Characterization of Quadriceps Neuromuscular Function in Knee Osteoarthritis
Bibliographic record
Abstract
PURPOSE: The purpose of this thesis was to characterize quadriceps neuromuscular dysfunction in patients with knee osteoarthritis (OA). Concerns pertaining to study design in this patient population (e.g. disease severity criteria and muscle imaging outcome measures) were also addressed.\nMETHODS: Five studies were undertaken using data acquired from volunteers recruited at the local institution and from participants in the public source dataset of the Osteoarthritis Initiative (http://oai.epi-ucsf.org/datarelease/). Clinical disease severity was evaluated with the Western Ontario and McMaster Osteoarthritis Index (WOMAC). Radiographic severity was evaluated with Kellgren-Lawrence Grading (KLG). Quadriceps muscle isometric strength and isotonic power were measured with dynamometry. Voluntary activation (VA) of the quadriceps was determined with the interpolated twitch technique. Information about intrinsic properties of the neuromuscular system were assessed with magnetic resonance imaging (MRI) derived measures of muscle volume, intramuscular and surface electromyography and measurement of evoked contractile properties.\nRESULTS: Radiographic definition of disease severity displayed a ceiling effect and led to underestimation of quadriceps muscle weakness in patients with knee OA (Chapter 2). Quadriceps muscle isometric strength, velocity and isotonic power were reduced across a clinical spectrum of knee OA, however muscle quality (i.e. specific torque and specific power were unaffected, Chapter 3). Quadriceps whole muscle volume, measured with MRI can be reliably measured and was the primary predictor of isometric strength (Chapter 4). VA deficits were minimal in knee OA patients, even in those with severe knee pain and disability (Chapter 5). No changes in evoked contractile properties were observed across a clinical spectrum of knee OA, however average motor unit size was larger and firing rates slightly lower in patients with knee OA compared to healthy controls (Chapter 6).\nCONCLUSION: This thesis provided information about the magnitude and mechanisms of quadriceps neuromuscular dysfunction in patients with knee OA, which have consequences with regard to the treatment and prognosis of this disorder. Furthermore, the information provided about the validity of commonly used predictor variables and outcome measures has implications for future study design in this disease population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".