Reference range of rivaroxaban‐calibrated anti‐Xa activity in Chinese children with giant coronary artery aneurysms after KawasakI disease: insights from a population pharmacokinetic and pharmacodynamic analysis
Bibliographic record
Abstract
Aims This study aimed to characterize the pharmacokinetics of rivaroxaban and its correlation with anti‐Xa activity and recommend reference range of anti‐Xa activity in Chinese children with giant coronary artery aneurysm (GCAA) after Kawasaki disease (KD). Methods Sparse sampling rivaroxaban concentration (C riva ) and anti‐Xa activity data from a prospective observational study conducted in the preceding population were analysed using NONMEM. The pharmacokinetic‐pharmacodynamic (PK/PD) model was developed sequentially following a PPP&D modelling approach. The patients' kinetic profiles of anti‐Xa activity were estimated by a Bayesian approach based on individual PK/PD parameters. Echocardiograms, coronary artery angiograms and clinical symptom evaluations were used to assess the effectiveness and safety of the clinically used dose regimen. Results This study included 35 children, with 145 rivaroxaban concentrations and 85 anti‐Xa measurements collected. A two‐compartment model with first‐order elimination best described the PK data. A linear model (Anti‐Xa = 0.945 × C riva + 4.37) was chosen to describe the relationship between C riva (within 0.5–500 ng/mL) and anti‐Xa activity. Anti‐Xa activity of patients, who all responded well to the medication, was regarded as the reference range for balancing the therapeutic effect and safety in Chinese paediatrics with GCAA after KD. The recommended anti‐Xa activity range is 50.9–187.3 ng/mL at peak (2–4 h after last dose), and 5.8–24.1 ng/mL at trough (22–24 h after last dose). Conclusions The developed population PK/PD model could be used to describe C riva and anti‐Xa activity simultaneously. The recommended anti‐Xa range could inform rivaroxaban use in Chinese children with GCAA after KD under dual antithrombotic therapy.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 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".