Evaluation of soft tissue release in mild-to-moderate medial knee osteoarthritis in the presence of medial synovial plica, using clinical and MRI parameters
Bibliographic record
Abstract
Abstract Objective. To evaluate the clinical outcomes of an arthroscopic soft tissue release procedure for the treatment of mild to moderate knee osteoarthritis. Materials and methods. This study involved 40 subjects who underwent arthroscopic release in knee osteoarthritis including Kellgren–Lawrence grades 2 and 3 between January 2019 and January 2021. The Western Ontario and McMaster Universities (WOMAC) scores at baseline and at 6 months following surgery were recorded. Magnetic resonance imaging (MRI) was performed pre- and postoperatively (6 months). The parameters for patellar instability, including patellar tilt angle, bisect offset, tibial tuberosity–trochlear groove distance and the Insall–Salvati ratio, were measured preoperatively and postoperatively. Quantitative measurements of bone marrow lesions were also conducted. Results. The mean WOMAC score for pain and the total score improved statistically 6 months after surgery. The pain and overall scores improved significantly (reductions of 64.6% and 39.3%, respectively) at 6 months. Pain score improved from 7.0 ± 3.0 to 2.5 ± 2.8 (P < 0.05), with the total score improving from17.8 ± 10.3 to 10.8 ± 10.6 (P < 0.05). Bone marrow lessions decreased from 8503 mm3 to 2250 mm3 (P < 0.05). Patellar tilt decreased from 5.11 to 4.24 (P < 0.05). The Insall–Salvati ratio decreased significantly from 1.13 ± 0.13 to 1.08 ± 0.12 (P < 0.05). Conclusion. Overall, the results suggest that soft tissue release has clinical symptoms and structure-modifying effects in patients with knee osteoarthritis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".