Clinical Survey of Pseudoexfoliation Syndrome
Bibliographic record
Abstract
OBJECTIVE: Assess the prevalence of PEX and identify the associated glaucoma and cataract. STUDY DESIGN & METHODOLOGY: A sample of 6,650 patients (age ≥40 years) that attended the single ophthalmic private clinic for different complaints, for five years (January 2013 until January 2018), those diagnosed with PEX enrolled in this study, with a total number of 296 patients. RESULTS: 14 (4.7%) patients with age from 40-49 years, 54(18.2%) from 50-59 years, 102 (34.5%) from 60-69 years, and 126(42.6%) equal or older than 70 years. Close sex frequencies were observed, with 153(51.7%) males, and 143(48.3%) females. In the current study, the prevalence of PEX was 4.45% (95% confidence interval (CI), 3.98-4.97). There was a statistically insignificant relationship between PEG or advanced glaucoma with age or sex, but cataract was significantly associated with older age and male sex. CONCLUSION: The prevalence of Pseudoexfoliation syndrome was 4.45%, with a sharp increase after the age of 50 years. Although the prevalence of PEG and advanced glaucoma increased with age, it was neither statistically associated with it, nor with sex. Cataract prevalence was associated with increased age and male sex.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".