Effects of Botulinum Toxin Landmark‐Guided Intra‐articular Injection in Subjects With Knee Osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Increasing evidence has suggested that botulinum toxin A (BoNT/A) can inhibit the release of selected neuropeptide transmitters from primary sensory neurons. Thus, intra-articular (IA) injection therapies with BoNT/A may reduce pain in patients with knee osteoarthritis (OA). OBJECTIVE: To investigate the effects of landmark-guided IA injection of BoNT/A on patients with knee OA. DESIGN: A prospective randomized controlled trial. SETTING: A rehabilitation clinic of a private teaching hospital. PATIENTS: A total of 46 patients with symptomatic knee OA (mostly Kellgren-Lawrence grade 2-3). METHODS: The patients were randomly assigned to 1 of the following groups: BoNT/A group (BoNT/A injection; n = 21) or control group (education only; n = 20). The patients in the BoNT/A group received an IA injection of 100 units of BoNT/A into the affected knee. MAIN OUTCOME MEASURES: The short-term (1 week posttreatment) and long-term (6 months posttreatment) effects were evaluated using a pain visual analogue scale (VAS) and questionnaires concerning functional status, including the Lequesne and Western Ontario and McMaster Universities (WOMAC) indexes. RESULTS: The between-group comparison revealed significant differences with regard to the pain VAS score at 1 week (P < .001) and at 6 months (P = .001) posttreatment. Similar findings for the between-group comparison were observed for the WOMAC and Lequesne indexes at 6 months (P < .05) posttreatment. The pain VAS score in the BoNT/A group significantly decreased from 5.05 ± 1.12 (pretreatment) to 2.89 ± 1.04 at 1 week (P < .001) and 3.45 ± 1.70 at 6 months posttreatment (P < .001) but not in the control group (P = .476). CONCLUSIONS: The IA injection of BoNT/A provided pain relief and improved functional abilities in patients with knee OA in both the short- and long-term follow-up. LEVEL OF EVIDENCE: I.
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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) | 0.001 | 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) | 0.002 | 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".