Nature of Cardiac Rehabilitation Around the Globe
Bibliographic record
Abstract
BACKGROUND: Cardiac rehabilitation (CR) is a clinically-effective but complex model of care. The purpose of this study was to characterize the nature of CR programs around the world, in relation to guideline recommendations, and compare this by World Health Organization (WHO) region. METHODS: In this cross-sectional study, a piloted survey was administered online to CR programs globally. Cardiac associations and local champions facilitated program identification. Quality (benchmark of ≥ 75% of programs in a given country meeting each of 20 indicators) was ranked. Results were compared by WHO region using generalized linear mixed models. FINDINGS: 111/203 (54.7%) countries in the world offer CR; data were collected in 93 (83.8%; N = 1082 surveys, 32.1% program response rate). The most commonly-accepted indications were: myocardial infarction (n = 832, 97.4%), percutaneous coronary intervention (n = 820, 96.1%; 0.10), and coronary artery bypass surgery (n = 817, 95.8%). Most programs were led by physicians (n = 680; 69.1%). The most common CR providers (mean = 5.9 ± 2.8/program) were: nurses (n = 816, 88.1%; low in Africa, p < 0.001), dietitians (n = 739, 80.2%), and physiotherapists (n = 733, 79.3%). The most commonly-offered core components (mean = 8.7 ± 1.9 program) were: initial assessment (n = 939, 98.8%; most commonly for hypertension, tobacco, and physical inactivity), risk factor management (n = 928, 98.2%), patient education (n = 895, 96.9%), and exercise (n = 898, 94.3%; lower in Western Pacific, p < 0.01). All regions met ≥ 16/20 quality indicators, but quality was < 75% for tobacco cessation and return-to-work counseling (lower in Americas, p = < 0.05). INTERPRETATION: This first-ever survey of CR around the globe suggests CR quality is high. However, there is significant regional variation, which could impact patient outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".