Rigorous Method to Assess Quality and Generalizability of Clinical Practice Guidelines
Bibliographic record
Abstract
Rigorous Method to Assess Quality and Generalizability of Clinical Practice GuidelinesClinical practice guidelines (CPGs) are important tools for clinical decision-making in modern health care. 1 The introduction of CPGs into clinical practice has revolutionized the way clinicians care for patients, by allowing them to integrate principles of evidencebased medicine with patient-specific factors and clinical judgment. 2Through dissemination of specific recommendations, CPGs attempt to standardize care according to established best practices.They also provide a means for monitoring prescriber practices at both individual and institutional levels. 3However, certain aspects of CPGs may, directly or indirectly, have negative effects on care. 4For example, use of expert opinion, lack of a stringent review process, or direct financial sponsorship may compromise the validity of a published guideline.A recent Point Counterpoint debate in the CJHP raised many points both supporting and refuting the use of CPGs in clinical practice. 5,6With this discussion as background, our aim was to demonstrate a process of rigorous guideline appraisal by using a standardized method to assess the recently published Joint National Committee hypertension guidelines. 7he hypertension CPG was appraised using the Appraisal of Guidelines for Research and Evaluation II (AGREE II) instrument. 8Application of this tool involves ranking 23 items within 6 domains and completing additional categories for "Overall Assessment" and "Recommendation".For the 23 items and the overall assessment, the appraisers were asked to assign a rank between 1 (strongly disagree) and 7 (strongly agree).For example, the first item under the domain "scope and purpose" states, "The overall objective(s) of the guideline is (are) specifically described", and appraisers used the 7-point scale to rate how well the CPG fulfilled this criterion.Standardized domain scores were subsequently calculated according to the formula provided in AGREE II. 8 Domain scores are reported as percentages, on a scale from 0 to 100%, with 100% being the highest score possible.For the final recommendation, appraisers were asked to state whether or not they would recommend using the guideline, or if they would recommend using the guideline with required modifications.The CPG was appraised independently by 6 investigators (the authors of this letter).Upon completion, all appraisals were forwarded to one investigator (K.J.W.),
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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 | 0.553 | 0.824 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.025 | 0.021 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".