Prevalence of Glaucoma in Hospitalized Older Adults with Alzheimer's Disease
Bibliographic record
Abstract
OBJECTIVE: To determine the prevalence of glaucoma in older adults with dementia of the alzheimer's type (DAT). METHODS: retrospective chart review: the prevalence of glaucoma was determined in older adults with a diagnosis of DAT or mixed dementia (DAT with vascular contribution) admitted to the geriatric and neurology units of the Centre hospitalier de l'université de Montréal and the hôpital Maisonneuve-rosemont between april 2008 and april 2009 (n=220; DAT group). they were matched for age and date of hospitalisation to the first 220 individuals without dementia (control group) recruited from other medical units in the same hospitals: gastroenterology, internal medicine or cardiology. a diagnosis of glaucoma was deemed positive if recorded in the chart or if there was a medication compatible with this diagnosis. Chi-square tests were used for between-group comparisons. RESULTS: Subjects' age ranged from 66 to 101 years. the prevalence of glaucoma was 6.8% in our study population (n=30/440). glaucoma was significantly more prevalent in the DAT group (n= 21; 9.5%) than in the control group (n= 9; 4.1%) [χ₁² = 5.15; p = 0.023]. CONCLUSIONS: the prevalence of glaucoma was higher in a group of older adults with DAT than in a comparable control group. these results underscore the importance of providing regular eyecare for persons affected by DAT.
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 | 0.002 |
| 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".