Ultrasound-Guided Aspiration and Corticosteroid Injection of Baker's Cysts in Knee Osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: To determine the effect on pain, function, and ultrasonographic findings of ultrasonography-guided Baker's cyst aspiration followed by corticosteroid injection in a group of patients with Baker's cyst secondary to knee osteoarthritis. DESIGN: Prospective observational study. RESULTS: Twenty-six subjects participated in this study. Clinical and instrumental evaluations were performed at baseline (T0), 1 wk (T1), and 4 wks (T2) after procedure. Mean Visual Analog Scale scores significantly dropped after the procedure (T0 = 6.2 [1.2]; T1 = 4.48 [1.5]; T2 = 4.32 [1.3]; T0 vs. T1 and P < 0.0001). A significant difference between preprocedure and postprocedure Western Ontario and McMaster Universities scores was found for pain (P < 0.0001) but not for joint stiffness (P = 0.7239) and disability (P = 0.6318). Ultrasonographic evaluation showed a significant reduction for both axial (P = 0.006) and sagittal (P = 0.01) areas of Baker's cyst, but no correlation was found between pain relief and Baker's cyst volume reduction. CONCLUSIONS: Cyst aspiration with corticosteroid injection give pain relief and cyst volume reduction in patients with Baker's cyst and concomitant knee osteoarthritis. However, when compared with current literature, our results are similar to those obtained with intra-articular knee corticosteroid injection.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".