Quality of reporting in abstracts of RCTs published in emergency medicine journals: a protocol for a systematic survey of the literature
Bibliographic record
Abstract
INTRODUCTION: The quality of reporting of abstracts of randomised controlled trials (RCTs) in major general medical journals and in some category-specific journals was shown to be poor before the publication of the ConsolidatedStandards of ReportingTrials (CONSORT) extension for abstracts in 2008, and an improvement in the quality of reporting of abstracts was observed after its publication. The effect of the publication of the CONSORT extension for abstracts on the quality of reporting of RCTs in emergency medicine journals has not been studied. In this paper, we present the protocol of a systematic survey of the literature, aimed at assessing the quality of reporting in abstracts of RCTs published in emergency medicine journals and at evaluating the effect of the publication of the CONSORT extension for abstracts on the quality of reporting. METHODS AND ANALYSIS: The Medline database will be searched for RCTs published in the years 2005-2007 and 2014-2015 in the top 10 emergency medicine journals, according to their impact factor. Candidate studies will be screened for inclusion in the review. Exclusion criteria will be the following: the abstract is not available, they are published only as abstracts, still recruiting, or duplicate publications. The study outcomes will be the overall quality of reporting (number of items reported) according to the CONSORT extension and the compliance with its individual items. Two independent reviewers will screen each article for inclusion and will extract data on the CONSORT items and on other variables, which can possibly affect the quality of reporting. ETHICS AND DISSEMINATION: This is a library-based study and therefore exempt from research ethics board review. The review results will be disseminated through abstract submission to conferences and publication in a peer-reviewed biomedical journal.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.276 | 0.330 |
| Meta-epidemiology (narrow) | 0.009 | 0.008 |
| Meta-epidemiology (broad) | 0.022 | 0.018 |
| Bibliometrics | 0.019 | 0.020 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.014 | 0.012 |
| Insufficient payload (model declined to judge) | 0.043 | 0.017 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".