Effect of Gabapentin Administered With Prednisolone, Ciclosporin or a Placebo on Clinical Outcomes and Motor Activity in Cats With Atopic Skin Syndrome: A Prospective, Blinded, Placebo‐Controlled Study
Bibliographic record
Abstract
BACKGROUND: Gabapentin reportedly decreases central sensitisation, a disorder associated with chronic pruritus in humans, although this is not well documented in cats. Its combined use with the standard antipruritic therapy for feline atopic skin syndrome (FASS) is not yet described. OBJECTIVES: To evaluate the impact of prednisolone, ciclosporin or placebo, with or without gabapentin, on lesional scores and actimetry in FASS cats. ANIMALS: Twenty-six cats from a laboratory colony with naturally acquired FASS. METHODS AND MATERIALS: Following a 12-week washout period, cats were allocated to one of three groups: prednisolone (1 mg/kg, n = 9), ciclosporin (7 mg/kg, n = 8) and placebo (Avicel, n = 9). Treatments were administered orally, once daily for 5 weeks (Week [W]0 to W4), then combined with gabapentin (10-15 mg/kg) for another 3 weeks. The Feline Dermatitis Extent and Severity Index (FeDESI) was assessed at baseline and W2, W4 and W7. Actimetry was recorded and analysed over weekend (WE) time points. A repeated-measures generalised mixed model was applied using the zero-inflated negative binomial (FeDESI) or log-normal (actimetry) distribution (α = 0.05). RESULTS: Prednisolone alone significantly improved FeDESI (p = 0.008), while ciclosporin required the addition of gabapentin to achieve a significant effect (p < 0.034). Gabapentin decreased FeDESI scores in all groups (p < 0.001) and demonstrated the highest incidence rate ratio (2.59) compared to placebo. Improvements in FeDESI were associated with significant (corresponding in intensity) decreases in motor activity. CONCLUSIONS AND CLINICAL RELEVANCE: Gabapentin, particularly when combined with prednisolone or ciclosporin, may reduce lesional score and actimetry-assessed itch in FASS cats, suggesting a potential central sensitisation in some cats.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".