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Record W7133017302

Cardiac rehabilitation for aerobic training in individuals post-stroke

2007· dissertation· W7133017302 on OpenAlexaboutno aff
Valerie Deanne Closson

Bibliographic record

VenueTSpace · 2007
Typedissertation
Language
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsRehabilitationAerobic exercisePopulationAerobic capacityWork (physics)Cardiac function curveTraining (meteorology)
DOInot available

Abstract

fetched live from OpenAlex

Aerobic capacity is often compromised in the post-stroke population, which can limit function and potentially increase subsequent stroke risk. In spite of the possible benefits of aerobic training in this population, appropriate programs are rare. The purpose of this thesis was to investigate the potential use of an existing program, cardiac rehabilitation, to provide post-stroke aerobic training. The potential availability of cardiac rehabilitation for this population was investigated using a survey of cardiac rehabilitation facilities in Ontario (n=47). Over half of respondents accepted some individuals post-stroke; however, potential barriers appeared to exist that limited enrollment. The potential effects of cardiac rehabilitation were investigated by enrolling individuals (n=27) into an existing cardiac rehabilitation program. Participation resulted in an improvement in aerobic capacity (32% increase in VO2 peak) and functional walking (11% increase in 6 minute walk time). This work has important implications for the health and function of individuals post-stroke.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.022
GPT teacher head0.370
Teacher spread0.348 · 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".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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