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Effect of watergym in knee osteoarthritis

2014· article· en· W2140158550 on OpenAlexaboutno aff
João Paulo Fernandes Guerreiro, Renan Floret Turin Claro, João Daniel Rodrigues, Beatriz Funayama Alvarenga Freire

Bibliographic record

VenueActa Ortopédica Brasileira · 2014
Typearticle
Languageen
FieldHealth Professions
TopicTherapeutic Uses of Natural Elements
Canadian institutionsnot available
FundersUniversidade Estadual Paulista
KeywordsOsteoarthritisWOMACPhysical therapyMedicineVisual analogue scaleKnee painAnalysis of variancePhysical medicine and rehabilitationAlternative medicineInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Evaluate the effectiveness of watergym to alleviate knee osteoarthritis (OA) symptoms and improve locomotor function. METHODS: Forty-two volunteers, 38 women and four men with OA, practicing watergym, divided into the following groups: beginners, intermediate, advanced, and advanced level with other physical activities in addition to watergym were included in the study. Individuals were assessed at times zero, 8 and 12 weeks, with classes lasting 45 minutes, twice a week. Function was assessed by the Aggregate Locomotor Function (ALF) score, and pain and other symptoms by the visual analogical scale (VAS) and by the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) questionnaire. Statistical analysis was carried out by the variance analysis for repeated measurements, followed by Tukey's method for comparison of time point means whenever required. RESULTS: None of the tests showed a significant improvement of pain or locomotion. CONCLUSION: Watergym was not effective in improving symptoms and did not affect the locomotor capacity of individuals with knee OA. Level of evidence IV, Case series.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.367
Teacher spread0.348 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations6
Published2014
Admission routes1
Has abstractyes

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