Impact of Combination Glaucoma Therapies on β-Blocker Exposure
Bibliographic record
Abstract
PURPOSE: β-adrenergic receptor antagonists (β-blockers) used in the treatment of glaucoma are an often-overlooked source of systemic adverse events. Ophthalmic timolol has been associated with severe systemic adverse events including numerous cases resulting in death. In recent years the number of fixed-dose combination therapies for glaucoma has grown rapidly, and among available combination therapies only the nonselective β-blocker timolol is used as the β-blocker component. METHODS: A population-based study was conducted in Ontario, Canada between January 1, 2001 and December 31, 2012 to assess the shift to combination therapies in the management of glaucoma, and to investigate the impact of this shift on the relative use of selective and nonselective β-blockers in patients with this disease. RESULTS: Between 2001 and 2012 timolol (nonselective β-blocker) use grew at an average annual rate of 2.2% (P<0.0001), whereas betaxolol (selective β-blocker) use declined by 14.1% per year (P<0.0001). These changes in the relative use of betaxolol and timolol coincided with changes in the relative use of combination and single-drug therapies. Over the study period, the use of β-blockers as single-drug therapy decreased by 7.7% annually (P<0.0001). In contrast, the use of combination therapies containing a β-blocker increased by 7.6% annually (P<0.0001). CONCLUSIONS: The introduction of fixed combination glaucoma therapies has been associated with a significant shift to greater use of nonselective β-blockers. In vulnerable older populations, this may have an important impact on patient safety that warrants further study.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".