The frequency and severity of ultrasound-detected osteoarthritis features in the knees and their associations with pain: Cross-sectional analyses of the Nor-Hand study
Bibliographic record
Abstract
Objective: To investigate the frequency and severity of ultrasound-detected osteophytes and synovitis in people with and without knee osteoarthritis (OA), and to explore the association between these ultrasound features and pain. Design: In the Nor-Hand study, both knees were assessed for osteophytes (0-3 scale, four locations per knee) and grey-scale synovitis (0-3 scale). The frequency and severity of the ultrasound-detected features were compared in individuals with and without knee OA defined by the American College of Rheumatology criteria. Pain was self-reported in each knee (yes/no) and by the Western/Ontario McMaster University index (WOMAC). The associations between ultrasound-detected features and pain were examined by regression analyses adjusted for age, sex, and body mass index. Results: We analyzed 286 participants. Osteophytes of all sizes were more common in participants with knee OA compared to those without (65.9 % vs. 40.8 %, p < 0.001). No between-group difference was found for the frequency of any grey-scale synovitis (45.5 % vs. 44.7 %, p = 0.67), while severe synovitis was more common in those with knee OA. Ultrasound-detected osteophyte sum score, but not synovitis, was associated with WOMAC pain (B = 0.18, 95 % CI 0.03-0.32). Osteophytes of all sizes were associated with pain in the same knee with odds ratio (OR, 95 % CI) ranging from 1.85 (1.20-2.84) to 9.02 (4.04-20.10). Statistically significant association was found for severe synovitis only (OR = 6.63, 95 % CI 2.26-19.43). Conclusions: Ultrasound-detected osteophytes were prevalent in people with knee OA and were associated with pain. OA pathology in individuals without fulfilling the knee OA criteria may reflect early or subclinical OA.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| 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".