Use of vagal nerve stimulation as a treatment for refractory epilepsy in dogs
Bibliographic record
Abstract
OBJECTIVE: To evaluate safety and efficacy of vagal nerve stimulation in dogs with refractory epilepsy. DESIGN: Placebo-controlled, double-masked, crossover study. ANIMALS: 10 dogs with poorly controlled seizures. PROCEDURE: A programmable pacemaker-like device designed to deliver intermittent stimulation to the left cervical trunk of the vagus was surgically implanted in each dog. Dogs were assigned randomly to two 13-week test periods, 1 with nerve stimulation and 1 without nerve stimulation. Owners recorded data on seizure frequency, duration, and intensity, as well as adverse effects. RESULTS: No significant difference in seizure frequency, duration, or severity was detected between overall 13-week treatment and control periods. During the final 4 weeks of the treatment period, a significant decrease in mean seizure frequency (34.4%) was detected, compared with the control period. Complications included transient bradycardia, asystole, and apnea during intraoperative device testing, and seroma formation, subcutaneous migration of the generator, and transient Horner's syndrome during the 14-day period between surgery and suture removal. No adverse effects of stimulation were detected, and most owners were satisfied with the treatment. CONCLUSIONS AND CLINICAL RELEVANCE: Vagal nerve stimulation is a potentially safe approach to seizure control that appears to be efficacious in certain dogs and should be considered a possible treatment option when antiepileptic medications are ineffective.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".