An evaluation of cataract surgery clinical practice guidelines
Bibliographic record
Abstract
PURPOSE: This study used the Appraisal of Guidelines for Research and Evaluation (AGREE) II Instrument to evaluate the methodological quality of clinical practice guidelines (CPG) published by the American Academy of Ophthalmology (AAO), Canadian Ophthalmological Society (COS) and Royal College of Ophthalmologists (RCO) for the management of cataract in adults. STUDY DESIGN: An evaluation of the AAO, COS and RCO CPGs using a reliable and validated instrument. METHODS: Four evaluators independently appraised the three CPGs using the AGREE II Instrument, which covers six domains (Scope and Purpose, Stakeholder Involvement, Rigour of Development, Clarity of Presentation, Applicability and Editorial Independence). The AGREE II includes an Overall Assessment summarising guideline methodological rigour across all domains, using a 7-point scale where perfect adherence equals a score of 7. RESULTS: Scores ranged from 36% to 75% for the AAO guideline; 45% to 94% for the COS guideline and 23% to 85% for the RCO guideline. Intraclass correlation coefficients for the reliability of mean scores for the AAO, COS, and RCO were 0.78, 0.74 and 0.80; 95% CIs (0.60 to 0.90), (0.45 to 0.88) and (0.53 to 0.91), respectively. The strongest domains were Scope and Purpose (COS, RCO), Clarity of Presentation (COS, RCO) and Editorial Independence (AAO, COS). The weakest were Stakeholder Involvement (AAO), Applicability (AAO, COS) and Editorial Independence (RCO). CONCLUSIONS: Cataract surgery practice guidelines can be improved by targeting stakeholder involvement, applicability and editorial independence.
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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 | 0.423 | 0.675 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.017 | 0.014 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".