Knee effusion volume assessed by magnetic resonance imaging and progression of knee osteoarthritis: data from the Osteoarthritis Initiative
Bibliographic record
Abstract
Objective: To examine whether baseline knee joint effusion volume and the change in effusion volume over 1 year are associated with cartilage volume loss, progression of radiographic OA (ROA) over 4 years and risk of total knee replacement over 6 years. Methods: This study included 4115 Osteoarthritis Initiative participants with knee joint effusion volume quantified by MRI at baseline. The change in effusion volume over 1 year was assessed. Cartilage volume loss and progression of ROA over 4 years were assessed using MRI and X-ray and total knee replacement over 6 years was assessed. Multiple linear regression and binary logistic regression were used for data analyses. Results: Baseline knee effusion volume (per 5 ml) was positively associated with a loss of medial and lateral cartilage volume [regression coefficient 0.13%/year (95% CI 0.10, 0.17) and 0.13%/year (95% CI 0.10, 0.16), respectively, both P < 0.001], progression of ROA [odds ratio (OR) 1.28 (95% CI 1.20, 1.37), P < 0.001], and risk of knee replacement [OR 1.12 (95% CI 1.05, 1.20), P = 0.001]. A 5 ml increase in knee effusion volume over 1 year was positively associated with medial cartilage volume loss [regression coefficient 0.09%/year (95% CI 0.04, 0.15), P = 0.001], progression of ROA [OR 1.21 (95% CI 1.11, 1.33), P < 0.001] and risk of knee replacement [OR 1.24 (95% CI 1.12, 1.37), P < 0.001]. Conclusions: Knee joint effusion volume assessed from MRI provides a continuous and sensitive measure that was associated with cartilage volume loss, progression of ROA and risk of total knee replacement. It may provide a method to identify individuals with an inflammatory OA phenotype who are at higher risk of disease progression.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".