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Status of cardiac rehabilitation services in low- and middle-income countries

2013· article· en· W2335172800 on OpenAlexaff
Shamila Shanmugasegaram

Bibliographic record

VenueEuropean Heart Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsYork University
Fundersnot available
KeywordsMedicineReferralRehabilitationDeveloping countryGovernment (linguistics)Low and middle income countriesFamily medicinePhysical therapyEconomic growth

Abstract

fetched live from OpenAlex

Purpose: Despite the benefits of cardiac rehabilitation (CR), there is lack of data on the availability, characteristics, and barriers to feasible CR services in low- and middle-income countries (LMIC). The objectives of this study were to assess the availability and characteristics of CR services and identify barriers to CR implementation and participation in LMIC. Methods: Sixty national cardiac societies, heart associations, and heart foundations and 100 cardiac specialists from LMIC throughout the World Health Organization regions were asked whether CR services were provided to adult cardiac patients at any institute in their countries. Responses were received from 40 LMIC. Of these, cardiac specialists from 23 countries that offered CR services completed a questionnaire which examined the characteristics of the CR services provided by the facility, patients' barriers to CR participation, and approaches that could transcend barriers to participation in CR. Cardiac specialists from 10 countries that did not offer CR services completed another questionnaire which assessed barriers to successful implementation of a CR programme and feasible components for sustainable CR. Results: CR services were available in 26 LMIC (questionnaire non-response=3 LMIC). CR components included exercise training (100%), healthy diet advice (100%), psychological support (95.7%), and smoking cessation (91.3%). Funding sources to operate the CR programmes were private insurance (4.5%), private (40.9%), central government (50.0%), and mixed (22.7%). Cardiac specialists reported "distance to the facility," "costs," and "lack of support/referral from doctor" as the leading barriers for CR participation for patients. Many of the respondents (68.2%) were in favour of a decentralized health care system and listed automatic referral and increasing cardiac specialists' and patients' knowledge regarding CR to transcend barriers. CR services were not available in 14 LMIC (questionnaire non-response=4 LMIC). The most endorsed barriers for successful implementation of a CR programme were "lack of economic resources," "lack of qualified personnel," "lack of equipment," and "rehabilitation is not supported by health policies." Cardiac specialists listed patient education, smoking cessation, and counselling regarding medications and diet as feasible components for sustainable CR in these countries. Conclusion: The results suggest the need to increase the availability and accessibility of cost-effective and feasible CR services in low-resource settings to assist in reducing the rate of premature mortality in patients with heart disease.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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.

Opus teacher head0.017
GPT teacher head0.310
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations4
Published2013
Admission routes1
Has abstractyes

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