Comparison of Agonist vs. Antagonist Stimulation on Triceps Surae Spasticity in Spinal Cord
Bibliographic record
Abstract
Objectives: One of the most common and disabling complications that affects individuals with spinal cord injury is spasticity.The purpose of this study is to compare the effect of agonist and antagonist electrical stimulations on triceps surae muscle spasticity in patients with spinal cord injury.Methods: A total of 30 subjects with spinal cord injury were considered for the study.They were divided into two groups randomly.Group 1 received agonist electrical stimulation (stimulation of triceps surae) and group 2 received antagonist electrical stimulation (stimulation of tibialis anterior) for 20 min, once daily, and 5 days per week for two weeks.To evaluate the therapeutic effect, modified Ashworth score, deep tendon reflex score and clonus score were tested before and after the treatment.Post treatment evaluation was made 24 h after the last treatment session.Results: Both the groups showed significant reductions in the modified Ashworth scores and deep tendon reflex scores after the intervention, but these reductions were not found in the clonus score.Also, there was no significant difference in the post intervention scores of modified Ashworth scale, deep tendon reflex and clonus score between the two groups.Discussion: This study provides evidence that both agonist electrical stimulation and antagonist electrical stimulations are equally effective in reducing spasticity in triceps surae muscle in patients with spinal cord injury.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| 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".