Evidence map›Paper›PMID 31956969›Full record

ArticleClinical pharmacokinetics2020

Population Pharmacokinetics of Imipenem in Critically Ill Patients: A Parametric and Nonparametric Model Converge on CKD-EPI Estimated Glomerular Filtration Rate as an Impactful Covariate.

Femke de Velde, Brenda C M de Winter, Michael N Neely, Walter M Yamada, Birgit C P Koch, Stephan Harbarth, Elodie von Dach, Teun van Gelder, Angela Huttner, Johan W Mouton and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Clinical pharmacokinetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 20% of its field
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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Review
  6. Article
  7. Population pharmacokinetics and dosing optimisation of imipenem in critically ill patients.European journal of hospital pharmacy : science and practice · 2024
    Article
  8. Article
  9. Article
  10. Article
  11. Observational
  12. Article
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  14. Review
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

11 authors at 3 institutions in 3 countries.

Femke de VeldeDepartment of Medical Microbiology and Infectious Diseases, Erasmus University Medical Center, Rotterdam, The Netherlands. f.develde@erasmusmc.nl.ORCID 0000-0003-4581-9688
Brenda C M de WinterDepartment of Hospital Pharmacy, Erasmus University Medical Center, Rotterdam, The Netherlands.
Michael N NeelyChildren's Hospital Los Angeles, University of Southern California Keck School of Medicine, Los Angeles, CA, USA.
Walter M YamadaChildren's Hospital Los Angeles, University of Southern California Keck School of Medicine, Los Angeles, CA, USA.
Birgit C P KochDepartment of Hospital Pharmacy, Erasmus University Medical Center, Rotterdam, The Netherlands.
Stephan HarbarthDivision of Infectious Diseases, Geneva University Hospitals, Faculty of Medicine, Geneva, Switzerland.
Elodie von DachDivision of Infectious Diseases, Geneva University Hospitals, Faculty of Medicine, Geneva, Switzerland.
Teun van GelderDepartment of Hospital Pharmacy, Erasmus University Medical Center, Rotterdam, The Netherlands.
Angela HuttnerDivision of Infectious Diseases, Geneva University Hospitals, Faculty of Medicine, Geneva, Switzerland.
Johan W MoutonDepartment of Medical Microbiology and Infectious Diseases, Erasmus University Medical Center, Rotterdam, The Netherlands.
COMBACTE-NET consortium
Erasmus MC · NLUniversity Hospital of Geneva · CHUniversity of Southern California · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPopulation pharmacokinetic (popPK) models for antibiotics are used to improve dosing strategies and individualize dosing by therapeutic drug monitoring. Little is known about the differences in results of parametric versus nonparametric popPK models and their potential consequences in clinical practice. We developed both parametric and nonparametric models of imipenem using data from critically ill patients and compared their results.

methodsTwenty-six critically ill patients treated with intravenous imipenem/cilastatin were included in this study. Median estimated glomerular filtration rate (eGFR) measured by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation was 116 mL/min/1.73 m

resultsFor both methods, data were best described by a model with two distribution compartments and the CKD-EPI eGFR equation unadjusted for body surface area as a covariate on the elimination rate constant (K

conclusionsBoth models described imipenem popPK well; the parameter estimates were comparable and the included covariate was identical. However, estimated BSV was higher in the nonparametric model. This may have consequences for estimated exposure during dosing simulations and should be further investigated in simulation studies.

Indexed as

Anti-Bacterial AgentsGlomerular Filtration RateImipenemRenal Insufficiency, ChronicAdultCritical IllnessFemaleHumansMaleMiddle AgedAnti-Bacterial AgentsImipenem

Identifiers

PMID31956969
PMCPMC7329758
OpenAlexW3001351827

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.