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Record W2754629999 · doi:10.1016/j.gaceta.2017.03.008

Marcos GRADE de la evidencia a la decisión (EtD): un enfoque sistemático y transparente para tomar decisiones sanitarias bien informadas. 2: Guías de práctica clínica

2017· article· es· W2754629999 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGaceta Sanitaria · 2017
Typearticle
Languagees
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsMcMaster University
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Clinicians do not have the time or resources to consider the underlying evidence for the myriad decisions they must make each day and, as a consequence, rely on recommendations from clinical practice guidelines. Guideline panels should consider all the relevant factors (criteria) that influence a decision or recommendation in a structured, explicit, and transparent way and provide clinicians with clear and actionable recommendations. In this article, we will describe the Evidence to Decision (EtD) frameworks for clinical practice recommendations. The general structure of the EtD framework for clinical recommendations is similar to EtD frameworks for other types of recommendations and decisions, and includes formulation of the question, an assessment of the different criteria, and conclusions. Clinical recommendations require considering criteria differently, depending on whether an individual patient or a population perspective is taken. For example, from an individual patient's perspective, out-of-pocket costs are an important consideration, whereas, from a population perspective, resource use (not only out-of-pocket costs) and cost effectiveness are important. From a population perspective, equity, acceptability, and feasibility are also important considerations, whereas the importance of these criteria is often limited from an individual patient perspective. Specific subgroups for which different recommendations may be required should be clearly identified and considered in relation to each criterion because judgments might vary across subgroups. This article is a translation of the original article published in the British Medical Journal. The EtD frameworks are currently used in the Clinical Practice Guideline Programme of the Spanish National Health System, co-ordinated by GuíaSalud.

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.

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)0.011
metaresearch head score (Gemma)0.059
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.255
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.059
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.150
GPT teacher head0.468
Teacher spread0.318 · 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