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Population pharmacokinetics of intravenous pantoprazole in paediatric intensive care patients

2009· article· en· W2055420509 on OpenAlexaff
Géraldine Pettersen, Samer Mouksassi, Yves Théorêt, Line Labbé, Christophe Fauré, Bao Nguyen, Catherine Litalien

Bibliographic record

VenueBritish Journal of Clinical Pharmacology · 2009
Typearticle
Languageen
FieldMedicine
TopicAntibiotics Pharmacokinetics and Efficacy
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsPantoprazoleNONMEMMedicinePharmacokineticsPopulationVolume of distributionIntensive care unitOmeprazoleIntensive careCYP2C19Proton-pump inhibitorPharmacologyInternal medicineAnesthesiaIntensive care medicine

Abstract

fetched live from OpenAlex

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT: The use of intravenous pantoprazole, a proton pump inhibitor, has been increasing in the paediatric intensive care unit. Despite this increased use, data on the disposition of intravenous pantoprazole in paediatric intensive care patients are very scarce. WHAT THIS STUDY ADDS: Our population approach has determined the pharmacokinetic parameters of intravenous pantoprazole in paediatric intensive care patients and the relative importance of factors influencing its disposition. Pantoprazole clearance was significantly influenced by developmental changes and by the presence of systemic inflammatory syndrome, hepatic dysfunction and CYP2C19 inhibitors. AIMS: To characterize the pharmacokinetics of intravenous pantoprazole in a paediatric intensive care population and to determine the influence of demographic factors, systemic inflammatory response syndrome (SIRS), hepatic dysfunction and concomitantly used CYP2C19 inducers and inhibitors on the drug's pharmacokinetics. METHODS: A total of 156 pantoprazole concentration measurements from 20 patients (10 days to 16.4 years of age) at risk for or with upper gastrointestinal bleeding, who received pantoprazole doses ranging from 19.9 to 140.6 mg/1.73 m(2)/day, were analysed using a population pharmacokinetic approach (nonmem program). RESULTS: The best structural model for pantoprazole was a two-compartment model with zero order infusion and first-order elimination. Body weight, SIRS, age, hepatic dysfunction and presence of CYP2C19 inhibitors were significant covariates affecting clearance (CL), accounting for 75% of interindividual variability. Only body weight significantly influenced central volume of distribution (V(c)). In the final population model, the estimated CL and V(c) were 5.28 l h(-1) and 2.22 l, respectively, for a typical 5-year-old child weighing 20 kg. Pantoprazole CL increased with weight and age, whereas the presence of SIRS, CYP2C19 inhibitors and hepatic dysfunction, when present separately, significantly decreased pantoprazole CL by 62.3, 65.8 and 50.5%, respectively. For patients aged between 6 months and 5 years without SIRS, CYP2C19 inhibitor or hepatic dysfunction, the predicted pantoprazole CL is faster than that reported in adults. CONCLUSION: These results provide important information for physicians regarding selection of a starting dose and dosing regimens of pantoprazole for paediatric intensive care patients based on factors frequently encountered in this population.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.028
GPT teacher head0.393
Teacher spread0.365 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations22
Published2009
Admission routes1
Has abstractyes

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