Coaching by non-drug prescribing health professionals reduced total cholesterol concentrations in coronary heart disease
Bibliographic record
Abstract
Vale MJ, Jelinek MV, Best JD, et al . Coaching patients On Achieving Cardiovascular Health (COACH): a multicenter randomized trial in patients with coronary heart disease. Arch Intern Med 2003;163:2775–83.[OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] Q In patients with coronary heart disease (CHD), does a 6 month programme of coaching by non-drug prescribing nurses and dietitians reduce total cholesterol (TC) concentrations? ### ![Graphic][5] Design: randomised controlled trial (Coaching patients On Achieving Cardiovascular Health [COACH]). ### ![Graphic][6] Allocation: concealed. ### ![Graphic][7] Blinding: blinded (outcome assessors). ### ![Graphic][8] Follow up period: 6 months. ### ![Graphic][9] Setting: cardiology departments of 6 university teaching hospitals in Melbourne, Australia. ### ![Graphic][10] Patients: 792 patients (mean age 59 y, 77% men) who were admitted to hospital for coronary artery bypass graft surgery; percutaneous coronary intervention; acute myocardial infarction or unstable angina and discharged on medical therapy; or coronary angiography with planned … [1]: {openurl}?query=rft.jtitle%253DArchives%2Bof%2BInternal%2BMedicine%26rft.stitle%253DArch%2BIntern%2BMed%26rft.aulast%253DVale%26rft.auinit1%253DM.%2BJ.%26rft.volume%253D163%26rft.issue%253D22%26rft.spage%253D2775%26rft.epage%253D2783%26rft.atitle%253DCoaching%2Bpatients%2BOn%2BAchieving%2BCardiovascular%2BHealth%2B%2528COACH%2529%253A%2BA%2BMulticenter%2BRandomized%2BTrial%2Bin%2BPatients%2BWith%2BCoronary%2BHeart%2BDisease%26rft_id%253Dinfo%253Adoi%252F10.1001%252Farchinte.163.22.2775%26rft_id%253Dinfo%253Apmid%252F14662633%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1001/archinte.163.22.2775&link_type=DOI [3]: /lookup/external-ref?access_num=14662633&link_type=MED&atom=%2Febnurs%2F7%2F3%2F81.atom [4]: /lookup/external-ref?access_num=000187007700015&link_type=ISI [5]: /embed/inline-graphic-1.gif [6]: /embed/inline-graphic-2.gif [7]: /embed/inline-graphic-3.gif [8]: /embed/inline-graphic-4.gif [9]: /embed/inline-graphic-5.gif [10]: /embed/inline-graphic-6.gif
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".