Chondrocalcinosis of the Knee and the Risk of Osteoarthritis Progression: Data From the Knee and Hip Osteoarthritis Long‐term Assessment Cohort
Bibliographic record
Abstract
OBJECTIVE: To assess the impact of knee chondrocalcinosis (CC) on the 5-year risk of joint replacement and disease progression in patients with knee osteoarthritis (OA). METHODS: Patients with symptomatic knee OA without previous total joint (knee or hip) replacement (TJR) were recruited from the Knee and Hip Osteoarthritis Long-term Assessment cohort. Cox proportional hazards regression and generalized estimating equation models were used to compare the time from inclusion or OA diagnosis to total knee replacement (TKR) or TJR between patients with and those without knee CC at inclusion. In patients without incident TKR, logistic regression was performed to examine the association between CC and radiographic progression (Kellgren/Lawrence [K/L] grade) or worsening of Western Ontario and McMaster Universities Arthritis Index (WOMAC) subscores for OA pain or function between years 0 and 5. Hazard ratios (HRs) and 95% confidence intervals (95% CIs) were estimated. Analyses were adjusted for age, sex, body mass index, WOMAC subscores, and K/L grade. RESULTS: Among the 656 patients included, 93 (14.2%) had knee CC, and 91 (13.9%) underwent TKR during the follow-up. Risk of TKR was not affected by the presence of knee CC (HR 1.26 [95% CI 0.74-2.17]). Similar results were obtained for the risk of incident TJR. For patients without incident TKR, knee CC did not affect the risk of worsening of K/L grade (odds ratio [OR] 0.9 [95% CI 0.4-1.7]), WOMAC pain subscore (OR 1.1 [95% CI 0.7-1.4]), or WOMAC function subscore (OR 0.9 [95% CI 0.4-2.0]). CONCLUSION: In patients with symptomatic knee OA, the presence of knee CC did not affect the risk of arthroplasty or disease progression at 5 years.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".