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Record W3092184013 · doi:10.1016/j.cjco.2020.10.004

Cardiac Rehabilitation Is Associated With Improved Long-Term Outcomes After Coronary Artery Bypass Grafting

2020· article· en· W3092184013 on OpenAlexafffundabout
Reena Karkhanis, Harindra C. Wijeysundera, Derrick Y. Tam, Paul Oh, David A. Alter, Bing Yu, Alex Kiss, Stephen E. Fremes

Bibliographic record

VenueCJC Open · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsHealth Sciences CentreInstitute for Clinical Evaluative SciencesSunnybrook Health Science CentreToronto Rehabilitation InstituteUniversity Health NetworkUniversity of Toronto
FundersCorHealth OntarioUniversity of TorontoOntario Ministry of Health and Long-Term CareHeart and Stroke Foundation of CanadaInstitute for Clinical Evaluative Sciences
KeywordsBypass graftingArteryRehabilitationCardiologyInternal medicineMedicineTerm (time)GraftingPhysical therapyMaterials science

Abstract

fetched live from OpenAlex

BACKGROUND: Although cardiac rehabilitation (CR) has proven to have short- and mid-term benefit in treatment of coronary artery disease, its long-term benefit in patients who have undergone coronary artery bypass grafting (CABG) is less certain. Our objective was to examine the late outcomes of patients who attended CR within the first year after CABG. METHODS: Adult CABG patients referred to Toronto Rehabilitation Institute (CR group: were referred and attended at least 1 session; No-CR group: were referred but did not attend) between January 1996 and September 2008 were identified through linkages with clinical and provincial administrative databases for comorbidities and outcome ascertainment. The primary outcome was a composite of all-cause mortality, acute myocardial infarction, stroke or repeat revascularization (major adverse cardiac and cerebrovascular events [MACCE]). The secondary outcome was all-cause mortality. Multivariable Cox proportional hazard models were used to assess the CR treatment effect, adjusting for baseline characteristics. RESULTS: < 0.0001), as compared with the No-CR group. CONCLUSIONS: There was a reduction in MACCE and late mortality associated with CR attendance, highlighting the importance of patient referral and participation in CR after CABG.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.006
Threshold uncertainty score0.623

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.025
GPT teacher head0.336
Teacher spread0.311 · 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

Citations7
Published2020
Admission routes3
Has abstractyes

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