Characteristics of cardiac rehabilitation programs in Latin America and the Caribbean, and estimation of capacity and needs in the region
Bibliographic record
Abstract
Abstract Background Cardiac rehabilitation (CR) is an established model of cardiovascular (CV) prevention that has proven benefits. Availability, characteristics and need of CR programs in Latin-American and Caribbean (LAC) countries remains poorly characterized. This study aims to establish the availability, capacity, density and aspects of CR delivery in LAC. Methods A cross-sectional survey was administered to CR programs in 24 LAC. Local CV organizations and societies identified CR programs. Characteristics of individual CR program were reviewed including: funding sources, core components, healthcare providers, and dose (number of sessions per weeks X total number of weeks) of CR. National CR capacity (median number of patients a program could serve per year X number of programs per country), density (Ischemic Heart Disease [IHD] incidence per year/ national capacity), need (IHD incidence per year- national capacity) and occupancy (median number patients program served per year/national capacity) were computed based on survey responses. Results At least one CR program was identified per LAC country (total 255 programs across 24 countries). Data was collected in 20 of the 24 countries. Responses were received from 139/255 programs (median program response rate=55%; Table 1). Over 50% (n=73) of programs were funded by multiple sources (government, hospital/clinic, private health insurance); Self-payment was reported by 63% programs, in which 24 (33.8%) patients paid over 50% of the cost. Guideline-indicated conditions were accepted in 77% or more programs. Physiotherapists (n=106, 76.3%), cardiologists (n=105, 75.5%) and dietitians (n=79, 56.8%) were the most common healthcare providers on CR teams. Regionally, programs offered 9 (IQR = 8–10) core components (patient education, exercise prescription and initial assessment delivered by nearly all programs). Median CR was 36 (IQR = 24–56) sessions/patient. Twenty-seven (20.9%) programs offered alternative CR models (e.g., home or community-based and hybrid models). Median national capacity was 500 CR spots/country (IQR= 200–2300). Regional density was 1 CR spot per 24 incident IHD patients per year. Greatest need in absolute terms for CR was observed in Brazil, Dominican Republic and Mexico (all with >150,000 spots needed per year to manage incident IHD patients; Table 1). Occupancy ranged from over 100% in Colombia to 15% in Chile (median=60%, IQR = 32%–81%), Table 1. Conclusion In LAC countries, there is very limited capacity to meet the need for CR. Nature of CR services varied regionally. Funding Acknowledgement Type of funding source: None
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".