Publication Bias of Randomized Controlled Trials in Emergency Medicine
Bibliographic record
Abstract
Objectives: To determine the publication status and time to publication of randomized controlled trials (RCTs) that were presented at the Society for Academic Emergency Medicine (SAEM) meetings from 1995 to 2003. The impact of positive-outcome bias, time-lag bias, and gray literature bias also was assessed. Methods: Retrospective cohort study of RCT abstracts presented at nine SAEM scientific meetings. Electronic searches identified publications from the abstracts. Results: Of 4,399 abstracts, 383 (8.7%; 95% confidence interval [CI] = 7.8% to 9.5%) were identified as RCTs. One hundred ninety-four (50.7%; 95% CI = 45.7% to 55.7%) were subsequently published up to May 2004. The median time to publication was 32 months (95% CI = 23 to 41), with 59% of RCT abstracts published within five years of presentation. No evidence of positive-outcome bias or time-lag bias was identified; however, changes from abstract to manuscript were found. Manuscripts were less likely to endorse the experimental intervention than were abstracts (OR, 0.2; 95% CI = 0.0 to 0.6). Conclusions: The proportion of emergency medicine RCT abstracts published is slightly lower than that for other biomedical specialties; however, biases reported by investigators in other biomedical areas do not appear to be as problematic in emergency medicine research. Differences between conclusions from abstracts and manuscripts must be considered when employing meeting abstracts as a source of evidence for future research or for systematic reviews in emergency medicine.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Reporting · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | MetaresearchScholarly communication Domain: Reporting · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.565 | 0.827 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.017 |
| Bibliometrics | 0.021 | 0.022 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.009 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".