Evidence map›Paper›PMID 28409203›Full record

ReviewIntensive care medicine2017

The role of infection models and PK/PD modelling for optimising care of critically ill patients with severe infections.

T Tängdén, V Ramos Martín, T W Felton, E I Nielsen, S Marchand, R J Brüggemann, J B Bulitta, M Bassetti, U Theuretzbacher, B T Tsuji and 6 more

Abstract readReview
PubMed Publisher
In one paragraph

Review in Intensive care medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed, 1 pooled it
–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

73 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Trial
  4. Trial
  5. Trial
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. New Antibiotics Against Multidrug-Resistant Gram-Negative Bacteria in Liver Transplantation: Clinical Perspectives, Toxicity, and PK/PD Properties.Transplant international : official journal of the European Society for Organ Transplantation · 2024
    Review

13 more citing papers are in PubMed but not listed here.

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

16 authors.

T TängdénDepartment of Medical Sciences, Section of Infectious Diseases, Uppsala University, Uppsala, Sweden.
V Ramos MartínDepartment of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK.
T W FeltonIntensive Care Unit, University Hospital of South Manchester, Manchester, UK.
E I NielsenDepartment of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.
S MarchandInserm U1070, Pole Biologie Santé, Poitiers, France.
R J BrüggemannDepartment of Pharmacy, Radboud University Medical Center, Nijmegen, The Netherlands.
J B BulittaCenter for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, USA.
M BassettiInfectious Diseases Division, Santa Maria della Misericordia University Hospital and University of Udine, Udine, Italy.
U TheuretzbacherCenter for Anti-Infective Agents, Vienna, Austria.
B T TsujiSchool of Pharmacy and Pharmaceutical Sciences, University at Buffalo, State University of New York, Buffalo, USA.
D W WarehamAntimicrobial Research Group, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
L E FribergDepartment of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.
J J De WaeleDepartment of Critical Care Medicine, Ghent University Hospital, Ghent, Belgium.
V H TamDepartment of Pharmacy Practice and Translational Research, University of Houston College of Pharmacy, Houston, USA.
Jason A RobertsBurns, Trauma and Critical Care Research Centre and Centre for Translational Anti-infective Pharmacodynamics, The University of Queensland, Brisbane, Australia. j.roberts2@uq.edu.au.ORCID http://orcid.org/0000-0001-6218-435X
Infection Section for the European Society of Intensive Care Medicine, the Pharmacokinetics and Pharmacodynamics Study Group of the European Society of Clinical Microbiology and Infectious Diseases, the International Society of Anti-Infective Pharmacology and the Critically Ill Patients Study Group of European Society of Clinical Microbiology and Infectious Diseases

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Critically ill patients with severe infections are at high risk of suboptimal antimicrobial dosing. The pharmacokinetics (PK) and pharmacodynamics (PD) of antimicrobials in these patients differ significantly from the patient groups from whose data the conventional dosing regimens were developed. Use of such regimens often results in inadequate antimicrobial concentrations at the site of infection and is associated with poor patient outcomes. In this article, we describe the potential of in vitro and in vivo infection models, clinical pharmacokinetic data and pharmacokinetic/pharmacodynamic models to guide the design of more effective antimicrobial dosing regimens. Individualised dosing, based on population PK models and patient factors (e.g. renal function and weight) known to influence antimicrobial PK, increases the probability of achieving therapeutic drug exposures while at the same time avoiding toxic concentrations. When therapeutic drug monitoring (TDM) is applied, early dose adaptation to the needs of the individual patient is possible. TDM is likely to be of particular importance for infected critically ill patients, where profound PK changes are present and prompt appropriate antibiotic therapy is crucial. In the light of the continued high mortality rates in critically ill patients with severe infections, a paradigm shift to refined dosing strategies for antimicrobials is warranted to enhance the probability of achieving drug concentrations that increase the likelihood of clinical success.

Indexed as

Anti-Bacterial AgentsAminoglycosidesAnimalsbeta-LactamsBiomarkersCritical IllnessDisease Models, AnimalDose-Response Relationship, DrugDrug MonitoringGlycopeptidesHumansIntensive Care UnitsQuinolonesSeverity of Illness IndexAminoglycosidesAnti-Bacterial Agentsbeta-LactamsBiomarkersGlycopeptidesQuinolonesAntibioticsIndividualised dosingMathematical modellingPharmacodynamicsPharmacokinetics

Identifiers

PMID28409203

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.