Secondary prevention programmes for coronary heart disease: a meta-regression showing the merits of shorter, generalist, primary care-based interventions
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: The aim of this study was to determine which programme characteristics influence the effectiveness of secondary prevention programmes for Coronary Heart Disease. DESIGN: The study follows a meta-regression design. METHODS: We conducted a meta-regression within a systematic review of randomized trials comparing secondary prevention programmes versus usual care. The primary outcome was all-cause mortality. Studies were identified by searching multiple electronic databases, bibliographies of published studies, contact with experts, and references provided by the United States Centers for Medicare and Medicaid Services. Primary authors of all relevant trials were surveyed for detailed information on programme characteristics. Forty-six unique trials were identified (18 821 patients). The pooled all-cause mortality risk ratio (RR) for programmes was 0.87 [95% confidence interval (CI) 0.79-0.97]. Programmes containing less than 10 h of patient contact with health professionals reduced all-cause mortality (RR 0.80, 95% CI 0.68-0.95) as effectively as programmes with more contact time. Programmes provided in general practice settings were effective at reducing all-cause mortality (RR 0.76, 95% CI 0.63-0.92) and compared favourably with the effectiveness of hospital-based programmes. Other characteristics, including specialist versus generalist provision, did not appreciably impact programme effectiveness. CONCLUSIONS: Shorter secondary prevention programmes, those based in general practice, and those staffed by generalists are at least as effective in reducing all cause mortality in patients with coronary heart disease as longer programmes, hospital-based programmes, and programmes staffed by specialists.
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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 | 0.028 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.036 |
| 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 | 0.001 |
| 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 it