Cardiac rehabilitation in low- and middle-income countries: a review on cost and cost-effectiveness
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: By 2030, more than 80% of cardiovascular disease-related deaths and disability-adjusted life years will occur in the 139 low- and middle-income (LMIC) countries. Cardiac rehabilitation (CR) has been demonstrated to be effective and cost-effective mainly based on data from high-income countries. The purpose of this paper was to review the literature for cost and cost-effectiveness data on CR in LMICs. METHODS: MEDLINE (Ovid) and EMBASE (Ovid) electronic databases were searched for CR 'cost' and 'cost-effectiveness' data in LMICs. RESULTS: Five CR publications with cost and cost-effectiveness data from middle-income countries were identified with none from low-income countries. Studies from Brazil demonstrated mean monthly savings of US$190 for CR, with a US$48 increase in a control group with mean costs of US$503 for a 3-month CR program. Mean costs to the public health care system of US$360 and US$540 when paid out-of-pocket were reported for a 3-month CR program in seven Latin American middle-income countries. Cardiac rehabilitation is reported to be cost-effective in both Brazil and Colombia. CONCLUSIONS: Cardiac rehabilitation for patients with heart failure in Brazil and Colombia was estimated to be cost-effective. However, given the limited health care budgets in many LMICs, affordable CR models will need to be developed for LMICs, particularly for low-income countries.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it