Association of Chondrocalcinosis in Knee Joints With Pain and Synovitis: Data From the Osteoarthritis Initiative
Bibliographic record
Abstract
OBJECTIVE: To evaluate the relationship between chondrocalcinosis and pain or synovitis in knee joints by examining data from the Osteoarthritis Initiative (OAI). METHODS: Data were obtained from the OAI public-use data sets. The relationship between chondrocalcinosis on baseline knee radiograph and pain at baseline and at 4 years was examined. Analyses were adjusted for age, sex, body mass index, and Kellgren-Lawrence (K/L) grade and the correlation between 2 knees in a subject was controlled using generalized estimating equations. The relationship between chondrocalcinosis and synovitis on magnetic resonance imaging (MRI) was examined by comparing knees with chondrocalcinosis at baseline and age, sex, and K/L grade-matched knees with no chondrocalcinosis. We read MRIs of a subset of knees for synovitis using the MRI Osteoarthritis Knee Score (MOAKS) on baseline and 4-year MRI. RESULTS: Knees with chondrocalcinosis (n = 162) more often had pain compared to knees without chondrocalcinosis (n = 2,030) at baseline and had higher Western Ontario and McMaster Universities Osteoarthritis Index pain scores, both at baseline (mean 2.4 [95% confidence interval (95% CI) 1.9, 2.9]) versus mean 1.8 [95% CI 1.7, 1.9]) and at 4 years (mean 2.5 [95% CI 1.9, 3.1] versus mean 1.6 [95% CI 1.5, 1.8]), as well as higher Intermittent and Constant Osteoarthritis Pain intermittent pain scores at 4 years. There was no difference in MOAKS synovitis scores at baseline and at 4 years between the chondrocalcinosis group (n = 102) and the control group (n = 99). CONCLUSION: Knees with chondrocalcinosis had increased pain and did not have higher synovitis scores on MRI compared to knees without chondrocalcinosis. The mechanisms by which chondrocalcinosis is associated with increased pain remain to be determined.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".