Bone marrow lesions and collateral ligament lesions are associated in interphalangeal joints with osteoarthritis: The Hand OSTeoArthritis in Secondary care cohort
Bibliographic record
Abstract
OBJECTIVES: To investigate whether bone activity adjacent to collateral ligaments is present and results in collateral ligament lesions (CLLs) of the proximal and distal interphalangeal joints in patients with hand osteoarthritis (OA), and vice versa. METHODS: We used data measured on baseline, year two and year four from the Hand OSTeoArthritis in Secondary care cohort. MR images of the right hand were scored at the radial and ulnar 1/3rd of each joint ("=joint side") for bone marrow lesions (BMLs) and CLLs (=non-visible or non-continuous ligament). Odds ratios (ORs) with 95% confidence intervals were used to quantify longitudinal associations at the same joint side, adjusted for patient effect. RESULTS: In 261 patients (mean age 61 years, 84% women), BMLs were present at baseline in 113/4169 joint sides (3%), and at year four in 89/3356 (3%). Any CLL was present at baseline in 500/4169 joint sides (12%), and at year four in 559/3356 (17%). The presence of BMLs and CLL was cross-sectionally associated. In baseline joint sides without CLLs, BMLs were positively associated with CLL development in the corresponding joint side at year two and four (OR 3.7 (1.5;9.1) and 4.9 (2.3;10.7), respectively), compared with no BMLs. In baseline joint sides without BMLs, CLLs were positively associated with BMLs at the same side at year two and four (9.2 (3.9;22.1) and 11.0 (5.8;20.9) respectively), compared with no CLLs. CONCLUSIONS: BMLs are rare yet associated with CLLs that are more common, both cross-sectionally and longitudinally, both adding to the OA process.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".