially different from the estimate of the effect Very low quality: We have very little confidence in the effect estimate; the true effect is likely to be substantially different from the estimate of effect a The risk in the intervention group (and its 95% CI) is based on the assumed risk in..
References
Bloch, Mcguire, Landeros-Weisenberger, Leckman, Pittenger, Meta-analysis of the dose-response relationship of SSRI in obsessive-compulsive disorder, Mol Psychiatry,
doi:10.1038/mp.2009.50
Bollini, Pampallona, Tibaldi, Kupelnick, Munizza, Effectiveness of antidepressants. Meta-analysis of dose-effect relationships in randomised clinical trials, Br J Psychiatry,
doi:10.1192/bjp.174.4.297
Bramante, Huling, Tignanelli, Buse, Liebovitz et al., Randomized Trial of Metformin, Ivermectin, and Fluvoxamine for Covid-19, N Engl J Med,
doi:10.1056/NEJMoa2201662
Calusic, Marcec, Luksa, Jurkovic, Kovac et al., Safety and efficacy of fluvoxamine in COVID-19 ICU patients: An open label, prospective cohort trial with matched controls, Br J Clin Pharmacol,
doi:10.1111/bcp.15126
Cheng, Pullenayegum, Marshall, Iorio, Thabane, Impact of including or excluding botharmed zero-event studies on using standard meta-analysis methods for rare event outcome: a simulation study, BMJ Open,
doi:10.1136/bmjopen-2015-010983
Guo, Harari, Chernecki, Thorlund, Forrest, Fluvoxamine for the Early Treatment of COVID-19: A Meta-analysis of Randomized Clinical Trials, Am J Trop Med Hyg,
doi:10.4269/ajtmh.21-1310
Guyatt, Oxman, Santesso, Helfand, Vist et al., GRADE guidelines: 12. J o u r n a l P r e -p r o o f Preparing summary of findings tables-binary outcomes, J Clin Epidemiol,
doi:10.1016/j.jclinepi.2012.01.012
Guyatt, Oxman, Vist, Kunz, Falck-Ytter et al., GRADE: an emerging consensus on rating quality of evidence and strength of recommendations, BMJ,
doi:10.1136/bmj.39489.470347.AD
Hashimoto, Activation of sigma-1 receptor chaperone in the treatment of neuropsychiatric diseases and its clinical implication, J Pharmacol Sci,
doi:10.1016/j.jphs.2014.11.010
Hashimoto, Repurposing of CNS drugs to treat COVID-19 infection: targeting the sigma-1 receptor, Eur Arch Psychiatry Clin Neurosci,
doi:10.1007/s00406-020-01231-x
Hoertel, Sánchez-Rico, Kornhuber, Gulbins, Reiersen et al., Antidepressant Use and Its Association with 28-Day Mortality in Inpatients with SARS-CoV-2: Support for the FIASMA Model against COVID-19, J Clin Med Res,
doi:10.3390/jcm11195882
Ishikawa, Ishiwata, Ishii, Kimura, Sakata et al., High occupancy of sigma-1 receptors in the human brain after single oral administration of fluvoxamine: a positron emission tomography study using [11C]SA4503, Biol Psychiatry,
doi:10.1016/j.biopsych.2007.04.001
Lee, Vigod, Bortolussi-Courval, Hanula, Boulware et al., Fluvoxamine for Outpatient Management of COVID-19 to Prevent Hospitalization: A Systematic Review and Metaanalysis, JAMA Netw Open,
doi:10.1001/jamanetworkopen.2022.6269
Lenze, Mattar, Zorumski, Stevens, Schweiger et al., Fluvoxamine vs Placebo and Clinical Deterioration in Outpatients With Symptomatic COVID-19: A Randomized Clinical Trial, JAMA,
doi:10.1001/jama.2020.22760
Mccarthy, Naggie, Boulware, Lindsell, Stewart et al., Fluvoxamine for Outpatient Treatment of COVID-19: A Decentralized, Placebo-controlled, Randomized, Platform Clinical Trial,
doi:10.1101/2022.10.17.22281178v2
Min, Kim, Oh, Kim, Lee, COVID-19 Prognosis in Association with Antidepressant Use, Pharmacopsychiatry,
doi:10.1055/a-1842-7859
Nawas, Zeidan, Edwards, El-Desoky, Barriers to COVID-19 Vaccines and Strategies to Improve Acceptability and Uptake, J Pharm Pract,
doi:10.1177/08971900221081621
Németh, Szûcs, Vitrai, Juhász, Németh et al., Fluoxetine use is associated with improved survival of patients with COVID-19 pneumonia: A retrospective case-control study, Ideggyogy Sz,
doi:10.18071/isz.74.0389
Oskotsky, Maric, Tang, Oskotsky, Wong et al., Mortality Risk Among Patients With COVID-19 Prescribed Selective Serotonin Reuptake Inhibitor Antidepressants, JAMA Netw Open,
doi:10.1001/jamanetworkopen.2021.33090
Page, Mckenzie, Bossuyt, Boutron, Hoffmann et al., The PRISMA 2020 statement: an updated guideline for reporting systematic reviews, BMJ,
doi:10.1136/bmj.n71
Pepperrell, Ellis, Wang, Hill, Barriers to Worldwide Access for Paxlovid, a New Treatment for COVID-19, Open Forum Infect Dis,
doi:10.1093/ofid/ofac174
Puzhko, Aboushawareb, Kudrina, Schuster, Barnett et al., Excess body weight as a predictor of response to treatment with antidepressants in patients with depressive disorder, J Affect Disord,
doi:10.1016/j.jad.2020.01.113
Reis, Santos Moreira-Silva, Silva, Thabane, Milagres et al., r n a l P r e -p r o o f Effect of early treatment with fluvoxamine on risk of emergency care and hospitalisation among patients with COVID-19: the TOGETHER randomised, platform clinical trial, Lancet Glob Health,
doi:10.1016/S2214-109X(21)00448-4
Ren, Lin, Lian, Zou, Chu, Real-world Performance of Meta-analysis Methods for Double-Zero-Event Studies with Dichotomous Outcomes Using the Cochrane Database of Systematic Reviews, J Gen Intern Med,
doi:10.1007/s11606-019-04925-8
Sattar, Valabhji, Obesity as a Risk Factor for Severe COVID-19: Summary of the Best Evidence and Implications for Health Care, Curr Obes Rep,
doi:10.1007/s13679-021-00448-8
Seftel, Boulware, Prospective Cohort of Fluvoxamine for Early Treatment of Coronavirus Disease 19, Open Forum Infect Dis,
doi:10.1093/ofid/ofab050
Seo, Kim, Bae, Park, Chung et al., Fluvoxamine Treatment of Patients with Symptomatic COVID-19 in a Community Treatment Center: A Preliminary Result of Randomized Controlled Trial, Infect Chemother,
doi:10.3947/ic.2021.0142
Sterne, Hernán, Reeves, Savović, Berkman et al., ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions, BMJ,
doi:10.1136/bmj.i4919
Sterne, Savović, Page, Elbers, Blencowe et al., RoB 2: a revised tool for assessing risk of bias in randomised trials, BMJ,
doi:10.1136/bmj.l4898
Sweeting, Sutton, Lambert, What to add to nothing? Use and avoidance of continuity corrections in meta-analysis of sparse data, Stat Med,
doi:10.1002/sim.1761