Identifying common trajectories of joint space narrowing over two years in knee osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: Little is known about the natural history of knee osteoarthritis (OA). We sought to identify common patterns of joint space narrowing (JSN) in well-characterized knee OA patients in the placebo arm of a 2-year international study. METHODS: We performed secondary data analyses of 622 adults ages 39-80 years in North America (n = 310) and Europe (n = 312) with symptomatic knee OA. Fluoroscopically positioned semiflexed anteroposterior radiographs were obtained at 0, 12, and 24 months. Group-based trajectory modeling was used to identify distinctive groups of individuals with similar trajectories of JSN, taking into account sex, age, and body mass index. RESULTS: Seven groups were identified. Four exhibited joint space width (JSW) stability over 2 years representing the most common trajectory (71%), which was unrelated to initial JSW. Atypical courses included slow, rapid, and moderate progressors; most had significant JSN at study entry. Slow progressors (20%) had a mean JSN of 0.2 mm over 2 years. Only 2% of the sample demonstrated rapid JSN (2.1 mm), while 7% had JSN of 0.7 mm. Rapid progressors tended to be men, while slow and moderate progressors were older and heavier. CONCLUSION: Most (70%) people with OA demonstrated no significant JSN over 2 years; 20% showed slow progression, 7% had moderate, and 2% had rapid JSN. Progressors tended to have less JSW at study entry and were older and heavier; rapid progressors were more likely to be men. Understanding common patterns of the course of knee OA may offer new opportunities to target those at greatest risk of disability.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".