Pseudoexfoliation in the Reykjavik Eye Study: prevalence and related ophthalmological variables
Bibliographic record
Abstract
PURPOSE: To examine the age and sex-specific prevalence of pseudoexfoliation syndrome (PEX) and its relationship with some ophthalmological variables. METHODS: We carried out a population-based study using a random sample taken from the national population census for citizens of Reykjavik, aged > or = 50 years. A total of 1045 individuals participated in all parts of the study. Pseudoexfoliation was established by slit-lamp examination with a maximally dilated pupil carried out by two experienced ophthalmologists, who were masked to one another's results except in cases of disagreement where they had to reach a consensus. RESULTS: In all, 108 (10.7%) persons were found to have PEX in at least one eye. Prevalence increased from 2.5% in those aged 50-59 years to 40.6% in those aged > or = 80 years. Women were more frequently affected than men (12.3% versus 8.7%). This difference remained statistically significant after controlling for the effect of age (p < 0.001). Eyes with PEX were found to have higher intraocular pressure (IOP) than eyes without PEX (p < 0.05). However, PEX was not found to be related to central corneal thickness, anterior chamber depth, lens thickness, nuclear lens opacifications or optic disc morphology in a multivariate model. CONCLUSIONS: Pseudoexfoliation is an age-related phenomenon commonly found in Iceland. It is more commonly found in women than in men and is associated with elevated IOP.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 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) | 0.001 | 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".