The validity of recommendations from clinical guidelines: a survival analysis
Bibliographic record
Abstract
BACKGROUND: Clinical guidelines should be updated to maintain their validity. Our aim was to estimate the length of time before recommendations become outdated. METHODS: We used a retrospective cohort design and included recommendations from clinical guidelines developed in the Spanish National Health System clinical guideline program since 2008. We performed a descriptive analysis of references, recommendations and resources used, and a survival analysis of recommendations using the Kaplan-Meier method. RESULTS: We included 113 recommendations from 4 clinical guidelines with a median of 4 years since the most recent search (range 3.9-4.4 yr). We retrieved 39 136 references (range 3343-14 787) using an exhaustive literature search, 668 of which were related to the recommendations in our sample. We identified 69 (10.3%) key references, corresponding to 25 (22.1%) recommendations that required updating. Ninety-two percent (95% confidence interval 86.9-97.0) of the recommendations were valid 1 year after their development. This probability decreased at 2 (85.7%), 3 (81.3%) and 4 years (77.8%). INTERPRETATION: Recommendations quickly become outdated, with 1 out of 5 recommendations being out of date after 3 years. Waiting more than 3 years to review a guideline is potentially too long.
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 | 0.127 | 0.678 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.018 | 0.024 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".