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Record W4384922546 · doi:10.1093/eurheartj/ehad225

Global perspectives on heart disease rehabilitation and secondary prevention: a scientific statement from the Association of Cardiovascular Nursing and Allied Professions, European Association of Preventive Cardiology, and International Council of Cardiovascular Prevention and Rehabilitation

2023· article· en· W4384922546 on OpenAlexaff
Suzanne Fredericks, Ian Jones, Lis Neubeck, Julie Sanders, Noémi de Stoutz, David R. Thompson, Deepti N Wadhwa, Sherry L. Grace

Bibliographic record

VenueEuropean Heart Journal · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsUniversity Health NetworkToronto Metropolitan UniversityToronto Rehabilitation InstituteYork UniversityUniversity of Toronto
FundersNational Institute for Health and Care Research
KeywordsMedicineRehabilitationDiseaseSecondary preventionQuality of life (healthcare)Global healthDisease burdenIntensive care medicineGerontologyFamily medicinePhysical therapyPublic healthNursingPathologyInternal medicine

Abstract

fetched live from OpenAlex

Cardiovascular disease is a leading cause of death, morbidity, disability, and reduced health-related quality of life, as well as economic burden worldwide, with some 80% of disease burden occurring in the low- and middle-income country (LMIC) settings. With increasing numbers of people living longer with symptomatic disease, the effectiveness and accessibility of secondary preventative and rehabilitative health services have never been more important. Whilst LMICs experience the highest prevalence and mortality rates, the global approach to secondary prevention and cardiac rehabilitation, which mitigates this burden, has traditionally been driven from clinical guidelines emanating from high-income settings. This state-of-the art review provides a contemporary global perspective on cardiac rehabilitation and secondary prevention, contrasting the challenges of and opportunities for high vs. lower income settings. Actionable solutions to overcome system, clinician, programme, and patient level barriers to cardiac rehabilitation access in LMICs are provided.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.066
Threshold uncertainty score0.469

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.037
GPT teacher head0.338
Teacher spread0.300 · 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 teacher head, 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".

Quick stats

Citations74
Published2023
Admission routes1
Has abstractyes

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