P162 Rigor of Development Of Clinical Practice Guidelines In Dentistry
Bibliographic record
Abstract
Background Some reports have shown the varying quality of clinical practice guidelines (CPGs), but this aspect has not been explored in the field of dentistry. With a growing number of guidelines in dentistry being published every year, and an increase in dentist’s interest to inform their practice with such documents, it is relevant to learn whether their development process has been appropriate. Objectives To assess the rigour of development of evidence-based CPG’s in dentistry. Methods We searched Pubmed, EMBASE, and the National Guideline Clearinghouse among others. We included all evidence-based CPGs with explicit clinical recommendations, published since 2004 in English. Two independent evaluators assessed the guidelines using the “Rigour of development” domain of AGREE II. Results A total of 73 CPGs were assessed. The mean score of the rigour of development domain across all guidelines was 34.54% (SD=19.18%). The items that scored the lowest were the description of a procedure for updating the guideline and the strengths and limitations of the evidence; whereas the items best rated were the explicit link between the evidence supporting the recommendations and the pondering of benefits, harms and risk for formulating the recommendations. Discussion CPGs aim to support clinical decision-making, and thus they can impact the quality of health-care. Thus, the rigour in their development is a relevant aspect to consider. There is a lot of room for improvement in this regard in CPGs in dentistry. Implications for Guideline Developers Guideline developers in dentistry should enhance the methodology when creating new guidelines or updating existing ones.
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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 | 0.574 | 0.885 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".