Availability and nature of cardiac rehabilitation by province in Iran: A 2018 update of ICCPR's global audit
Bibliographic record
Abstract
Background: Cardiac rehabilitation (CR) is scantly available in Iran, although it is the cost-benefit strategy in cardiac patients, It has not been established how CR is delivered within Iran. This study aimed to determine: (a) availability, density and unmet need for CR, and (b) nature of CR services in Iran by province. Materials and Methods: In this cross-sectional sub-study of the global CR audit, program availability was determined through cardiovascular networks. An online survey was then disseminated to these programs in June 2016-2017 which assessed capacity and characteristics; a paper-based survey was disseminated in 2018 to nonresponding and any new programs. CR density and need was computed based on annual incidence of acute myocardial infarction (AMI) in each province. Results: Of the 31 provinces, 12 (38.7%) had CR services. There were 30 programs nationally, all in capital cities; of these, programs in 9 (75.0%) provinces, specifically 22 (73.3%) programs, participated. The national CR density is 1 spot per 7 incident AMI patients/year. Unmet need is greatest in Khuzestan, Tehran and west Azerbaijan, with 44,816 more spots needed/year. Most programs assessed cardiovascular risk factors, and offered comprehensive services, delivered by a multi-disciplinary team, comprised chiefly of nurses, dietitians and cardiologists. Median dose is 14 sessions/program in supervised programs. A third of programs offered home-based services. Conclusion: Where programs do exist in IRAN, they are generally delivered in accordance with guidelines. Therefore, we must increase capacity in CR services in all provinces to improve secondary prevention services.
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How this classification was reachedexpand
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 | 0.030 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".