Hydroxychloroquine in Nonhospitalized Adults With Early COVID-19
Bibliographic record
Abstract
BACKGROUND: No effective oral therapy exists for early coronavirus disease 2019 (COVID-19). OBJECTIVE: To investigate whether hydroxychloroquine could reduce COVID-19 severity in adult outpatients. DESIGN: Randomized, double-blind, placebo-controlled trial conducted from 22 March through 20 May 2020. (ClinicalTrials.gov: NCT04308668). SETTING: Internet-based trial across the United States and Canada (40 states and 3 provinces). PARTICIPANTS: Symptomatic, nonhospitalized adults with laboratory-confirmed COVID-19 or probable COVID-19 and high-risk exposure within 4 days of symptom onset. INTERVENTION: Oral hydroxychloroquine (800 mg once, followed by 600 mg in 6 to 8 hours, then 600 mg daily for 4 more days) or masked placebo. MEASUREMENTS: Symptoms and severity at baseline and then at days 3, 5, 10, and 14 using a 10-point visual analogue scale. The primary end point was change in overall symptom severity over 14 days. RESULTS: = 0.29). LIMITATION: Only 58% of participants received SARS-CoV-2 testing because of severe U.S. testing shortages. CONCLUSION: Hydroxychloroquine did not substantially reduce symptom severity in outpatients with early, mild COVID-19. PRIMARY FUNDING SOURCE: Private donors.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".