Evidence map›Paper›PMID 29572663›Full record

ArticleClinical pharmacokinetics2019

The Influence of Normalization Weight in Population Pharmacokinetic Covariate Models.

Sebastiaan C Goulooze, Swantje Völler, Pyry A J Välitalo, Elisa A M Calvier, Leon Aarons, Elke H J Krekels, Catherijne A J Knibbe

Abstract read
In one paragraph

Article in Clinical pharmacokinetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Review
  2. Strategies for pediatric dose derivation from population pharmacokinetic models.Journal of pharmacokinetics and pharmacodynamics · 2026
    Article
  3. Article
  4. Article
  5. Semi-mechanistic PK/PD modelling of meropenem and sulbactam combination against carbapenem-resistant strains of Acinetobacter baumannii.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2021
    Article
  6. Observational
  7. Article
  8. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Sebastiaan C GouloozeDivision of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
Swantje VöllerDivision of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
Pyry A J VälitaloDivision of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
Elisa A M CalvierDivision of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
Leon AaronsDivision of Pharmacy and Optometry, University of Manchester, Manchester, UK.
Elke H J KrekelsDivision of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
Catherijne A J KnibbeDivision of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands. c.knibbe@antoniusziekenhuis.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In covariate (sub)models of population pharmacokinetic models, most covariates are normalized to the median value; however, for body weight, normalization to 70 kg or 1 kg is often applied. In this article, we illustrate the impact of normalization weight on the precision of population clearance (CL

Indexed as

Body WeightModels, BiologicalPharmacokineticsAdultHumansInfant, NewbornObesityPhenobarbitalPhenobarbital

Identifiers

PMID29572663
PMCPMC6325985

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.