HOPE Study Impact on ACE Inhibitors Use
Bibliographic record
Abstract
BACKGROUND: Angiotensin-converting enzyme (ACE) inhibitors are used to treat cardiovascular diseases, major causes of death in Canada. The HOPE (Heart Outcomes Prevention Evaluation) study showed that ramipril benefits patients at high risk for cardiovascular disease. We analyzed ACE inhibitor use and costs in Canada before and after publication of HOPE. METHODS: We obtained pharmacy and hospital sales data for 1985-2001 from IMS Canada for all ACE inhibitors (Anatomical Therapeutic Category code C09A0) and for the 3 largest provinces (i.e., British Columbia, Quebec, Ontario). Prescription numbers, total costs, cost/prescription, and market share of individual ACE inhibitors were plotted over time and analyzed using regression. Canadian dollars were used to report costs. RESULTS: We examined 10 drugs; captopril was the first, introduced in 1985. Overall, prescriptions increased consistently from 356 000 in 1985 to 11.5 million in 2001, representing an annual increase of 660 000 (y = 661 410x-510 360; r(2) = 0.99). Total costs increased linearly from 1985 (14.5 million US dollars) to 2001 (513 million US dollars): Y = 29.3.10(6)x - 29.9.10(6); r(2) = 0.99. Provincial utilization patterns were also similar. Ramipril's national use increased dramatically from 1999 (822 000 prescriptions, 9.2% of all ACE inhibitors) to 2001 (3.8 million, 32.8% of all ACE inhibitors). National costs for ramipril increased exponentially (y = 1.08e(0.6248x)) to a total of 157 million US dollars in 2001, with the 3 major provinces accounting for 78.9%. Costs per prescription followed no observable trend (range 39.45-46.20 US dollars). CONCLUSIONS: The number of prescriptions and the total cost of ACE inhibitors increased over the period studied. Ramipril use increased in concert with publication of the HOPE trial, while the growth rates of other ACE inhibitors remained constant.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".