Comparative study on efficacy of antiepileptic drugs in canine epilepsy
Bibliographic record
Abstract
The current study aimed to assess the prevalence of canine epilepsy in and around Bidar, investigate associated hematological and biochemical changes and to evaluate the efficacy of phenobarbital sodium and levetiracetam in managing the condition. The study was carried out at the Veterinary Clinical Complex, Veterinary College, Bidar, from March 2021 to August 2024, analyzed a total of 7,005 canine cases. Among these, 46 cases of epilepsy were identified, resulting in an overall prevalence rate of 0.66 per cent. Male dogs and those aged 6 months to 6 years exhibited the highest prevalence. Non-descript breeds were most affected, followed by Spitz and Labrador Retrievers. Dogs were randomly divided into two groups for treatment: Group I received phenobarbital sodium (3 mg/kg BW, twice daily) and Group II was treated with levetiracetam (15 mg/kg BW, three times daily). A control group of healthy dogs was used for hematological and biochemical comparisons. No significant differences in hemoglobin, total erythrocyte count, or major biochemical parameters were found between epileptic and control dogs. However, a significant increase in total leukocyte count and a significant decrease in magnesium levels were observed in epileptic dogs. In the present investigation, levetiracetam demonstrated superior efficacy, with 83.33 per cent of dogs achieving recovery by Day 30, compared to 66.67 per cent in the phenobarbital group. This research highlights levetiracetam's better therapeutic response in managing canine epilepsy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".