Association of magnetic resonance imaging–based knee cartilage T2 measurements and focal knee lesions with knee pain: Data from the Osteoarthritis Initiative
Bibliographic record
Abstract
OBJECTIVE: To evaluate the association of magnetic resonance imaging (MRI)-based knee cartilage T2 measurements and focal knee lesions with knee pain in knees without radiographic osteoarthritis (OA) among subjects with OA risk factors. METHODS: We studied the right knees of 126 subjects from the Osteoarthritis Initiative database. We randomly selected 42 subjects ages 45-55 years with OA risk factors, right knee pain (Western Ontario and McMaster Universities Osteoarthritis Index [WOMAC] pain score ≥5), no left knee pain (WOMAC pain score 0), and no radiographic OA (Kellgren/Lawrence [K/L] score ≤1) in the right knee. We also selected 2 comparison groups: 42 subjects without knee pain in either knee and 42 with bilateral knee pain. Both groups were frequency matched to subjects with right knee pain only by sex, age, body mass index, and K/L score. All of the subjects underwent 3T MRI of the right knee. Focal knee lesions were assessed and cartilage T2 measurements were performed. RESULTS: Prevalences of meniscal, bone marrow, and ligamentous lesions and joint effusion were not significantly different between the groups (P > 0.05), while cartilage lesions were more frequent in subjects with right knee pain only compared to subjects without knee pain (P < 0.05). T2 values averaged over all of the compartments were similar in subjects with right knee pain only (mean ± SD 34.4 ± 1.8 msec) and in subjects with bilateral knee pain (mean ± SD 34.7 ± 4.7 msec), but were significantly higher compared to subjects without knee pain (mean ± SD 32.4 ± 1.8 msec; P < 0.05). CONCLUSION: These results suggest that elevated cartilage T2 values are associated with findings of pain in the early phase of OA, whereas among morphologic knee abnormalities only knee cartilage lesions are significantly associated with knee pain status.
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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 | 0.003 |
| 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 | 0.000 |
| 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".