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Record W2136068942 · doi:10.1136/bmj.330.7491.594

Validity of composite end points in clinical trials

2005· review· en· W2136068942 on OpenAlexaff
Víctor M. Montori, Gaietà Permanyer-Miralda, Ignacio Ferreira‐González, Jason W. Busse, Valeria Pacheco‐Huergo, Dianne Bryant, Jordi Alonso, Elie A. Akl, Antònia Domingo‐Salvany, Edward J. Mills, Ping Wu, Holger J. Schünemann, Roman Jaeschke, Gordon Guyatt

Bibliographic record

VenueBMJ · 2005
Typereview
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsCanadian College of Naturopathic MedicineMcMaster University
Fundersnot available
KeywordsComposite numberClinical trialPsychologyMedicineMathematicsInternal medicineAlgorithm

Abstract

fetched live from OpenAlex

Use of composite end points as the main outcome in randomised trials can hide wide differences in the individual measures. How should you apply the results to clinical practice?

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)0.794
metaresearch head score (Gemma)0.944
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.206
Threshold uncertainty score0.254

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.7940.944
Meta-epidemiology (narrow)0.0040.006
Meta-epidemiology (broad)0.0210.026
Bibliometrics0.0210.020
Science and technology studies0.0040.029
Scholarly communication0.0230.020
Open science0.0080.014
Research integrity0.0150.021
Insufficient payload (model declined to judge)0.0050.002

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 head0.969
GPT teacher head0.730
Teacher spread0.239 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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

Citations435
Published2005
Admission routes1
Has abstractyes

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