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Record W4365479014 · doi:10.1002/jcsm.13225

Exercise for sarcopenia in older people: A systematic review and network meta‐analysis

2023· review· en· W4365479014 on OpenAlexaff
Yanjiao Shen, Qingyang Shi, Kailei Nong, Sheyu Li, Jirong Yue, Jin Huang, Birong Dong, Marla Beauchamp, Qiukui Hao

Bibliographic record

VenueJournal of Cachexia Sarcopenia and Muscle · 2023
Typereview
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsMcMaster University
FundersNational Key Research and Development Program of ChinaHealth and Family Planning Commission of Sichuan Province
KeywordsSarcopeniaMedicineMeta-analysisGerontologyOlder peopleMEDLINESystematic reviewInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Sarcopenia is a serious public health concern among older adults worldwide. Exercise is the most common intervention for sarcopenia. This study aimed to compare the effectiveness of different exercise types for older adults with sarcopenia. METHODS: Randomized controlled trials (RCTs) that examined the effectiveness of exercise interventions on patient-important outcomes for older adults with sarcopenia were eligible. We systematically searched MEDLINE, Embase and Cochrane Central Register of Controlled Trials via Ovid until 3 June 2022. We used frequentist random-effects network meta-analyses to summarize the evidence and applied the Grading of Recommendations, Assessment, Development, and Evaluations framework to rate the certainty of evidence. RESULTS: Our search identified 5988 citations, of which 42 RCTs proved eligible with 3728 participants with sarcopenia (median age: 72.9 years, female: 73.3%) with a median follow-up of 12 weeks. We are interested in patient-important outcomes that include mortality, quality of life, muscle strength and physical function measures. High or moderate certainty evidence suggested that resistance exercise with or without nutrition and the combination of resistance exercise with aerobic and balance training were the most effective interventions for improving quality of life compared to usual care (standardized mean difference from 0.68 to 1.11). Moderate certainty evidence showed that resistance and balance exercise plus nutrition (mean difference [MD]: 4.19 kg) was the most effective for improving handgrip strength (minimally important difference [MID]: 5 kg). Resistance and balance exercise with or without nutrition (MD: 0.16 m/s, moderate) were the most effective for improving physical function measured by usual gait speed (MID: 0.1 m/s). Moderate certainty evidence showed that resistance and balance exercise (MD: 1.85 s) was intermediately effective for improving physical function measured by timed up and go test (MID: 2.1 s). High certainty evidence showed that resistance and aerobic, or resistance and balance, or resistance and aerobic exercise plus nutrition (MD from 1.72 to 2.28 s) were intermediately effective for improving physical function measured by the five-repetition chair stand test (MID: 2.3 s). CONCLUSIONS: In older adults with sarcopenia, high or moderate certainty evidence showed that resistance exercise with or without nutrition and the combination of resistance exercise with aerobic and balance training were the most effective interventions for improving quality of life. Adding nutritional interventions to exercise had a larger effect on handgrip strength than exercise alone while showing a similar effect on other physical function measures.

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)0.019
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.047
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0210.032
Bibliometrics0.0090.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.141
GPT teacher head0.422
Teacher spread0.281 · 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 designMeta-analysis
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

Citations401
Published2023
Admission routes1
Has abstractyes

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