Evaluating fluvoxamine for the outpatient treatment of COVID‐19: A systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract This systematic review and meta‐analysis of randomised controlled trials (RCTs) aimed to evaluate the efficacy, safety, and tolerability of fluvoxamine for the outpatient management of COVID‐19. We conducted this review in accordance with the PRISMA 2020 guidelines. Literature searches were conducted in MEDLINE, EMBASE, International Pharmaceutical Abstracts, CINAHL, Web of Science, and CENTRAL up to 14 September 2023. Outcomes included incidence of hospitalisation, healthcare utilization (emergency room visits and/or hospitalisation), mortality, supplemental oxygen and mechanical ventilation requirements, serious adverse events (SAEs) and non‐adherence. Fluvoxamine 100 mg twice a day was associated with reductions in the risk of hospitalisation (risk ratio [RR] 0.75, 95% confidence interval [CI] 0.58–0.97; I 2 = 0%) and reductions in the risk of healthcare utilization (RR 0.68, 95% CI 0.53–0.86; I 2 = 0%). While no increased SAEs were observed, fluvoxamine 100 mg twice a day was associated with higher treatment non‐adherence compared to placebo (RR 1.61, 95% CI 1.22–2.14; I 2 = 53%). In subgroup analyses, fluvoxamine reduced healthcare utilization in outpatients with BMI ≥30 kg/m2, but not in those with lower BMIs. While fluvoxamine offers potential benefits in reducing healthcare utilization, its efficacy may be most pronounced in high‐risk patient populations. The observed non‐adherence rates highlight the need for better patient education and counselling. Future investigations should reassess trial endpoints to include outcomes relating to post‐COVID sequelaes. Registration: This review was prospectively registered on PROSPERO (CRD42023463829).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.035 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".