Evaluation of clinical symptoms and sonographic characteristics of femoral trochlear cartilage in primary knee osteoarthritis
Bibliographic record
Abstract
Objective: This study was designed to evaluate the clinical symptoms and sonographic characteristics of femoral trochlear cartilage in patients with knee joint osteoarthritis (OA). Methods: This cross-sectional study was conducted on 94 patients with painful primary knee OA according to the American College of Rheumatology criteria with a visual analog scale pain score of 30 mm or more. Clinical features were evaluated by a rheumatologist according to the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) criteria, and a radiologist performed ultrasonography within a week. The thickness and echogenicity grade of three cartilage regions were evaluated. Other findings such as meniscal extrusion, effusion, and Baker’s cyst were recorded. Results: The average age of patients was 60 years. The linear regression model showed a significant association of grades II and III trochlear cartilage injury with the pain index, physical activity, and WOMAC overall index. However, there was no significant association between the trochlear cartilage thickness in these three regions and the WOMAC indexes (including pain, physical activity, and the overall index). There was also no significant association between Baker’s cyst and the WOMAC indexes, but a significant association was found between meniscal extrusion and the WOMAC index (P≤0.001). Conclusion: According to our study, the echogenicity grade determined by ultrasonography of femoral trochlear cartilage affects the clinical symptoms of patients including pain. These findings indicate the role of this diagnostic device in understanding changes due to the disease, and it can help physicians focus on the pathology in order to control clinical symptoms in patients.
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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 | 0.003 |
| 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 | 0.000 |
| 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".