Effect of treating elbow flexor spasticity with botulinum toxin injection and adjunctive casting on hemiparetic gait parameters: A prospective case series
Bibliographic record
Abstract
OBJECTIVE: To investigate changes in hemiparetic gait parameters after treatment of elbow flexor spasticity with botulinum neurotoxin (BoNT) injection and adjunctive casting. DESIGN: Prospective case series. SUBJECTS: Ten participants with spasticity secondary to acquired brain injury (8 stroke, 2 traumatic brain injury). INTERVENTIONS: Participants received BoNT injections for their spastic elbow flexors under ultrasound guid-ance. Two weeks post-injection, an elbow stretching cast was applied for 1 week. OUTCOME MEASURES: Assessments using the Modified Ashworth Scale (MAS), Tardieu scale V1 angle of arrest at slow speed and V3 angle of catch at fast speed, 2-min walk test (2MWT), Edinburgh Gait Score scale (EGS) and video gait analysis for step-length symmetry were conducted pre-BoNT injection (t0) and at cast removal (t1). Goal attainment scale (GAS) was used to assess changes in spasticity and gait 3 months post-injection (t2). RESULTS: At t1, participants showed a mean increase of 16.7° (p < 0.01) on the Tardieu Scale V3 and a mean reduction of 0.5 points on the MAS (p < 0.05). There was also a mean reduction on EGS of 2.7 points (p < 0.05), and a mean increase on 2MWT of 3.1 m (p < 0.05). On the GAS, all participants report-ed impro-ved gait at t2 and 80% reported a decrease in spasticity. CONCLUSION: Combining BoNT injection with casting for treatment of elbow flexor spasticity without treat-ing the lower limb may improve hemiparetic gait parameters.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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".