Magnetic Resonance Imaging–Defined Osteoarthritis Features and Anterior Knee Pain in Individuals With, or at Risk for, Knee Osteoarthritis: A Multicenter Study on Osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: The lack of strong association between knee osteoarthritis (OA) structural features and pain continues to perplex researchers and clinicians. Evaluating the patellofemoral joint in addition to the tibiofemoral joint alone has contributed to explaining this structure-pain discordance, hence justifying a more comprehensive evaluation of whole-knee OA and pain. The present study, therefore, was undertaken to evaluate the association between patellofemoral and tibiofemoral OA features with localized anterior knee pain (AKP) using 2 study designs. METHODS: Using cross-sectional data from the Multicenter Osteoarthritis Study, our first approach was a within-person, knee-matched design in which we identified participants with unilateral AKP. We then assessed magnetic resonance imaging (MRI)-derived OA features (cartilage damage, bone marrow lesions [BMLs], osteophytes, and inflammation) in both knees and evaluated the association of patellofemoral and tibiofemoral OA features to unilateral AKP. In our second approach, MRIs from 1 knee per person were scored, and we evaluated the association of OA features to AKP in participants with AKP and participants with no frequent knee pain. RESULTS: Using the first approach (n = 71, 66% women, mean ± SD age 69 ± 8 years), lateral patellofemoral osteophytes (odds ratio [OR] 5.0 [95% confidence interval (95% CI) 1.7-14.6]), whole-knee joint effusion-synovitis (OR 4.7 [95% CI 1.3-16.2]), and infrapatellar synovitis (OR 2.8 [95% CI 1.0-7.8]) were associated with AKP. Using the second approach (n = 882, 59% women, mean ± SD age 69 ± 7 years), lateral and medial patellofemoral cartilage damage (prevalence ratio [PR] 2.3 [95% CI 1.3-4.0] and PR 1.9 [95% CI 1.1-3.3], respectively) and lateral patellofemoral BMLs (PR 2.6 [95% CI 1.5-4.7]) were associated with AKP. CONCLUSION: Patellofemoral but not tibiofemoral joint OA features and inflammation were associated with AKP.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".