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Record W2810344922 · doi:10.1136/svn-2018-000155

Exercise for stroke prevention

2018· review· en· W2810344922 on OpenAlexaff
Peter L. Prior, Neville Suskin

Bibliographic record

VenueStroke and Vascular Neurology · 2018
Typereview
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsWestern UniversitySt Joseph's Health CareLawson Health Research Institute
Fundersnot available
KeywordsMedicineStroke (engine)Physical therapyCardiorespiratory fitnessMotivational interviewingObservational studyQuality of life (healthcare)Depression (economics)ReferralRandomized controlled trialPhysical medicine and rehabilitationFamily medicineNursing

Abstract

fetched live from OpenAlex

We review evidence concerning exercise for stroke prevention. Plausible biological reasons suggest that exercise would be important in preventing stroke. While definitive randomised controlled trials evaluating the impact of physical activity (PA) and exercise on preventing stroke and mortality are lacking, observational studies, small randomised controlled trials and meta-analyses have provided evidence that PA and exercise favourably modify stroke risk factors, including hypertension, dyslipidaemia, diabetes, sedentary lifestyle, obesity, excessive alcohol consumption and tobacco use. It is, therefore, important to understand the factors associated with poststroke PA/exercise and cardiorespiratory fitness. Positively associated factors include self-efficacy, social support and quality of patients' relationships with health professionals. Negatively associated factors include logistical barriers, medical comorbidities, stroke-related deficits, negative exercise beliefs, fear of falling, poststroke fatigue, arthropathy/pain and depression. Definitive research is needed to specify efficacious behavioural approaches to increase poststroke exercise. Effective techniques probably include physician endorsement of exercise programmesto patients, enhancement of patient-professional relationships, providing patients an exercise rationale, motivational interviewing, collaborative goal-setting with patients, addressing logistical concerns, social support in programsmes, structured exercise programming, individualised behavioural instruction, behavioural diary recording, reviewing behavioural consequences of exercise efforts, reinforcing successful exercise performance. Exercise programming without counselling may increase short-term activity; simple advice or information-giving is probably ineffective. Older patients or those with cognitive impairment may need increased structure, with emphasis on behaviour per se, versus self-regulation skills. We support the latest American Heart Association/American Stroke Association guidelines (2014) recommending PA and exercise for stroke prevention, and referral to behaviourally oriented programmes to improve PA and exercise.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.023
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.002
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0230.005

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 head0.040
GPT teacher head0.346
Teacher spread0.307 · 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 designNot applicable
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

Citations101
Published2018
Admission routes1
Has abstractyes

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