The impact of ICCPR's Global Audit of Cardiac Rehabilitation: where are we now and where do we need to go?
Bibliographic record
Abstract
Despite the global epidemic of cardiovascular disease and the well-established mitigating benefits of cardiovascular rehabilitation (CR), availability is known to be grossly insufficient, and little was known about the nature of services delivered in resource-poor settings where it is needed most. Indeed, this had not been quantified before the International Council of Cardiovascular Prevention and Rehabilitation's (ICCPR) 2017 Global Audit, published in volume 13 of eClinicalMedicine.1,2 This commentary will: (1) summarize the key findings of the Global Audit, (2) actions taken to address identified issues, (3) what is known about current CR availability and the nature of delivered services globally, and finally (4) consider open questions and future directions to achieve change.
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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 | 0.043 | 0.173 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.013 | 0.017 |
| Insufficient payload (model declined to judge) | 0.005 | 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".