Pharmacokinetic and pharmacodynamic analyses of terlipressin in patients with hepatorenal syndrome
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Bibliographic record
Abstract
Abstract The objective of this population pharmacokinetics (PK) analysis was to characterize the PK of terlipressin and its active metabolite, lysine-vasopressin (L-VP), in patients with hepatorenal syndrome (HRS), following intravenous administration of terlipressin 1 mg to 2 mg every 6 h. Sparse PK samples from 69 patients with HRS who participated in terlipressin phase 3 clinical studies were used for model development. In addition, mean arterial pressure (MAP) and heart rate (HR) from 40 patients with HRS were available to explore the relationship between terlipressin and L-VP plasma concentrations and pharmacodynamic (PD) response. A two-compartment model with first-order elimination adequately described the PK of terlipressin. L-VP was well characterized as the active metabolite of terlipressin by a one-compartment model with first-order elimination. The population PK modeling results showed that the estimated clearances for terlipressin and L-VP are 27.4 L/h and 318 L/h, respectively, for a typical patient with a body weight of 86 kg. Body weight was identified as the only covariate for the clearance of terlipressin. However, simulation suggested that body weight had no clinically meaningful effects on the exposure of L-VP through terlipressin. Therefore, no weight-based dose is needed for terlipressin to treat HRS patients. PD response, change in MAP, and HR were well correlated to L-VP concentrations; compared with baseline values, the estimated maximum decrease in HR would be 10.6 bpm and the estimated maximum increase in MAP would be 16.2 mm Hg.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it