Growth in use of statins after trials is not targeted to most appropriate patients
Bibliographic record
Abstract
OBJECTIVE: To determine whether growth in the use of lipid-lowering drugs after publication of studies in the primary and secondary prevention of coronary heart disease is in the population in which benefit was established, particularly middle-aged men. METHODS: We performed a series of pharmacoepidemiologic surveys of community prescribing in Ireland over 4 years. RESULTS: Nationally, the use of lipid-lowering drugs (92% statins) increased approximately fourfold from 1994 to 1998. In the Eastern Health Board region, the number of monthly recipients increased from 447 in April 1994 to 3530 in March 1998. Although use increased steadily after publication of Scandinavian Simvastatin Survival Study (4S) and West of Scotland Coronary Prevention Study (WOSCOPS) in 1994 and 1995, respectively, this occurred to a greater extent in women. However, after the Cholesterol and Recurrent Events (CARE) study in 1996 and subsequent recommendations that targeted statin use, particularly in men from 35 to 69 years old, there was a relatively greater increase in that population but, at 2.3%, it was well short of the target population of 5.8%. More women than men older than 65 years are receiving statins. The 10-mg dosage (a fourth or half that used in studies) is the most frequently dispensed. CONCLUSION: The use of statins, although rising rapidly, is below targets and was initially not directed at the population likely to benefit most or in the recommended dosage. Consequently, the benefits projected from clinical trials may not be seen in clinical practice.
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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 | 0.035 | 0.164 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".