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Record W7039680910

Muscle performance, body fat, pain and function in the elderly with arthritis

2014· article· en· W7039680910 on OpenAlexaboutno aff

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2014
Typearticle
Languageen
FieldMaterials Science
TopicDiatoms and Algae Research
Canadian institutionsnot available
Fundersnot available
KeywordsOsteoarthritisWOMACIsometric exerciseBioelectrical impedance analysisIntensity (physics)ArthritisCorrelationChronic pain
DOInot available

Abstract

fetched live from OpenAlex

Objective: To correlate muscule performance, body composition, pain and joint function in elderly people with gonarthrosis. Method: 21 elderly patients were submitted to bioelectrical impedance analysis, dynamometry associated with electromyographic (EMG) evaluation of isometric knee extension, in addition to pain assessment by the Numeric Pain Intensity Scale and function assessment, by the Western Ontario and McMaster Universities (WOMAC) Osteoarthritis (OA) questionnaire. Correlations were checked by the Pearson's correlation coefficient. Results: The sample characteristics were mean age 67.36 ± 4.21 years old, body fat percentage 40.57±6.15%, total WOMAC score 43.27 ± 16.32%, and maximum strength 19.95 ± 6.99 kgF. Pain during movement showed a statistical association with WOMAC physical activity domain (r = 0.47) and its general score (r = 0.51); pain intensity at night presented association with WOMAC stiffness domain (r = 0.55), in addition to the negative correlation with the slope values of the Medium Frequency of the EMG signal (r = - 0.57). Conclusion: pain intensity is correlated to functional incapacity in elderly people with knee OA and to a greater expression of fatigue in EMG signal. Levels of Evidence III, Study of non consecutive patients

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.920
Threshold uncertainty score0.689

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.225
Teacher spread0.212 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations1
Published2014
Admission routes1
Has abstractyes

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