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Record W2539345815 · doi:10.14740/jocmr2767w

Exercise Intervention for Anti-Sarcopenia in Community-Dwelling Older People

2016· review· en· W2539345815 on OpenAlexvenueno aff
Ryo Miyazaki, Taro Takeshima, Kazuhiko Kotani

Bibliographic record

VenueJournal of Clinical Medicine Research · 2016
Typereview
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsnot available
Fundersnot available
KeywordsSarcopeniaMedicinePsychological interventionGerontologyMuscle massRandomized controlled trialPhysical therapyIntervention (counseling)MEDLINEPhysical medicine and rehabilitationInternal medicineNursing

Abstract

fetched live from OpenAlex

Sarcopenia is an age-related health problem in general communities. Effective exercise programs against sarcopenia remain necessary for community-dwelling older people. In order to summarize the available knowledge on this subject, we collected English articles from a MEDLINE/Pubmed database examining the effects of exercise interventions on sarcopenia-related outcome measures in community-dwelling older people. When nine articles, including eight randomized controlled trials, were reviewed, most studies demonstrated significant improvements in some outcome measures. Indeed, a significant improvement in the muscle mass in one study, muscle strength in two studies and physical performance in two studies was reported among five studies using exercise (E) alone. A significant improvement in the muscle mass in two studies, muscle strength in one study and physical performance in two studies was also reported among four studies using exercise plus nutritional supplementation (EN). Notably, the EN studies appeared to have less extensive exercise interventions than the E studies. One EN study further exhibited significant improvements in all outcome measures. Collectively, exercise could be used as anti-sarcopenic strategies and nutritional interventions when combined with exercise might play a compensated or perhaps a comprehensive role among community-dwelling older people. Limited studies exist and more studies are required for the optimum programs in the community settings.

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)0.060
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.912
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0600.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.007
Insufficient payload (model declined to judge)0.0010.000

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 head0.625
GPT teacher head0.691
Teacher spread0.066 · 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; both teacher heads agree on what is shown here.

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

Citations21
Published2016
Admission routes1
Has abstractyes

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