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Record W2092386056 · doi:10.1136/bmjqs-2013-002293.63

032 Rapid Guidelines: A Systematic Review

2013· review· en· W2092386056 on OpenAlexaff
Maicon Falavigna, Faria Sakhia, Yuan Zhang, Nancy Santesso, Susan L. Norris, Holger J. Schünemann

Bibliographic record

VenueBMJ Quality & Safety · 2013
Typereview
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineMEDLINEData scienceComputer science

Abstract

fetched live from OpenAlex

Background Guidelines often take two or more years to be developed. This timeframe is not practical for providing guidance in situations when rapid advice is needed. Objectives To describe current practices about the development of rapid guidelines and to provide advice about adequate methodology. Methods We performed a systematic review, including grey literature, to identify (1) rapid guidelines, defined as guidelines produced in a shortened time frame, and (2) methodological manuals addressing its development. Results We only documents by WHO and NICE that described methods and actual guidelines. The WHO handbook describes “rapid advice guidelines”; guidelines produced in response to a public health emergency in which WHO is required to provide rapid global leadership and guidance. This advice should be produced within 1 to 3 months and be evidence-informed, however, it may not be supported by full reviews of the evidence. We identified six WHO rapid guidelines and one methodological guidance paper based on a WHO guideline. NICE produces “short clinical guidelines”; guidelines that address only part of a care pathway, allowing rapid (11–13-month) development of guidance on aspects of care for which the NHS requires urgent advice. We identified 18 NICE short clinical guidelines. Discussion Literature is lacking about rapid guidelines and the intended role appears to differ. Despite its relevance, there are few rapid guidelines published and clarity about the terminology is needed. Implications for Guideline Developers We will provide a framework for those developing rapid guidelines, including practical advice and clarification about the terminology used.

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)0.046
metaresearch head score (Gemma)0.218
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score0.246

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0460.218
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0060.007
Bibliometrics0.0200.018
Science and technology studies0.0010.002
Scholarly communication0.0040.008
Open science0.0040.004
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0150.002

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 head0.726
GPT teacher head0.665
Teacher spread0.061 · 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.

Study designSystematic review
DomainMethods
GenreReview

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

Citations0
Published2013
Admission routes1
Has abstractyes

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