Evidence map›Paper›PMID 38478027›Full record

Trial reportIntensive care medicine2024

Achievement of therapeutic antibiotic exposures using Bayesian dosing software in critically unwell children and adults with sepsis.

Ming G Chai, Quyen Tu, Menino O Cotta, Michelle J Bauer, Ross Balch, Charles Okafor, Tracy Comans, Peter Kruger, Jason Meyer, Kiran Shekar and 20 more

Erratum issuedOpen access · hybridAbstract readClinical TrialMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Intensive care medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.8field-weighted citation impact, top 17% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

30 authors at 8 institutions in 5 countries.

Ming G ChaiUQ Centre for Clinical Research, The University of Queensland, Brisbane, QLD, Australia.
Quyen TuUQ Centre for Clinical Research, The University of Queensland, Brisbane, QLD, Australia.
Menino O CottaUQ Centre for Clinical Research, The University of Queensland, Brisbane, QLD, Australia.
Michelle J BauerUQ Centre for Clinical Research, The University of Queensland, Brisbane, QLD, Australia.
Ross BalchUQ Centre for Clinical Research, The University of Queensland, Brisbane, QLD, Australia.
Charles OkaforCentre for Health Services Research, The University of Queensland, Brisbane, Australia.
Tracy ComansCentre for Health Services Research, The University of Queensland, Brisbane, Australia.
Peter KrugerIntensive Care Unit, Princess Alexandra Hospital, Brisbane, QLD, Australia.
Jason MeyerIntensive Care Unit, Princess Alexandra Hospital, Brisbane, QLD, Australia.
Kiran ShekarAdult Intensive Care Services and Critical Care Research Group, The Prince Charles Hospital, Brisbane, QLD, Australia.
Kara BradyAdult Intensive Care Services and Critical Care Research Group, The Prince Charles Hospital, Brisbane, QLD, Australia.
Cheryl FourieDepartment of Infectious Diseases, Royal Brisbane and Women's Hospital, Brisbane, QLD, Australia.
Natalie SharpPaediatric Intensive Care Unit, Queensland Children's Hospital, South Brisbane, QLD, Australia.
Luminita VladUQ Centre for Clinical Research, The University of Queensland, Brisbane, QLD, Australia.
David WhileyUQ Centre for Clinical Research, The University of Queensland, Brisbane, QLD, Australia.
Jacobus P J UngererDepartment of Chemical Pathology, Pathology Queensland, Brisbane, QLD, Australia.
Brett C McwhinneyDepartment of Chemical Pathology, Pathology Queensland, Brisbane, QLD, Australia.
Andras FarkasOptimum Dosing Strategies, Bloomingdale, NJ, 07403, USA.
David L PatersonUQ Centre for Clinical Research, The University of Queensland, Brisbane, QLD, Australia.
Julia E ClarkInfection Management and Prevention Service, Queensland Children's Hospital, Brisbane, Australia.
Krispin HajkowiczDepartment of Infectious Diseases, Royal Brisbane and Women's Hospital, Brisbane, QLD, Australia.
Sainath RamanPaediatric Intensive Care Unit, Queensland Children's Hospital, South Brisbane, QLD, Australia.
Seweryn BialasiewiczSchool of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, QLD, Australia.
Jeffrey LipmanUQ Centre for Clinical Research, The University of Queensland, Brisbane, QLD, Australia.
Brian M FordeUQ Centre for Clinical Research, The University of Queensland, Brisbane, QLD, Australia.
Patrick N A HarrisUQ Centre for Clinical Research, The University of Queensland, Brisbane, QLD, Australia.
Luregn J SchlapbachPaediatric Intensive Care Unit, Queensland Children's Hospital, South Brisbane, QLD, Australia.
Lachlan CoinDepartment of Microbiology and Immunology, University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia.
Jason A Roberts *UQ Centre for Clinical Research, The University of Queensland, Brisbane, QLD, Australia.
Adam D Irwin *UQ Centre for Clinical Research, The University of Queensland, Brisbane, QLD, Australia. a.irwin@uq.edu.au.ORCID 0000-0001-8974-6789
The University of Queensland · AUQueensland Health · AUChildren's Health Queensland Hospital and Health Service · AUPrince Charles Hospital · AUPrincess Alexandra Hospital · AURoyal Brisbane and Women's Hospital · AUSt. Clare Hospital in Lakewood · USUniversity Children's Hospital Zurich · CH

Funding

National Health and Medical Research Council APP1161657National Health and Medical Research Council APP1197743National Health and Medical Research Council APP2002981National Health and Medical Research Council APP2007007
6 · The paper itself

Abstract

purposeEarly recognition and effective treatment of sepsis improves outcomes in critically ill patients. However, antibiotic exposures are frequently suboptimal in the intensive care unit (ICU) setting. We describe the feasibility of the Bayesian dosing software Individually Designed Optimum Dosing Strategies (ID-ODS™), to reduce time to effective antibiotic exposure in children and adults with sepsis in ICU.

methodsA multi-centre prospective, non-randomised interventional trial in three adult ICUs and one paediatric ICU. In a pre-intervention Phase 1, we measured the time to target antibiotic exposure in participants. In Phase 2, antibiotic dosing recommendations were made using ID-ODS™, and time to target antibiotic concentrations were compared to patients in Phase 1 (a pre-post-design).

results175 antibiotic courses (Phase 1 = 123, Phase 2 = 52) were analysed from 156 participants. Across all patients, there was no difference in the time to achieve target exposures (8.7 h vs 14.3 h in Phase 1 and Phase 2, respectively, p = 0.45). Sixty-one courses in 54 participants failed to achieve target exposures within 24 h of antibiotic commencement (n = 36 in Phase 1, n = 18 in Phase 2). In these participants, ID-ODS™ was associated with a reduction in time to target antibiotic exposure (96 vs 36.4 h in Phase 1 and Phase 2, respectively, p < 0.01). These patients were less likely to exhibit subtherapeutic antibiotic exposures at 96 h (hazard ratio (HR) 0.02, 95% confidence interval (CI) 0.01-0.05, p < 0.01). There was no difference observed in in-hospital mortality.

conclusionsDosing software may reduce the time to achieve target antibiotic exposures. It should be evaluated further in trials to establish its impact on clinical outcomes.

Indexed as

Anti-Bacterial AgentsSepsisAdultBayes TheoremChildCritical IllnessHumansIntensive Care Units, PediatricProspective StudiesSoftwareAnti-Bacterial AgentsAntibioticsDosing softwarePharmacokinetic–pharmacodynamicSepsis

Identifiers

PMID38478027
PMCPMC11018654
OpenAlexW4392748872

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.