Effect of Intrathecal Baclofen Bolus Injection on Ankle Muscle Activation During Gait in Patients With Acquired Brain Injury
Bibliographic record
Abstract
BACKGROUND: Intrathecal baclofen (ITB) bolus injection effectively decreases spinal excitability but the impact on lower limb muscle activation during gait has not been thoroughly investigated. OBJECTIVE: Examine activation of medial gastrocnemius (MG) and tibialis anterior (TA) muscles during gait before and after ITB bolus injection in patients with resting hypertonia after acquired brain injury. METHODS: Lower extremity Ashworth score, temporospatial gait parameters, characteristics of the linear relationship between electromyogram (EMG) and lengthening velocity (LV) in MG during stance, and the duration and magnitude of TA-MG coactivation were assessed before and at 2, 4, and 6 hours after a 50-µg ITB injection via lumbar puncture in 8 hemorrhagic stroke and 11 traumatic brain injury subjects. RESULTS: Temporospatial gait parameters did not significantly differ across the evaluation points (P ≥ .170). However, Ashworth score (P < .001), frequency and gain of significant positive EMG-LV slope (P ≤ .020), and duration of TA-MG coactivation (P ≤ .013) significantly decreased in the more-affected leg after ITB bolus. EMG changes were not significantly different between patients who did (n = 10) and did not (n = 9) increase gait speed after the injection. The timing of the largest decrease in Ashworth score and the largest decrease in EMG parameters coincided in 36% of cases, on average. CONCLUSIONS: ITB bolus injection alters the activation of MG and TA during gait. However, the changes in muscle activation are not closely related to the changes in gait speed or resting muscle hypertonia. The analysis of ankle muscle activation during gait better characterizes the response to ITB bolus injection than gait kinematics.
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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 | 0.001 |
| 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".