Recommendation Reversals in Gastroenterology Clinical Practice Guidelines
Bibliographic record
Abstract
Background: Recommendations in clinical practice guidelines (CPGs) may be reversed when evidence emerges to show they are futile or unsafe. In this study, we identified and characterized recommendation reversals in gastroenterology CPGs. Methods: We searched CPGs published by 20 gastroenterology societies from January 1990 to December 2019. We included guidelines which had at least two iterations of the same topic. We defined reversals as when (a) the more recent iteration of a CPG recommends against a specific practice that was previously recommend in an earlier iteration of a CPG from the same body, and (b) the recommendation in the previous iteration of the CPG is not replaced by a new diagnostic or therapeutic recommendation in the more recent iteration of the CPG. The primary outcome was the number of recommendation reversals. Secondary outcomes included the strength of recommendations and quality of evidence cited for reversals. Results: Twenty societies published 1022 CPGs from 1990 to 2019. Our sample for analysis included 129 unique CPGs. There were 11 recommendation reversals from 10 guidelines. New evidence was presented for 10 recommendation reversals. Meta-analyses were cited for two reversals, and randomized controlled trials (RCTs) for seven reversals. Recommendations were stronger after the reversal for three cases, weaker in two cases, and of similar strength in three cases. We were unable to compare recommendation strengths for three reversals. Conclusion: Recommendation reversals in gastroenterology CPGs are uncommon but highlight low value or harmful practices.
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 | 0.218 | 0.711 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.017 | 0.016 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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, 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".