The Extensive Lifestyle Management Intervention (ELMI) following cardiac rehabilitation trial
Bibliographic record
Abstract
AIM: Previous studies have reported lifestyle and risk factor deterioration following completion of a cardiac rehabilitation program (CRP). We report the results of a one-year Extensive Lifestyle Management Intervention (ELMI) aimed at preventing these adverse changes. METHODS AND RESULTS: A total of 302 men and women with ischaemic heart disease were recruited following completion of a CRP and randomized to either the ELMI (consisting of exercise sessions, telephone follow-ups and risk factor and lifestyle counselling) or usual care. The primary outcome was global cardiovascular risk using the Framingham and Procam risk scores. Secondary outcomes included risk factors and lifestyle behaviours. Baseline characteristics were similar between the two groups. Adherence to the ELMI was high. There was a non-significant trend in favour of the ELMI between for both the Framingham (6.6+/-3.1 to 6.2+/-2.9 vs 6.6+/-3.2 to 6.7+/-3.2, P=0.138) and Procam (20.0+/-20.0 to 20.6+/-19.5 vs 19.1+/-18.7 to 21.8+/-19.1, P=0.089) scores. There were no differences in secondary outcomes. CONCLUSIONS: A one-year multi-factorial post-CRP intervention results in modest, non-significant benefits to global risk compared to usual care. The absence of deterioration in the usual care group may be due to improved practices in usual care.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".