Effect of Early Treatment with Fluvoxamine on Risk of Emergency Care and Hospitalization Among Patients with COVID-19: The TOGETHER Randomized Platform Clinical Trial
Bibliographic record
Abstract
ABSTRACT Background Recent evidence indicates a potential therapeutic role of fluvoxamine for COVID-19. In the TOGETHER randomized platform clinical trial for acutely symptomatic patients with COVID-19, we assessed the efficacy of fluvoxamine vs. placebo in preventing either extended emergency room observation or hospitalization due to COVID-19. Herein, we report the preliminary findings. Methods This placebo-controlled, randomized, adaptive, platform trial conducted among symptomatic Brazilian adults confirmed positive for SARS-CoV-2 included eligible patients with a known risk factor for progression to severe disease. Patients were randomly assigned to either fluvoxamine (100 mg twice daily for 10 days) or placebo. The primary endpoint was a composite outcome of emergency room observation for >6 hours or hospitalization from COVID-19 up to 28 days post randomization using intention to treat. Modified intention to treat (mITT) explored patients receiving at least 24 hours of treatment before a primary outcome event. Secondary outcomes included viral clearance at day 7, time to hospitalization, mortality, and adverse drug reactions. We used a Bayesian analytic framework to determine effects along with probability of success of intervention compared to placebo. The trial is registered at clinicaltrials.gov ( NCT04727424 ) and is ongoing. Findings The study team screened 9020 potential participants for this trial. The trial was initiated on June 2, 2020, with the current protocol reporting randomization from January 15, 2021 to August 6 th 2021, when the trial arms were stopped for superiority. A total of 3238 patients were allocated to fluvoxamine (n=739), placebo (n=733) and other treatments (n=1766). Herein, we report the effectiveness of fluvoxamine vs. a concurrent placebo control. The average age of participants was 50 years (range 18-102 years); 57% were female. The proportion of patients observed in an emergency room for >6 hours or admitted to hospital due to COVID-19 was lower for the fluvoxamine group compared to placebo (77/739 vs 108/733; Relative Risk [RR]: 0.71; 95% Bayesian Credible Interval [95% BCI]: 0.54 - 0.93), with a probability of superiority of 99.4% surpassing the prespecified superiority threshold of 97.6% (risk difference 4.3%). Of the composite primary outcome events, 88% were hospitalizations. Findings were similar for the mITT analysis (RR0.68, 95% BCI : 0.50- 0.91). We found no significant relative effects between the fluvoxamine and placebo groups on viral clearance at day 7 (Odds ratio [OR]: 0.75; 95% Confidence Intervals [95% CI]: 0.53 - 1.07), mortality (OR: 0.70; 95% CI: 0.36 - 1.30), time to death (Hazard ratio [HR]: 0.79; 95% CI: 0.58 - 1.08), days hospitalized (Mean Difference (MD) 1.22 days; 95% CI: 0.98 - 1.53), number of days ventilated (MD 1.10; 95% CI: 0.70 - 1.73) or other secondary outcomes. Data capturing all 28 days of follow-up will be reported after August 26 th , 2021. Interpretation Treatment with fluvoxamine (100 mg twice daily for 10 days) among high-risk outpatients with early diagnosed COVID-19, reduced the need for extended emergency room observation or hospitalization. Funding The trial was supported by FastGrants and The Rainwater Foundation.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".