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Record W2014198136 · doi:10.1155/2012/959120

Reduced Cardiorespiratory Fitness after Stroke: Biological Consequences and Exercise-Induced Adaptations

2011· article· en· W2014198136 on OpenAlexaff
Sandra A. Billinger, Eileen Coughenour, Marilyn MacKay-Lyons, Frederick M. Ivey

Bibliographic record

VenueStroke Research and Treatment · 2011
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCardiorespiratory fitnessMedicineStroke (engine)PopulationPhysical medicine and rehabilitationPhysical therapyPhysical fitnessPsychological interventionGerontologyPsychiatry

Abstract

fetched live from OpenAlex

Evidence from several studies consistently shows decline in cardiorespiratory (CR) fitness and physical function after disabling stroke. The broader implications of such a decline to general health may be partially understood through negative poststroke physiologic adaptations such as unilateral muscle fiber type shifts, impaired hemodynamic function, and decrements in systemic metabolic status. These physiologic changes also interrelate with reductions in activities of daily living (ADLs), community ambulation, and exercise tolerance, causing a perpetual cycle of worsening disability and deteriorating health. Fortunately, initial evidence suggests that stroke participants retain the capacity to adapt physiologically to an exercise training stimulus. However, despite this evidence, exercise as a therapeutic intervention continues to be clinically underutilized in the general stroke population. Far more research is needed to fully comprehend the consequences of and remedies for CR fitness impairments after stroke. The purpose of this brief review is to describe some of what is currently known about the physiological consequences of CR fitness decline after stroke. Additionally, there is an overview of the evidence supporting exercise interventions for improving CR fitness, and associated aspects of general health in this population.

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 score0.271
Threshold uncertainty score0.443

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.186
GPT teacher head0.375
Teacher spread0.189 · 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

Citations188
Published2011
Admission routes1
Has abstractyes

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