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Record W2133246960 · doi:10.1682/jrrd.2007.01.0014

Balance, falls, and bone health: Role of exercise in reducing fracture risk after stroke

2008· review· en· W2133246960 on OpenAlexaff
Janice J. Eng

Bibliographic record

VenueThe Journal of Rehabilitation Research and Development · 2008
Typereview
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineStroke (engine)Physical therapyRehabilitationPhysical medicine and rehabilitationBalance (ability)Psychological interventionHip fractureRandomized controlled trialBone healthFall preventionFragilityOsteoporosisInjury preventionPoison controlBone mineralMedical emergencySurgeryPsychiatry

Abstract

fetched live from OpenAlex

Fractures occur frequently in people living with stroke and have high personal, social, and economic costs for these individuals, their families, and the community. Exercise to reduce the risk of fragility fractures is a relatively new application in stroke rehabilitation but is a promising treatment with the potential to reduce the incidence of falls as well as maintain or improve bone health. In this article, we outline fracture risk factors and provide an overview of exercise interventions aimed at reducing fracture risk poststroke. Although randomized controlled trials support the use of exercise to reduce fracture risk factors poststroke, the body of literature is small and further studies are required. Further, the optimal dose of exercise and the additive effects of pharmacology on fracture risk need to be determined. Given the many health benefits associated with exercise, it should be considered an important modality for the management of falls and maintenance of bone health following 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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.033
GPT teacher head0.371
Teacher spread0.338 · 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

Citations72
Published2008
Admission routes1
Has abstractyes

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