Abstract TMP34: OnabotulinumtoxinA Treatment in Post-stroke Lower Limb Spasticity: Long-term Results From a Phase 3 Study
Bibliographic record
Abstract
Introduction: Long-term efficacy of onabotulinumtoxinA (onabotA) in post-stroke lower limb spasticity (PSLLS) is not clearly established. Hypothesis: OnabotA provides sustained efficacy in PSLLS. Methods: A multicenter, phase 3, 12-week, double-blind (DB), placebo-controlled study of patients with ankle PSLLS (Modified Ashworth Scale [MAS] ≥3) was followed by an open-label (OL) extension, during which all patients received 1-3 treatment cycles (∼12-week intervals) of onabotA (≤400U). Endpoints: change from baseline in MAS and Clinical Global Impression of Change (CGI) physician rating, and percent of patients achieving passive and active goals (Goal Attainment Scale [GAS]) by physician and patient. Results: 468 patients enrolled (onabotA, n=233; placebo, n=235); 447 (95.5%) completed the DB and 249 (53.2%) completed the OL phase at DB database lock. Significant improvement in MAS achieved with onabotA in DB was sustained in OL phase (Table). Significant improvements in CGI in DB continued to improve in OL phase. During OL phase, MAS ankle change from baseline and CGI by physician raw scores and proportions of responders were largest at week 6 and generally increased over 3 OL treatment cycles. With onabotA, GAS by patient improved ( P =0.036), as did the proportion that progressed toward active ( P =0.009) and passive ( P =0.044) goal attainment by physician. The percentage of patients who met passive and active goals (GAS by physician≥0) after 1 onabotA treatment increased from 40% to 64% and 27% to 65%, respectively, after 4 treatments. Common DB treatment-related AEs (onabotA vs placebo): injection-site pain (1.7% vs 0.9%) and pain in extremity (0.4% vs 2.1%). Conclusions: OnabotA was well-tolerated and produced improvements in MAS, CGI, and GAS during the DB phase that continued into the OL phase, demonstrating long-term benefits in patients with PSLLS.
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".