Guidelines based on multiple randomized studies prove the most durable, US study finds
Bibliographic record
Abstract
Guideline recommendations based on a single trial, observational data, expert opinion, or standard of care were three times more likely to be downgraded, reversed, or omitted in subsequent guidelines than those based on multiple randomized trials, a new study published in JAMA has shown.1 In the study researchers looked at changes in class I recommendations in the two most recent versions of 11 guidelines jointly issued by the American Heart Association and the American College of Cardiology. The guidelines included recommendations on issues such as managing atrial fibrillation, chronic stable angina, and heart failure; the use of cardiac pacemakers and anti-arrhythmia devices; and the secondary prevention of coronary artery disease and cardiovascular disease prevention in women. These guidelines used four …
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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 | 0.234 | 0.687 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.011 | 0.013 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.020 | 0.011 |
| Insufficient payload (model declined to judge) | 0.016 | 0.009 |
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".