Bone curvature changes can predict the impact of treatment on cartilage volume loss in knee osteoarthritis: data from a 2-year clinical trial
Bibliographic record
Abstract
Objectives: Knee bone curvature assessed by MRI was associated with OA cartilage loss. A recent knee OA trial demonstrated the superiority of chondroitin sulfate over celecoxib (comparator) at reducing cartilage volume loss (CVL) in the medial compartment (condyle). The main objectives were to identify which baseline bone curvature regions of interest (BCROI) best associated with CVL and investigate whether baseline BCROI and 2-year change are correlated with the protective effect of chondroitin sulphate on CVL. Methods: This post hoc analysis of a clinical trial used the according-to-protocol population (chondroitin sulphate, n = 57; celecoxib, n = 63) baseline and 2-year MRI to assess bone curvature and CVL. Global optimum search identified the BCROI in the medial condyle using celecoxib as reference. Statistical analyses were performed with Pearson's correlation, Mann-Whitney U -test, Student's t -test and analysis of covariance. Results: The BCROI including the medial posterior condyle and lateral central condyle was found to correlate best with medial condyle CVL at 2 years ( r = 0.33, P = 0.008). In patients with a baseline BCROI value less than the median (more flattened bone), chondroitin sulphate demonstrated a protective effect on CVL compared with celecoxib in the medial compartment (P = 0.037). In patients with 2-year BCROI changes greater than the median (greater severity of bone flattening), chondroitin sulphate protected against CVL in the medial compartment, condyle and central plateau (P ⩽ 0.030). Conclusion: This study is the first to demonstrate the feasibility and usefulness of bone curvature measurements to predict effectiveness of OA treatment on CVL. The results identify bone curvature as a potential novel biomarker for knee OA clinical trials.
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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 | 0.013 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.004 | 0.001 |
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".