Structure-symptom relationship with wide-area ultrasound scanning of knee osteoarthritis
Bibliographic record
Abstract
The aetiology of knee pain in osteoarthritis (OA) is heterogeneous and its relationship with structural changes and function is unclear. Our goal was to determine the prevalence of wide-area scanned ultrasound-defined knee OA structural features and their association with pain and functional impairment in 79 symptomatic and 63 asymptomatic subjects. All subjects underwent ultrasound knee wide-area scanning and the severity of articular cartilage degeneration, the presence and size of osteophytes, and meniscal extrusion were evaluated. Subjects filled in a self-administrated questionnaire on present knee pain, and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) on clinical symptoms and function over the past week. Cartilage changes were the most prevalent followed by lateral meniscal extrusion, osteophytes and medial meniscal extrusion. The global femoral cartilage grade associated strongly with pain and the WOMAC index. Site-specifically, early medial cartilage changes and thinning in sulcus and lateral site were associated with symptoms. The presence of femoral lateral osteophytes was also associated with both outcomes. Using the novel wide-area ultrasound scanning technique, we were able to confirm the negative impact of femoral cartilage OA changes on clinical symptoms. Presence, not necessarily size, of lateral femoral osteophytes was also associated with increased pain and 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 | 0.001 | 0.004 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".