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Effectiveness of balance training on pain and functional outcomes in knee osteoarthritis: A systematic review and meta-analysis

2023· review· en· W4387616304 on OpenAlexaboutno aff
Ashish John Prabhakar, R Shruthi, Dias Tina Thomas, Pradeepa Nayak, Abraham M. Joshua, Srikanth Prabhu, Yogeesh D. Kamat

Bibliographic record

VenueF1000Research · 2023
Typereview
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineWOMACMeta-analysisPhysical therapyOsteoarthritisCochrane LibraryRandomized controlled trialBalance (ability)Visual analogue scalePhysical medicine and rehabilitationInternal medicineAlternative medicinePathology

Abstract

fetched live from OpenAlex

Background: Knee osteoarthritis (OA) is a musculoskeletal disorder that causes pain and increasing loss of function, resulting in reduced proprioceptive accuracy and balance. Therefore, the goal of this systematic review and meta-analysis is to evaluate the effectiveness of balance training on pain and functional outcomes in knee OA. Methods: “PubMed”, “Scopus”, “Web of Science”, “Cochrane”, and “Physiotherapy Evidence Database” were searched for studies conducted between January 2000 and December 2021. Randomized controlled trials (RCTs) that investigated the effectiveness of balance training in knee OA, as well as its effects on pain and functional outcome measures, were included. Conference abstracts, case reports, observational studies, and clinical commentaries were not included. Meta-analysis was conducted for the common outcomes, i.e., Visual Analog Scale (VAS), The Timed Up and Go (TUG), Western Ontario and McMaster Universities Arthritis Index (WOMAC). The PEDro scale was used to determine the quality of the included studies. Results: This review includes 22 RCTs of which 17 articles were included for meta-analysis. The included articles had 1456 participants. The meta-analysis showed improvement in the VAS scores in the experimental group compared to the control group [ I 2= 92%; mean difference= -0.79; 95% CI= -1.59 to 0.01; p<0.05] and for the WOMAC scores the heterogeneity ( I 2) was 81% with a mean difference of -0.02 [95% CI= -0.44 to 0.40; p<0.0001]. The TUG score was analyzed, the I 2 was 95% with a mean difference of -1.71 [95% CI= -3.09 to -0.33; p<0.0001] for the intervention against the control group. Conclusions: Balance training significantly reduced knee pain and improved functional outcomes measured with TUG. However, there was no difference observed in WOMAC. Although due to the heterogeneity of the included articles the treatment impact may be overestimated. Registration: The current systematic review was registered in PROSPERO on 7th October 2021 (registration number CRD42021276674).

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)0.016
metaresearch head score (Gemma)0.033
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 score0.020
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.033
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0200.041
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0030.002
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 head0.164
GPT teacher head0.399
Teacher spread0.235 · 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

Citations7
Published2023
Admission routes1
Has abstractyes

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