Quadriceps strength and the risk of cartilage loss and symptom progression in knee osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: To determine the effect of quadriceps strength in individuals with knee osteoarthritis (OA) on loss of cartilage at the tibiofemoral and patellofemoral joints (assessed by magnetic resonance imaging [MRI]) and on knee pain and function. METHODS: We studied 265 subjects (154 men and 111 women, mean+/-SD age 67+/-9 years) who met the American College of Rheumatology criteria for symptomatic knee OA and who were participating in a prospective, 30-month natural history study of knee OA. Quadriceps strength was measured at baseline, isokinetically, during concentric knee extension. MRI of the knee at baseline and at 15 and 30 months was used to assess cartilage loss at the tibiofemoral and patellofemoral joints, with medial and lateral compartments assessed separately. At baseline and at followup visits, knee pain was assessed using a visual analog scale, and physical function was assessed using the Western Ontario and McMaster Universities Osteoarthritis Index. RESULTS: There was no association between quadriceps strength and cartilage loss at the tibiofemoral joint. Results were similar in malaligned knees. However, greater quadriceps strength was protective against cartilage loss at the lateral compartment of the patellofemoral joint (for highest versus lowest tertile of strength, odds ratio 0.4 [95% confidence interval 0.2, 0.9]). Those with greater quadriceps strength had less knee pain and better physical function over followup (P<0.001). CONCLUSION: Greater quadriceps strength had no influence on cartilage loss at the tibiofemoral joint, including in malaligned knees. We report for the first time that greater quadriceps strength protected against cartilage loss at the lateral compartment of the patellofemoral joint, a finding that requires confirmation. Subjects with greater quadriceps strength also had less knee pain and better physical function over followup.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".