A living WHO guideline on drugs for covid-19 (2020-2023)
Bibliographic record
Abstract
Updates: This is the fourteenth version (thirteenth update) of the living guideline, replacing earlier versions (available as data supplements). New recommendations will be published as updates to this guideline. Clinical question: What is the role of drugs in the treatment of patients with covid-19? Context: The evidence base for therapeutics for covid-19 is evolving with numerous randomised controlled trials (RCTs) recently completed and underway. Emerging SARS-CoV-2 variants and subvariants are changing the role of therapeutics. What is new?: The guideline development group (GDG) defined 1.5% as a new threshold for an important reduction in risk of hospitalisation in patients with non-severe covid-19. Combined with updated baseline risk estimates, this resulted in stratification into patients at low, moderate, and high risk for hospitalisation. New recommendations were added for moderate risk of hospitalisation for nirmatrelvir/ritonavir, and for moderate and low risk of hospitalisation for molnupiravir and remdesivir. New pharmacokinetic evidence was included for nirmatrelvir/ritonavir and molnupiravir, supporting existing recommendations for patients at high risk of hospitalisation. The recommendation for ivermectin in patients with non-severe illness was updated in light of additional trial evidence which reduced the high degree of uncertainty informing previous guidance. A new recommendation was made against the antiviral agent VV116 for patients with non-severe and with severe or critical illness outside of randomised clinical trials based on one RCT comparing the drug with nirmatrelvir/ritonavir. The structure of the guideline publication has also been changed; recommendations are now ordered by severity of covid-19. About this guideline: This living guideline from the World Health Organization (WHO) incorporates new evidence to dynamically update recommendations for covid-19 therapeutics. The GDG typically evaluates a therapy when the WHO judges sufficient evidence is available to make a recommendation. While the GDG takes an individual patient perspective in making recommendations, it also considers resource implications, acceptability, feasibility, equity, and human rights. This guideline was developed according to standards and methods for trustworthy guidelines, making use of an innovative process to achieve efficiency in dynamic updating of recommendations. The methods are aligned with the WHO Handbook for Guideline Development and according to a pre-approved protocol (planning proposal) by the Guideline Review Committee (GRC). A box at the end of the article outlines key methodological aspects of the guideline process. MAGIC Evidence Ecosystem Foundation provides methodological support, including the coordination of living systematic reviews with network meta-analyses to inform the recommendations. The full version of the guideline is available online in MAGICapp and in PDF on the WHO website, with a summary version here in The BMJ. These formats should facilitate adaptation, which is strongly encouraged by WHO to contextualise recommendations in a healthcare system to maximise impact. Future recommendations: Recommendations on anticoagulation are planned for the next update to this guideline. Updated data regarding systemic corticosteroids, azithromycin, favipiravir and umefenovir for non-severe illness, and convalescent plasma and statin therapy for severe or critical illness, are planned for review in upcoming guideline iterations.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.037 | 0.035 |
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".