Prevalence and Determinants of Glaucoma in Citizens of Qatar Aged 40 Years or Older: A Community-Based Survey
Bibliographic record
Abstract
BACKGROUND: We present the prevalence and determinants of glaucoma among subjects 40 years of age and older in Qatar. MATERIALS AND METHODS: This community-based survey was held in 2009 at 49 randomly selected clusters. Demographic details and history of glaucoma was collected by the nurses. Ophthalmologists evaluated the optic disc and retina using a digital camera housed in a mobile van. Visual field was tested with an automated perimeter, the intraocular pressure with an applanation tonometer and the angle of the anterior chamber by gonioscopy. A panel of glaucoma experts diagnosed subjects with glaucoma. RESULTS: This survey enrolled 3,149 (97.3%) participants. The age- and sex-adjusted prevalence of glaucoma in the population aged 40 years and older was 1.73% (95% confidence intervals [CI] 1.69-1.77). Accordingly, 5,641 individuals in this age group in Qatar would have glaucoma. Chronological age of 60 years and older (Odds ratio [OR] 11.1) and the presence of myopia (OR 1.78) were predictors of glaucoma. Open-angle glaucoma was diagnosed in 44 (65.7%) individuals with glaucoma. In nine (13.4%) and 15 (20.9%) subjects, angle closure glaucoma and other (post-traumatic, pseudoexfoliation) glaucoma were present. Bilateral blindness (vision <3/60) and severe visual impairment (<6/60) were found in four (6%) and three (4.5%) subjects with glaucoma, respectively. Glaucoma was treated in 36 (54%) subjects. CONCLUSIONS: The prevalence of glaucoma among citizens of Qatar aged 40 years and older was 1.71%. Glaucoma was associated with the age of 60 years and older and the presence of myopia.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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; 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".