Safety of Hydroxychloroquine Among Outpatient Clinical Trial Participants for COVID-19
Bibliographic record
Abstract
BACKGROUND: Use of hydroxychloroquine in hospitalized patients with coronavirus disease 2019 (COVID-19), especially in combination with azithromycin, has raised safety concerns. Here, we report safety data from 3 outpatient randomized clinical trials. METHODS: We conducted 3 randomized, double-blind, placebo-controlled trials investigating hydroxychloroquine as pre-exposure prophylaxis, postexposure prophylaxis, and early treatment for COVID-19 using an internet-based design. We excluded individuals with contraindications to hydroxychloroquine. We collected side effects and serious adverse events. We report descriptive analyses of our findings. RESULTS: We enrolled 2795 participants. The median age of research participants (interquartile range) was 40 (34-49) years, and 59% (1633/2767) reported no chronic medical conditions. Overall 2544 (91%) participants reported side effect data, and 748 (29%) reported at least 1 medication side effect. Side effects were reported in 40% with once-daily, 36% with twice-weekly, 31% with once-weekly hydroxychloroquine, compared with 19% with placebo. The most common side effects were upset stomach or nausea (25% with once-daily, 19% with twice-weekly, and 18% with once-weekly hydroxychloroquine, vs 11% for placebo), followed by diarrhea, vomiting, or abdominal pain (23% for once-daily, 17% twice-weekly, and 13% once-weekly hydroxychloroquine, vs 7% for placebo). Two individuals were hospitalized for atrial arrhythmias, 1 on placebo and 1 on twice-weekly hydroxychloroquine. No sudden deaths occurred. CONCLUSIONS: Data from 3 outpatient COVID-19 trials demonstrated that gastrointestinal side effects were common but mild with the use of hydroxychloroquine, while serious side effects were rare. No deaths occurred related to hydroxychloroquine. Randomized clinical trials, in cohorts of healthy outpatients, can safely investigate whether hydroxychloroquine is efficacious for COVID-19. CLINICALTRIALSGOV IDENTIFIER: NCT04308668 for postexposure prophylaxis and early treatment trials; NCT04328467 for pre-exposure prophylaxis trial.
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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 | 0.035 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".