Evidence map›Paper›PMID 29569104›Full record

ReviewDrugs2018

Individualising Therapy to Minimize Bacterial Multidrug Resistance.

A J Heffernan, F B Sime, J Lipman, J A Roberts

Registry-linked trialAbstract readReview
PubMed Publisher
In one paragraph

Review in Drugs, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04450680 (A Prospective Cohort Study on Beta-lactam Therapeutic Drug Monitoring in Singapore), which is not on this map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 12% 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.

NCT04450680 unknown statusnot on this mapstarted 2019, after this paper: background citation

A Prospective Cohort Study on Beta-lactam Therapeutic Drug Monitoring in Singapore

TypeobservationalSponsorSingapore General HospitalRan2019 to 2022Enrolled80ConditionsInfection, BacterialArmsBeta-lactam Therapeutic Drug Monitoring
3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 1 synthesis or guideline pooled it, 57 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
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  13. Review
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  17. Postantifungal Effect of Antifungal Drugs againstJournal of fungi (Basel, Switzerland) · 2022
    Review
  18. Review
  19. Pharmaceutics · 2021
    Article
  20. Article
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

4 authors at 2 institutions in 1 country.

A J HeffernanSchool of Medicine, Griffith University, Gold Coast, Queensland, Australia.ORCID http://orcid.org/0000-0002-7929-9812
F B SimeCentre for Translational Anti-Infective Pharmacodynamics, School of Pharmacy, The University of Queensland, Brisbane, Queensland, Australia.
J LipmanUQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Building 71/918, Herston Rd, Herston, Queensland, 4029, Australia.
J A RobertsCentre for Translational Anti-Infective Pharmacodynamics, School of Pharmacy, The University of Queensland, Brisbane, Queensland, Australia. j.roberts2@uq.edu.au.
The University of Queensland · AUGriffith University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The scourge of antibiotic resistance threatens modern healthcare delivery. A contributing factor to this significant issue may be antibiotic dosing, whereby standard antibiotic regimens are unable to suppress the emergence of antibiotic resistance. This article aims to review the role of pharmacokinetic and pharmacodynamic (PK/PD) measures for optimising antibiotic therapy to minimise resistance emergence. It also seeks to describe the utility of combination antibiotic therapy for suppression of resistance and summarise the role of biomarkers in individualising antibiotic therapy. Scientific journals indexed in PubMed and Web of Science were searched to identify relevant articles and summarise existing evidence. Studies suggest that optimising antibiotic dosing to attain defined PK/PD ratios may limit the emergence of resistance. A maximum aminoglycoside concentration to minimum inhibitory concentration (MIC) ratio of > 20, a fluoroquinolone area under the concentration-time curve to MIC ratio of > 285 and a β-lactam trough concentration of > 6 × MIC are likely required for resistance suppression. In vitro studies demonstrate a clear advantage for some antibiotic combinations. However, clinical evidence is limited, suggesting that the use of combination regimens should be assessed on an individual patient basis. Biomarkers, such as procalcitonin, may help to individualise and reduce the duration of antibiotic treatment, which may minimise antibiotic resistance emergence during therapy. Future studies should translate laboratory-based studies into clinical trials and validate the appropriate clinical PK/PD predictors required for resistance suppression in vivo. Other adjunct strategies, such as biomarker-guided therapy or the use of antibiotic combinations require further investigation.

Indexed as

AminoglycosidesAnti-Bacterial AgentsBiomarkersDrug Resistance, Multiple, BacterialDrug Therapy, CombinationFluoroquinolonesHumansMicrobial Sensitivity TestsMolecular Targeted TherapyPrecision MedicineProcalcitoninAminoglycosidesAnti-Bacterial AgentsBiomarkersFluoroquinolonesProcalcitonin

Identifiers

PMID29569104
OpenAlexW2790320770

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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.