Is Pain in One Knee Associated with Isometric Muscle Strength in the Contralateral Limb?
Bibliographic record
Abstract
OBJECTIVE: Knee pain and muscle weakness confer risk for knee osteoarthritis incidence and progression. The purpose of this study was to determine whether unilateral knee pain influences contralateral thigh muscle strength. DESIGN: Of 4796 Osteoarthritis Initiative participants, 224 (mean ± SD age, 63.9 ± 8.9 yrs) cases could be matched to a control. Cases were defined as having unilateral knee pain (numerical rating scale, ≥ 4/10; ≥infrequent pain) and one pain-free knee (numerical rating scale, 0-1; ≤infrequent pain; Western Ontario and McMaster Universities Arthritis Index, ≤ 1). Controls were defined as having bilaterally pain-free knees (numerical rating scale, 0-1; ≤infrequent pain; Western Ontario and McMaster Universities Arthritis Index, ≤ 1). Maximal isometric muscle strength (N) was compared between limbs in participants with unilateral pain (cases) as well as between pain-free limbs of cases and controls. RESULTS: Knee extensor/flexor strength in pain-free limbs of the cases was lower than that in bilaterally pain-free controls (-5.5%/-8.4%; P = 0.043/P = 0.022). Within the cases, maximum extensor/flexor strength was significantly lower in the painful limb than in the pain-free limb (-6.3%/4.1%; P < 0.0001/P = 0.015). CONCLUSIONS: These results suggest that strength in limbs without knee pain is associated with the pain status of the contralateral knee. The strength difference between unilateral pain-free cases and matched bilateral pain-free controls was similar to that between limbs in persons with unilateral knee pain. Lower strength caused by contralateral knee pain might be centrally mediated.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".