How Evidence-Based Are Publications in Clinical Ophthalmic Journals?
Bibliographic record
Abstract
PURPOSE: To evaluate the methodological quality and level of evidence of publications in four leading general clinical ophthalmology journals. METHODS: All 1919 articles published in the American Journal of Ophthalmology, Archives of Ophthalmology, British Journal of Ophthalmology, and Ophthalmology in 2004 were reviewed. The methodological rigor and the level of evidence in the articles were rated according to the McMaster Hedges Project criteria and the Oxford Centre for Evidence-Based Medicine levels of evidence. RESULTS: Overall, 196 (24.4%) of the 804 publications that were included for assessment met the Hedges criteria. Articles on economics evaluation and those on prognosis achieved the highest passing rate, with 80.0% and 74.4% of articles, respectively, meeting the Hedges criteria. Publications on etiology, diagnosis, and treatment fared less well, with respective passing rates of 28.3%, 20.2%, and 14.7%. Published systematic reviews and randomized controlled trials were uncommon in the ophthalmic literature, at least in these four journals during 2004. According to the Oxford criteria, 57.6% of the articles were classified as level 4 evidence compared with 18.1% classified as level 1. Articles on prognosis had the highest proportion (43.0%) rated as level 1 evidence. Generally, articles that reached the Hedges threshold were rated higher on the level-of-evidence scale (Spermans rho = 0.73; P < 0.001). CONCLUSIONS: The methodological quality of publications in the clinical ophthalmic literature was comparable to that in the literature of other specialties. There was substantial heterogeneity in quality between different types of articles. Future methodological improvements should focus on the areas identified as having the largest deficiencies.
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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 | 0.360 | 0.842 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.055 | 0.042 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.017 | 0.012 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".