Correlates of Gait Speed in Advanced Knee Osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: This study aims to evaluate correlates of gait speed, a measure of disability, in older adults with advanced knee osteoarthritis (OA) and chronic pain. DESIGN/SETTING/SUBJECTS/METHODS: Baseline data were analyzed from a clinical trial of 190 participants aged >50 with advanced knee OA (according to clinical and radiographic American College of Rheumatology criteria) and chronic pain. Data included 4-meter gait speed, quality of life (Short Form Health Survey 36 global health subscale), knee pain (Western Ontario and McMasters Universities Osteoarthritis Index [WOMAC]), depressive symptoms (Center for Epidemiologic Studies Depression Scale), coping strategies (catastrophizing subscale and Cognitive Strategies Questionnaire), self-efficacy (Athritis Self-efficacy Scale [ASES]), comorbidity (Cumulative Illness Rating Scale), analgesic use, and pain comorbidities (location, frequency, and intensity). A multivariable regression model was used to investigate these variables as they relate to gait speed. RESULTS: In the univariate analysis, the following variables were associated with gait speed: knee pain (per WOMAC), age, depressive symptoms, global health, catastrophizing, ASES function and other, comorbidity, and opioid use (all P values <0.05). In the fully adjusted multivariate model, controlling for knee pain, significant associations between gait speed and age (β = -0.006; P < 0.001), ASES function (β = 0.003; P < 0.001), and opioid use (β = -0.082; P = 0.009) persisted. The correlation between opioid dose and gait speed (among opioid users) was not statistically significant (r = 0.04; P = 0.81). CONCLUSION: In a cross-sectional study of older adults with advanced knee OA and chronic pain, we found that age, arthritis function self-efficacy, and opioid use (but not dose) were significantly associated with decreased gait speed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".