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Record W4409417738 · doi:10.1001/jama.2025.4347

CONSORT 2025 Statement

2025· letter· en· W4409417738 on OpenAlexaff
Sally Hopewell, An‐Wen Chan, Gary S. Collins, Asbjørn Hróbjartsson, David Moher, Kenneth F. Schulz, R. Tunn, Rakesh Aggarwal, Michael Berkwits, Jesse A. Berlin, Nita Bhandari, Nancy J. Butcher, Marion Campbell, Runcie C.W. Chidebe, Diana Elbourne, Andrew Farmer, Dean Fergusson, Robert Golub, Steven N. Goodman, Tammy Hoffmann, John P. A. Ioannidis, Brennan C Kahan, Rachel L Knowles, Sarah E Lamb, Steff Lewis, Elizabeth Loder, Martin Offringa, Philippe Ravaud, Dawn P. Richards, Frank W. Rockhold, David L. Schriger, Nandi Siegfried, Sophie Staniszewska, Rod S Taylor, Lehana Thabane, David Torgerson, Sunita Vohra, Ian R. White, Isabelle Boutron

Bibliographic record

VenueJAMA · 2025
Typeletter
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsImpactUniversity of AlbertaRobarts Clinical TrialsUniversity of TorontoSickKids FoundationSt. Joseph’s Healthcare HamiltonHospital for Sick ChildrenOttawa HospitalMcMaster UniversityWomen's College Hospital
Fundersnot available
KeywordsConsolidated Standards of Reporting TrialsChecklistMedicineDelphi methodRandomized controlled trialPsychological interventionQuality (philosophy)Family medicineMedical educationComputer sciencePsychologyNursingSurgery

Abstract

fetched live from OpenAlex

Importance: Well-designed and properly executed randomized trials are considered the most reliable evidence on the benefits of health care interventions. However, there is overwhelming evidence that the quality of reporting is not optimal. The CONSORT (Consolidated Standards of Reporting Trials) statement was designed to improve the quality of reporting and provides a minimum set of items to be included in a report of a randomized trial. CONSORT was first published in 1996, then updated in 2001 and 2010. Herein, we present the updated CONSORT 2025 statement, which aims to account for recent methodological advancements and feedback from end users. Observations: We conducted a scoping review of the literature and developed a project-specific database of empirical and theoretical evidence related to CONSORT to generate a list of potential changes to the checklist. The list was enriched with recommendations provided by the lead authors of existing CONSORT extensions (harms, outcomes, nonpharmacological treatment), other related reporting guidelines (Template for Intervention Description and Replication [TIDieR]), and recommendations from other sources (eg, personal communications). The list of potential changes to the checklist was assessed in a large, international, online, 3-round Delphi survey involving 317 participants and discussed at a 2-day online expert consensus meeting of 30 invited international experts. We have made substantive changes to the CONSORT checklist. We added 7 new checklist items, revised 3 items, deleted 1 item, and integrated several items from key CONSORT extensions. We also restructured the CONSORT checklist, with a new section on open science. The CONSORT 2025 statement consists of a 30-item checklist of essential items that should be included when reporting the results of a randomized trial and a diagram for documenting the flow of participants through the trial. To facilitate implementation of CONSORT 2025, we have also developed an expanded version of the CONSORT 2025 checklist, with bullet points eliciting critical elements of each item. Conclusions and Relevance: Authors, editors, reviewers, and other potential users should use CONSORT 2025 when writing and evaluating manuscripts of randomized trials to ensure that trial reports are clear and transparent.

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)0.089
metaresearch head score (Gemma)0.034
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.316
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0890.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.000
Open science0.0030.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0910.032

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 head0.709
GPT teacher head0.539
Teacher spread0.170 · 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; both teacher heads agree on what is shown here.

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

Citations219
Published2025
Admission routes1
Has abstractyes

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