Cost considerations of the new fixed combinations for glaucoma medical therapy
Bibliographic record
Abstract
OBJECTIVE: To compare the costs of the new fixed combinations for glaucoma medical therapy. METHODS: The studied drugs were: Cosopt (5-mL bottle), Combigan (5-mL bottle) and Xalacom (2.5-mL bottle). Five bottles of each drug were obtained from pharmacies, and the medications lot numbers were recorded. To calculate the drop volume, 10 drops and 1 mL of each bottle were weighed with a digital precision scale. Drop volume was calculated by the relation between volume and weight. The cost of each bottle of medication was determined from the average retail price in Canada. The prices were obtained in Canadian dollars (dollars). RESULTS: The drops of Cosopt (39.60 +/- 0.45 microL) were considerably larger than the drops of Combigan (33.75 +/- 0.60 microL) and Xalacom (30.87 +/- 0.37 microL). The average number of drops per millilitre varied from 25.25 +/- 0.29 (Cosopt) to 32.40 +/- 0.39 microL (Xalacom). Combigan presented the lowest daily cost (dollars 0.87 +/- 0.02) followed by Xalacom (dollars 1.09 +/- 0.01) and Cosopt (dollars 1.22 +/- 0.01). The average cost by year varied from dollars 316.75 +/- 5.59 (Combigan) to dollars 445.96 +/- 5.16 (Cosopt), with a total difference of dollars 129.21 per year of treatment. CONCLUSIONS: There was a statistically significant difference in average drop size and cost among the three studied drugs. Combigan presented the lowest daily cost followed by Xalacom and Cosopt.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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, unvalidatedMachine predicted; a candidate call from one teacher head, 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".