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Record W6893469821 · doi:10.5281/zenodo.2537148

COMPARING CARDIAC REHABILITATION GUIDELINES

2019· article· en· W6893469821 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Effects of Exercise
Canadian institutionsnot available
Fundersnot available
KeywordsGuidelineRehabilitationAerobic exerciseTest (biology)Quality of life (healthcare)MEDLINE

Abstract

fetched live from OpenAlex

<strong>Objectives:</strong> Comparing Cardiac Rehabilitation Guidelines. <strong>Method</strong>: guidelines were searched alone and with combination with different nations in English language. To review information about the exercises modes, exercise intensity, testing, and monitoring of patients. <strong>Results</strong>: the United States, Canadian, United Kingdome, and European guidelines all have common components and have differences in the exercises modes and intensity. The United States, Canada, and European guideline suggest aerobic training should progressing from moderate to vigorous intensity through the program, these guidelines also suggest resistance training combined with the aerobic training to improve quality of life. The United Kingdome recommends lower intensity program and less ECG monitoring. Although the other guidelines recommend ECG exercises stress test for functional capacity assessment. <strong>Conclusion</strong>: guideline for the Mediterranean region should be assembled and after reviewing these guidelines, it is recommended to use ECG monitoring for functional assessment. Managing the risk factors is recommended in all the guidelines. Aerobic endurance training is recommended to advance from moderate to high intensity exercises combined with resistance training. These characteristics are safe for the patients and also showed improvements in patient’s health and quality of life.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.309
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0030.016

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 head0.038
GPT teacher head0.281
Teacher spread0.244 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations2
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)Same topicCardiovascular Effects of ExerciseFrench-language works237,207