Effects of physiological covariables on pharmacokinetic parameters of clomipramine in a large population of cats after a single oral administration
Bibliographic record
Abstract
This study was conducted to confirm an interindividual variability in pharmacokinetic parameters of clomipramine in a large population of cats and to identify potential covariables that would explain the presence of such pharmacokinetic variability after a single dose of Clomicalm. Clomipramine hydrochloride was administered orally according to a weight-dose chart from 0.32 to 0.61 mg/kg, to 76 cats and five blood samples were then taken by direct venipuncture at 1, 3, 6, 12, and 24 h. Plasma concentrations of clomipramine and desmethylclomipramine (DCMP) were measured by LC-MS/MS. The Standard Two-Stage technique was used to assess differences and detect correlations between pharmacokinetic parameter estimates and individual covariables. A large interindividual variability in all pharmacokinetic parameters (CV% 64-124) was detected. Statistically significant gender-related differences were detected in MR and Cl/F, where female cats had a higher mean MR (0.53) and faster Cl/F (0.36 L/h.kg) than males (0.36 and 0.21 L/h.kg, respectively). No correlation could be found between clomipramine AUC0-24 h or DCMP AUC0-24 h and sedation scores. Further feline studies are required to assess these findings after multiple dosing of clomipramine and DCMP to allow clinical extrapolation.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 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".