Bibliographic record
Abstract
Heart failure is a worldwide health-care problem, recently highlighted in a report from the Global Heart Failure Awareness Programme of the Heart Failure Association of the European Society of Cardiology. 1 For nearly all countries for which there are data, heart failure consumes 1-2% of expenditure, chiefly related to the costs of hospitalization.Despite differences in heart failure aetiology and demographics in high-and middle-income countries, the need for accurate and speedy diagnosis, access to life-saving therapies, and appropriate support for individuals and their families is universal.International guidelines strongly support disease management programmes, 2,3 including follow-up shortly after discharge from hospital and in the high-risk period (the first 3 months) thereafter.The most recent edition of the American College of Cardiology/American Heart Association guidelines suggest that a follow-up visit within 7-14 days and/or a telephone follow-up within 3 days of hospital discharge are 'reasonable', with a B grading for level of evidence and a IIa class of recommendation.Standards have also been suggested for disease management programmes, with the goal of providing a seamless system of care across primary and hospital care.4 Patient education to support self-monitoring and self-care, where appropriate, is seen as central to any such programme.However, the evidence base for such recommendations is largely confined to randomized trials from high-income countries.In a recent meta-analysis of disease management programmes for heart failure, including 46 studies, 5 30 (65%) were based in the USA or Canada, nine in Europe, six in Australia or New Zealand, and only one came from a middle-income country (Argentina).Despite international guidelines, the relevance of a randomized clinical trial (RCT) to routine practice is often questioned.This is particularly the case when the RCT is based in a health-care system that is constructed (and funded) in a very different way from that found in the geography considering how to organize heart failure services.Reimbursement authorities and health-care insurance companies frequently question the relevance of studies from other geographies.Of course, the biology of the heart failure is unlikely to be different, but the impact of a health-care intervention on the pattern of health-care utilization may be very different.Where the quality or relevance of the
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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 | 0.071 | 0.223 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.019 | 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".