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Record W2143204087 · doi:10.3138/ptc.58.4.259

Aerobic Testing and Training for Persons with Multiple Sclerosis: A Review with Clinical Recommendations

2006· review· en· W2143204087 on OpenAlexvenueno aff
Jo-Anne Howe, Michelle A. Gomperts

Bibliographic record

VenuePhysiotherapy Canada · 2006
Typereview
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAerobic exerciseMedicinePhysical therapyDeconditioningQuality of life (healthcare)DiseasePsychosocialAerobic capacityPhysical medicine and rehabilitationNursingPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Purpose: In this article, we review the evidence for aerobic training in persons with multiple sclerosis (MS). The effects of aerobic training on enhancing cardiovascular fitness, muscle strength, and health-related quality of life (HRQOL) and reducing risk factors for cardiovascular disease are summarized. Clinical considerations and recommendations for aerobic testing and training are also presented. Summary of Key Points: Persons with MS may limit their participation in physical activity, predisposing them to deconditioning and additional disability, previously attributed to the disease process itself. However, individuals with mild to moderate levels of disability who participate in aerobic training can improve aerobic fitness, muscle strength, and HRQOL and reduce the risk factors for cardiovascular disease. Aerobic testing and training are safe for these patients provided that they are adequately screened and managed for fatigue, dysautonomia, and thermosensitivity. These historical concerns should not preclude active participation in aerobic training as current evidence suggests that the benefits outweigh the risks. Conclusions: To minimize activity limitations and participation restrictions and enhance physical and psychosocial well-being, aerobic exercise should be promoted and included in the overall management plan of clients with MS.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.924
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.288
GPT teacher head0.434
Teacher spread0.145 · 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.

Study designOther design
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

Citations7
Published2006
Admission routes1
Has abstractyes

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