Radiographically detectable intra-articular mineralization: Predictor of knee osteoarthritis outcomes or only an indicator of aging? A brief report from the osteoarthritis initiative
Bibliographic record
Abstract
Objective: To determine the association between Intra-articular mineralization (IAM) and knee osteoarthritis (OA) outcomes stratified according to participants' age. Methods: Participants from the Osteoarthritis Initiative (OAI) with baseline radiographic OA (i.e., Kellgren-Lawrence grade ≥2 with Osteoarthritis Research Society International (OARSI) atlas joint space narrowing (JSN)) in either knee were identified. Both knees and dominant hand baseline radiographs were evaluated for the presence of IAM. Whole-grade OARSI-JSN radiographic progression and increased Western Ontario and McMaster universities osteoarthritis index scores of the knees with baseline radiographic OA (assessed annually) were defined as radiographic and symptomatic progression, respectively. Cox proportional-hazards and longitudinal multilevel regression models investigated radiographic and symptomatic progression, respectively. Results: 2010 participants with baseline radiographic OA in either one or both knees (N = 2976) were identified. 178 participants had baseline IAM (hand radiographs = 46, knee radiographs = 166, both = 34). An adjusted logistic regression model suggests an association between age and IAM (Odds Ratio: 1.06, 95% Confidence Interval (CI): 1.04-1.08). Presence of any IAM was not associated with whole-grade OARSI-JSN (Hazard Ratio (HR): 1.00, 95% CI: 0.73-1.37) or symptomatic progression (Estimated difference: 1.24, p-value: 0.13) in all participants. Using stratification analysis, in younger participants <60 years old, presence of any IAM was associated with radiographic progression (HR: 1.90, 95% CI: 1.01-3.60). Conclusion: Although the presence of any radiographic IAM increases with higher age and does not predict knee OA outcomes across the entire sample of OAI participants, it is associated with knee OA radiographic progression in participants aged <60.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| 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".