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Record W2756226120 · doi:10.1136/bmj.j4090

Corticosteroids for sore throat: a clinical practice guideline

2017· article· en· W2756226120 on OpenAlexaff
Bert Aertgeerts, Thomas Agoritsas, Reed Siemieniuk, Jako Burgers, Geertruida E Bekkering, Arnaud Merglen, Mieke van Driel, Mieke Vermandere, Dominique Bullens, Patrick Okwen, Ricardo Niño, Lyubov Lytvyn, Carla Berg-Nelson, Shunjie Chua, Jack L. Leahy, Jennifer F. Raven, Michael Weinberg, Behnam Sadeghirad, Per Olav Vandvik, Romina Brignardello‐Petersen

Bibliographic record

VenueBMJ · 2017
Typearticle
Languageen
FieldMedicine
TopicOtolaryngology and Infectious Diseases
Canadian institutionsCochraneUniversity of TorontoMcMaster UniversityImpact
Fundersnot available
KeywordsSore throatGuidelineMedicineInfographicClinical PracticeIntensive care medicineFamily medicineSurgeryData miningComputer sciencePathology

Abstract

fetched live from OpenAlex

What is the role of a single dose of oral corticosteroids for those with acute sore throat? Using the GRADE framework according to the BMJ Rapid Recommendation process, an expert panel make a weak recommendation in favour of corticosteroid use. The panel produced these recommendations based on a linked systematic review triggered by a large randomised trial published in April 2017. This trial reported that corticosteroids increased the proportion of patients with complete resolution of pain at 48 hours. Box 1 shows all of the articles and evidence linked in this Rapid Recommendation package. The infographic provides the recommendation together with an overview of the absolute benefits and harms of corticosteroids in the standard GRADE format. Table 2 below shows any evidence that has emerged since the publication of this article. Clinicians and their patients can find consultation decision aids to facilitate shared decision making in MAGICapp (www.magicapp.org/goto/guideline/JjXYAL/section/j79pvn).

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.050
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.050
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0050.007
Bibliometrics0.0070.006
Science and technology studies0.0020.002
Scholarly communication0.0040.004
Open science0.0060.003
Research integrity0.0140.013
Insufficient payload (model declined to judge)0.0150.015

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 head0.079
GPT teacher head0.492
Teacher spread0.413 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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

Citations23
Published2017
Admission routes1
Has abstractyes

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Same venueBMJSame topicOtolaryngology and Infectious DiseasesFrench-language works237,207