The association between change in bone marrow lesion size and change in tibiofemoral cartilage volume and knee symptoms
Bibliographic record
Abstract
OBJECTIVE: To describe the association between change in subchondral bone marrow lesions (BMLs) and change in tibiofemoral cartilage volume and knee symptoms in patients with symptomatic knee OA. METHODS: In total, 251 participants (mean 61.7 years, 51% female) were included. Tibiofemoral cartilage volume was measured at baseline and 24 months, and BML size at baseline, 6 and 24 months. Knee pain and function scores were evaluated at baseline, 6 and 24 months. Change in total and compartment-specific BML size was categorized according to the Least Significance Criterion. Linear mixed-effects models were used to evaluate the associations of change in BMLs over 6 and 24 months with change in cartilage volume over 24 months and knee symptoms over 6 and 24 months. RESULTS: Total BML size enlarged in 26% of participants, regressed in 31% and remained stable in 43% over 24 months. Compared with stable BMLs in the same compartment, enlarging BMLs over 24 months were associated with greater cartilage loss (difference: -53.0mm3, 95% CI: -100.0, -6.0), and regressing BMLs were not significantly associated with reduced cartilage loss (difference: 32.4mm3, 95% CI: -8.6, 73.3) over 24 months. Neither enlargement nor regression of total BML size over 6 and 24 months was associated with change in knee pain and function over the same time intervals. CONCLUSIONS: In subjects with symptomatic knee osteoarthritis and BMLs, enlarging BMLs may lead to greater cartilage loss but regressing lesions are not associated with reduced cartilage loss while neither is associated with change in knee symptoms.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.003 | 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".