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Record W4403320236 · doi:10.1136/bjsports-2023-107625

Quantitative analysis of effectiveness and associated factors of exercise on symptoms in osteoarthritis: a pharmacodynamic model-based meta-analysis

2024· review· en· W4403320236 on OpenAlexaboutno aff
Shun Han, Ting Li, Ying Cao, Zewei Li, Yiying Mai, Tianxiang Fan, Muhui Zeng, Xin Wen, Weiyu Han, Lijun Lin, Lixin Zhu, Siu Ngor Fu, Kim L. Bennell, David J. Hunter, Changhai Ding, Lujin Li, Zhaohua Zhu

Bibliographic record

VenueBritish Journal of Sports Medicine · 2024
Typereview
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsWOMACMedicineOsteoarthritisPhysical therapyMinimal clinically important differenceMeta-analysisVisual analogue scaleCochrane LibraryRandomized controlled trialPhysical medicine and rehabilitationInternal medicineAlternative medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: This study aims to evaluate the time point and magnitude of peak effectiveness of exercise and the effects of various exercise modalities for osteoarthritis (OA) symptoms and to identify factors that significantly affect the effectiveness of exercise. DESIGN: Pharmacodynamic model-based meta-analysis (MBMA). DATA SOURCES: Embase, PubMed, Cochrane Library, Web of Science and Scopus were searched for randomised controlled trials (RCTs) examining the effect of exercise for OA from inception to 20 November 2023. ELIGIBILITY CRITERIA: RCTs of exercise interventions in patients with knee, hip or hand OA, using Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) subscales or Visual Analogue Scale (VAS) pain scores as outcome measures, were included. The minimum clinically important difference (MCID) for WOMAC total, pain, stiffness, function and VAS pain was 9.0, 1.6, 0.8, 5.4 and 0.9, respectively. RESULTS: A total of 186 studies comprising 12 735 participants with symptomatic or radiographic knee, hip or hand OA were included. The effectiveness of exercise treatments peaked at 1.6-7.2 weeks after initiation of exercise interventions. Exercise was more effective than the control, but the differences in the effects of exercise compared with control on all outcomes were only marginally different with the MCID (7.5, 1.7, 1.0, 5.4 and 1.2 units for WOMAC total, pain, stiffness, function and VAS pain, respectively). During a 12-month treatment period, local exercise (strengthening muscles and improving mobilisations of certain joints) had the best effectiveness (WOMAC pain decreasing by 42.5% at 12 weeks compared with baseline), followed by whole-body plus local exercise. Adding local water-based exercise (eg, muscle strengthening in warm water) to muscle strengthening exercise and flexibility training resulted in 7.9, 0.5, 0.7 and 8.2 greater improvements in the WOMAC total score, pain, stiffness and function, respectively. The MBMA models revealed that treatment responses were better in participants with more severe baseline symptom scores for all scales, younger participants for the WOMAC total and pain scales, and participants with obesity for the WOMAC function. Subgroup analyses revealed participants with certain characteristics, such as female sex, younger age, knee OA or more severe baseline symptoms on the WOMAC pain scale, benefited more from exercise treatment. CONCLUSION: Exercise reaches peak effectiveness within 8 weeks and local exercise has the best effectiveness, especially if local water-based exercise is involved. Patients of female sex, younger age, obesity, knee OA or more severe baseline symptoms appear to benefit more from exercise treatment than their counterparts.

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)0.074
metaresearch head score (Gemma)0.118
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: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.074
Threshold uncertainty score0.393

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0740.118
Meta-epidemiology (narrow)0.0050.002
Meta-epidemiology (broad)0.0240.084
Bibliometrics0.0070.006
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0030.002
Research integrity0.0030.003
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 head0.048
GPT teacher head0.357
Teacher spread0.308 · 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

Citations16
Published2024
Admission routes1
Has abstractyes

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