MétaCan
Menu
Back to cohort
Record W3133718957 · doi:10.1136/bmj.n526

A living WHO guideline on drugs to prevent covid-19

2021· article· en· W3133718957 on OpenAlexaff
François Lamontagne, Miriam Stegemann, Arnav Agarwal, Thomas Agoritsas, Reed Siemieniuk, Bram Rochwerg, Jessica J Bartoszko, Lisa Askie, Helen Macdonald, Muna Almaslamani, Wagdy Amin, André Ricardo Araújo da Silva, Fabián Alberto Jaimes Barragán, Frédérique Jacquerioz Bausch, Erlina Burhan, Maurizio Cecconi, Binila Chacko, Duncan Chanda, Vu Quoc Dat, Bin Du, Heike Geduld, Patrick O. Gee, Muhammad Mohsin Haider, Nerina Harley, Madiha Hashimi, Fyezah Jehan, David S.C. Hui, Beverley J. Hunt, Mohamed Ismail, S. K. Kabra, Seema Kanda, Letícia Kawano-Dourado, Yae‐Jean Kim, Niranjan Kissoon, Sanjeev Krishna, Arthur Kwizera, Thiago Lisboa, Yee‐Sin Leo, Imelda Mahaka, Hela Manai, Giovanni Battista Migliori, G Miño, Emmanuel Nsutebu, N. Pshenichnaya, Nida Qadir, Shalini Sri Ranganathan, Saniya Sabzwari, Rohit Sarin, Manu Shankar‐Hari, Yinzhong Shen, João Paulo Souza, Tshokey Tshokey, Sebastián Ugarte, Tim Uyeki, Sridhar Venkatapuram, Ablo Prudence Wachinou, Ananda Wijewickrama, Dubula Vuyiseka, Jacobus Preller, Romina Brignardello‐Petersen, Elena Kum, Anila Qasim, Dena Zeraatkar, Andrew Owen, Gordon Guyatt, Lyubov Lytvyn, Michael Jacobs, Per Olav Vandvik, Janet Dı́az

Bibliographic record

VenueBMJ · 2021
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsUniversity of British ColumbiaImpactMcMaster UniversityUniversité de Sherbrooke
FundersEngineering and Physical Sciences Research CouncilWorld Health OrganizationBill and Melinda Gates Foundation
KeywordsGuidelineMedicineHydroxychloroquinePsychological interventionGrading (engineering)MEDLINEFamily medicineAlternative medicineRandomized controlled trialHealth careCoronavirus disease 2019 (COVID-19)NursingPathologyPolitical science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.216
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.561
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.216
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.097
GPT teacher head0.516
Teacher spread0.419 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations150
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueBMJSame topicCOVID-19 Clinical Research StudiesFrench-language works237,207