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Record W1997039211 · doi:10.1186/1471-2474-12-199

Vastus medialis motor unit properties in knee osteoarthritis

2011· article· en· W1997039211 on OpenAlexafffund
Michael Berger, David G. Chess, Timothy J. Doherty

Bibliographic record

VenueBMC Musculoskeletal Disorders · 2011
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsSt Joseph's Health CareWestern University
FundersCanadian Institutes of Health ResearchCanada Research Chairs
KeywordsIsometric exerciseVastus medialisMedicineOsteoarthritisMotor unitElectromyographyPhysical medicine and rehabilitationInternal medicinePhysical therapyKnee painKnee JointCardiologyAnatomySurgeryPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Maximal isometric quadriceps strength deficits have been widely reported in studies of knee osteoarthritis (OA), however little is known about the effect of osteoarthritis knee pain on submaximal quadriceps neuromuscular function. The purpose of this study was to measure vastus medialis motor unit (MU) properties in participants with knee OA, during submaximal isometric contractions. METHODS: Vastus medialis motor unit potential (MUP) parameters were assessed in 8 patients with knee OA and 8 healthy, sex and age-matched controls during submaximal isometric contractions (20% of maximum isometric torque). Unpaired t-tests were used to compare groups for demographic and muscle parameters. RESULTS: Maximum knee extension torque was ~22% lower in the OA group, a difference that was not statistically significantly (p = 0.11). During submaximal contractions, size related parameters of the needle MUPs (e.g. negative peak duration and amplitude-to-area ratio) were greater in the OA group (p < 0.05), with a rightward shift in the frequency distribution of surface MUP negative peak amplitude. MUP firing rates were significantly lower in the OA group (p < 0.05). CONCLUSIONS: Changes in MU recruitment and rate coding strategies in OA may reflect a chronic reinnervation process or a compensatory strategy in the presence of chronic knee pain associated with OA.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.697
Threshold uncertainty score0.926

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.020
GPT teacher head0.211
Teacher spread0.191 · 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 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

Citations37
Published2011
Admission routes2
Has abstractyes

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