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Record W4384938004 · doi:10.1016/j.cjca.2023.07.017

Effect of Exercise Training on Peak Aerobic Power After Heart Transplantation: A Brief Review

2023· review· en· W4384938004 on OpenAlexaffvenue
Stephen Foulkes, Dean Hewitt, Anthony E. Peters, Thomas Schmidt, Nils Reiss, Ken Riess, Sarah Paterson, André La Gerche, Mark J. Haykowsky

Bibliographic record

VenueCanadian Journal of Cardiology · 2023
Typereview
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsNorthern Alberta Institute of TechnologyAlberta HealthUniversity of Alberta
Fundersnot available
KeywordsMedicineAerobic exerciseRehabilitationPhysical therapyAthletesQuality of life (healthcare)Heart failureTransplantationHeart transplantationPhysical medicine and rehabilitationAerobic capacityCardiologyInternal medicineNursing

Abstract

fetched live from OpenAlex

Heart transplantation (HTP) is a life-saving therapy for selected individuals with end-stage refractory heart failure. Despite improvements in quality of life and survival, HTP recipients' peak aerobic power (peak VO 2 ) remains up to 50% lower than age-matched healthy control subjects owing to abnormal cardiovascular and skeletal muscle function. Currently, little is known regarding the effect of exercise training (ET) to improve peak VO 2 after HTP. This brief review aims to summarise existing evidence regarding the role of ET on peak VO 2 and its determinants, highlights the upper limits of endurance performance in highly trained HTP athletes, and identifies areas for future HTP exercise rehabilitation research.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.057
GPT teacher head0.373
Teacher spread0.316 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations6
Published2023
Admission routes2
Has abstractno

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