Pharmacodynamics of warfarin in cats
Bibliographic record
Abstract
The overall purpose of this study was to evaluate the pharmacodynamic response to warfarin in cats. The specific aim was to determine if a log‐linear indirect response model ( Nagashima et al., 1969 ) used to describe the in vivo effect of warfarin in humans could be applied to cats. The pharmacokinetics of racemic warfarin were described using a non‐compartmental approach. The relationship between prothrombin complex activity (PCA) and normalized prothrombin time (PTR) was defined for feline plasma under our experimental conditions, and determined to be: %PCA=12.38+648 e−PTR/0.492. These data were then integrated and used to predict the warfarin dose associated with therapeutic anti‐coagulation defined as an International Normalized Ratio (INR) of 2.0–3.0. The maximum prothrombinopenic response to warfarin in cats after a single intravenous dose of 0.5 mg/kg occurred at 24–48 h. Pharmacodynamic modeling suggested that each cat had a narrow therapeutic range of the steady‐state concentration of total warfarin required to appropriately block prothrombin complex synthesis (median: 265.2–358.7 ng/mL). The median daily dose range predicted to yield therapeutic concentrations of warfarin was 0.061–0.088 mg/kg per day. Wide inter‐individual variations in both pharmacokinetics and pharmacodynamic response suggest that a more optimal dosing of warfarin may be possible with the development of individual pharmacokinetic/pharmacodynamic algorithms, analogous to those currently employed in human patients.
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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 | 0.000 | 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 | 0.000 |
| 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".