Therapeutic Effects of Intra-articular Botulinum Neurotoxin in Advanced Knee Osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Osteoarthritis (OA) is a major cause of musculoskeletal pain that causes morbidity, physical limitation, and poor quality of life. The purpose of this study was to evaluate the therapeutic effects of intra-articular (IA) injection of botulinum neurotoxin A (BoNT/A) for advanced knee OA. METHODS: Twenty-four patients (38 knees) were enrolled, and the subjects were radiographically verified as having stage III or IV OA according to the Kellgren-Lawrence classification. We used the Western Ontario and McMaster Universities Osteoarthritis Index to evaluate the therapeutic effects monthly for 6 months. BoNT/A (100 U) was reconstituted with 4.0 mL saline and was injected into the symptomatic knee joints after baseline evaluation and 3 months later. RESULTS: The therapeutic effects of BoNT/A were clinically significant at 1 month after the first injection, but statistical significance was not noted until 3 months after the first IA injection. Pain and stiffness improved clinically; however, the effect of BoNT/A achieved statistical significance only for the pain subscale in stage III OA. There was no significant difference between the stage III and IV groups. There was no significant muscle atrophy or serious adverse effect in any group after treatment. CONCLUSION: IA BoNT/A provides a new therapeutic option for refractory pain in patients with advanced knee OA. Although IA BoNT/A appears to be effective and safe for the management of advanced knee OA, these results cannot be generalized to patients with mild knee joint pain or nonspecific soft tissue pain in the knee joint region.
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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 | 0.000 |
| 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".