Customized clinical practice guidelines for management of adult cataract in Iran
Bibliographic record
Abstract
PURPOSE: To customize clinical practice guidelines (CPGs) for cataract management in the Iranian population. METHODS: First, four CPGs (American Academy of Ophthalmology 2006 and 2011, Royal College of Ophthalmologists 2010, and Canadian Ophthalmological Society 2008) were selected from a number of available CPGs in the literature for cataract management. All recommendations of these guidelines, together with their references, were studied. Each recommendation was summarized in 4 tables. The first table showed the recommendation itself in clinical question components format along with its level of evidence. The second table contained structured abstracts of supporting articles related to the clinical question with their levels of evidence. The third table included the customized recommendation of the internal group respecting its clinical advantage, cost, and complications. In the fourth table, the internal group their recommendations from 1 to 9 based on the customizing capability of the recommendation (applicability, acceptability, external validity). Finally, customized recommendations were sent one month prior to a consensus session to faculty members of all universities across the country asking for their comments on recommendations. RESULTS: The agreed recommendations were accepted as conclusive while those with no agreement were discussed at the consensus session. Finally, all customized recommendations were codified as 80 recommendations along with their sources and levels of evidence for the Iranian population. CONCLUSION: Customization of CPGs for management of adult cataract for the Iranian population seems to be useful for standardization of referral, diagnosis and treatment of patients.
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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 | 0.046 | 0.202 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| 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; 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".