Enalapril and Enalaprilat Pharmacokinetics in Children with Heart Failure Due to Dilated Cardiomyopathy and Congestive Heart Failure after Administration of an Orodispersible Enalapril Minitablet (LENA-Studies)
Bibliographic record
Abstract
Angiotensin-converting enzyme inhibitors (ACEI), such as enalapril, are a cornerstone of treatment for pediatric heart failure which is still used off-label. Using a novel age-appropriate formulation of enalapril orodispersible minitablets (ODMTs), phase II/III open-label, multicenter pharmacokinetic (PK) bridging studies were performed in pediatric patients with heart failure due to dilated cardiomyopathy (DCM) and congenital heart disease (CHD) in five participating European countries. Children were treated for 8 weeks with ODMTs according to an age-appropriate dosing schedule. The primary objective was to describe PK parameters (area under the curve (AUC), maximal concentration (Cmax), time to reach maximal concentration (t-max)) of enalapril and its active metabolite enalaprilat. Of 102 patients, 89 patients (n = 26, DCM; n = 63 CHD) were included in the primary PK endpoint analysis. Rate and extent of enalapril and its active metabolite enalaprilat were described and etiology and age could be identified as potential PK modifying factors. The dosing schedule appeared to be tolerated well and did not result in any significant drug-related serious adverse events. The PK analysis and the lack of severe safety events supports the applied age-appropriate dosing schedule for the enalapril ODMTs.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".