PRE AND POST TREATMENT COMPARATIVE STUDY OF MENISCUS TEARS TREATED WITH INTRAARTICULAR STEROID INJECTION
Bibliographic record
Abstract
Objective: To evaluate the safety and efficacy of long-term intraarticular (IA) steroid injections for knee pain related to meniscus tear. Methods: In this study 50 patients with meniscus tear of the knee received IA injections of triamcinolone acetonide 40 mg (50 patients) into the knee every 3 months for up to 2 years. The clinical efficacy measure of primary interest was the pain subscale from the Western Ontario and McMaster Universities OA Index (WOMAC). Efficacy measures of secondary interest were the total score on the WOMAC, physician's global assessment, patient's global assessment, patient's assessment of pain, range of motion (ROM) of the affected knee, and 50-foot walking time. Clinical symptoms were assessed just before each injection. Results: The steroid-injected knees showed a trend toward greater symptom improvement, especially at 1 year, for the WOMAC pain subscale, night pain, and ROM values (P <0.001). Using area under the curve analyses, knee pain and stiffness were significantly improved throughout the 2-year study by repeated injections of triamcinolone acetonide in type1, type2 and degenerative meniscus tear. Conclusion: This study support long-term safety of IA steroid injections for patients with symptomatic knee with meniscus tear without any deleterious effects. It is also clinically effective to relive symptoms.
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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) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".