Telmisartan as an add-on treatment for dogs with refractory idiopathic epilepsy: a nonrandomized, uncontrolled, open-label clinical trial
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effect on seizure frequency of add-on telmisartan treatment in dogs with refractory idiopathic epilepsy. ANIMALS: 11 client-owned dogs with idiopathic epilepsy and ≥ 2 generalized seizures/mon that were currently being treated with ≥ 2 antiepileptic drugs. PROCEDURES: Telmisartan was administered at a dosage of 0.25 to 1 mg/kg, PO, every 12 hours for 4 to 16 months. Seizure frequencies before and during telmisartan treatment were recorded. RESULTS: 10 dogs completed the 4-month treatment protocol. One dog was excluded owing to a transient increase in serum creatinine concentration; no adverse effects of telmisartan were observed in the remaining 10 dogs. A reduction in seizure frequency greater than an estimated expected placebo effect of 30% was evident in 7 of the 10 dogs. Long-term (12 to 16 months) follow-up information was available for 6 dogs, of which 4 had a further reduction in seizure frequency. Differences in seizure frequency were not statistically significant. No significant difference was found in serum phenobarbital concentration throughout the treatment period in the 7 dogs that were tested. CLINICAL RELEVANCE: Telmisartan has the potential to reduce seizure frequency when administered as an add-on antiepileptic drug in dogs with refractory idiopathic epilepsy. A randomized, double-blind, placebo-controlled trial is needed to determine the true efficacy of telmisartan. On the basis of our results, a sample size of 54 dogs with refractory idiopathic epilepsy would be needed.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".