Ultrasonographic evaluation in symptomatic knee osteoarthritis: clinical and radiological correlation
Bibliographic record
Abstract
AIM: To explore the relationship among clinical, radiological and ultrasonographical findings in knee osteoarthritis (OA). METHOD: Sixty-one patients (122 knees) with knee OA were enrolled. Patients' knees were classified into two groups according to symptom severity. Group I consisted of 61 more symptomatic knees and Group II comprised 61 less symptomatic knees. Subjects were clinically assessed for pain and functional status by using a visual analog scale and the Western Ontario and McMaster Universities Arthritis Index (WOMAC), respectively. Knee radiographs were evaluated by using the Kellgren-Lawrence (K-L) grading system. All knees were also evaluated ultrasonographically for meniscal bulging, distal femoral cartilage thickness, cartilage grading and also for the presence of effusion, Baker's cyst and so on. RESULTS: Baker's cyst and joint effusion were observed more in Group I when compared with Group II. Positive correlations were found between meniscal bulging and all WOMAC scores (all P < 0.05). K-L grades of the patients were also positively correlated with WOMAC scores (all P < 0.05). Meniscal bulging measurements and K-L grades were positively correlated (P < 0.001). There was a negative correlation between cartilage grades and cartilage thickness measurements (all P < 0.001). CONCLUSIONS: We found that joint space narrowing seemed to be associated with meniscal bulging. Moreover, increased meniscal bulging and presence of Baker's cyst/joint effusion were associated with worse pain or poorer function.
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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 | 0.001 | 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".