A living WHO guideline on drugs to prevent covid-19
Bibliographic record
Abstract
CLINICAL QUESTION: What is the role of drugs in preventing covid-19? WHY DOES THIS MATTER?: There is widespread interest in whether drug interventions can be used for the prevention of covid-19, but there is uncertainty about which drugs, if any, are effective. The first version of this living guideline focuses on the evidence for hydroxychloroquine. Subsequent updates will cover other drugs being investigated for their role in the prevention of covid-19. RECOMMENDATION: The guideline development panel made a strong recommendation against the use of hydroxychloroquine for individuals who do not have covid-19 (high certainty). HOW THIS GUIDELINE WAS CREATED: This living guideline is from the World Health Organization (WHO) and provides up to date covid-19 guidance to inform policy and practice worldwide. Magic Evidence Ecosystem Foundation (MAGIC) provided methodological support. A living systematic review with network analysis informed the recommendations. An international guideline development panel of content experts, clinicians, patients, an ethicist and methodologists produced recommendations following standards for trustworthy guideline development using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. UNDERSTANDING THE NEW RECOMMENDATION: The linked systematic review and network meta-analysis (6 trials and 6059 participants) found that hydroxychloroquine had a small or no effect on mortality and admission to hospital (high certainty evidence). There was a small or no effect on laboratory confirmed SARS-CoV-2 infection (moderate certainty evidence) but probably increased adverse events leading to discontinuation (moderate certainty evidence). The panel judged that almost all people would not consider this drug worthwhile. In addition, the panel decided that contextual factors such as resources, feasibility, acceptability, and equity for countries and healthcare systems were unlikely to alter the recommendation. The panel considers that this drug is no longer a research priority and that resources should rather be oriented to evaluate other more promising drugs to prevent covid-19. UPDATES: This is a living guideline. New recommendations will be published in this article and signposted by update notices to this guideline. READERS NOTE: This is the first version of the living guideline for drugs to prevent covid-19. It complements the WHO living guideline on drugs to treat covid-19. When citing this article, please consider adding the update number and date of access for clarity.
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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 | 0.016 | 0.068 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.009 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.018 | 0.014 |
| Insufficient payload (model declined to judge) | 0.024 | 0.021 |
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".