Association Between Glaucoma, Glaucoma Therapies, and Erectile Dysfunction
Bibliographic record
Abstract
PURPOSE: To examine the association between (1) glaucoma and erectile dysfunction (ED) and (2) topical β-blocker (BB) use and ED. METHODS: A comprehensive, province-wide database of physician visits and diagnoses and prescription drug dispensing was used to identify cases of ED (1380) and find corresponding controls (13,800). A conditional logistic regression model was used to estimate rate ratios for 2 main exposures: (1) diagnosis of glaucoma and (2) use of a prescription of a topical BB before the index date. A variety of risk factors were adjusted for. RESULTS: Cases were more likely to have coronary artery disease, chronic obstructive pulmonary disease, and diabetes. A crude rate ratio of the current diagnosis of ED in a population with at least 2 separate diagnoses of glaucoma was 1.34 and when adjusted for a number of variables (including oral BB use), this ratio was 1.37 [95% confidence interval (CI), 1.06-1.76]. Use of topical BB in the 30 days before the diagnosis of ED did not have a significant association with a diagnosis of ED, with crude and adjusted rate ratios of 1.05 and 1.10, respectively (95% CI, 0.61-1.99). Topical ocular prostaglandin use was also not associated with ED, with crude and adjusted rate ratios of 0.96 and 0.93, respectively (95% CI, 0.57-1.53). CONCLUSIONS: Our results confirmed an association between ED and glaucoma that cannot be attributed to topical BB use. Given that most cardiovascular and metabolic risk factors were adjusted for, further research in this area will be necessary to elucidate the nature of this association and potential causation.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.003 | 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".