The association between subchondral bone cysts and tibial cartilage volume and risk of joint replacement in people with knee osteoarthritis: a longitudinal study
Bibliographic record
Abstract
INTRODUCTION: To examine the natural history of subchondral bone cysts and to determine whether knee cartilage loss and risk of joint replacement is higher in knees with cysts, compared with those with bone marrow lesions (BMLs) only or those with neither BMLs nor cysts. METHODS: The symptomatic knee in 132 subjects with knee osteoarthritis (OA) was imaged by using magnetic resonance imaging at baseline and 2 years later. Tibial cartilage volume, subchondral bone cysts, and BMLs were measured by using validated methods. Knee arthroplasty over a 4-year period was ascertained. RESULTS: Bone cysts were present in 47.7% of subjects, 98.1% of whom also had BMLs. Over a 2-year period, 23.9% of subjects had cysts progress, 13.0% developed new cysts, and 11.4% had cysts regress. Bone cysts at baseline were associated with lower medial and lateral tibial cartilage volume compared with those with BMLs only or those with neither (P for trend 0.004 and <0.001, respectively). Annual medial cartilage volume loss was greatest in those with bone cysts compared with those with BMLs only or those with neither (9.3%, 6.3%, and 2.6%, respectively; P for trend, <0.001). As the severity of bone abnormality in the medial compartment increased from no BMLs or cysts present, to BMLs only, to subchondral bone cysts present, the risk of knee replacement was increased (odds ratio, 1.99; 95% confidence interval (CI), 1.01 to 3.90; P = 0.05). CONCLUSIONS: When cysts are present, cartilage loss and risk of knee replacement are higher than if only BMLs are present, suggesting that cysts identify those most likely to benefit from prevention of disease progression. As cysts can regress, they may also provide therapeutic targets in knee OA.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".