Predictive performance of multi-model approaches for model-informed precision dosing of piperacillin in critically ill patients
In conclusion, MAA streamlines MIPD by reducing the risk of selecting an inappropriate model for specific patients. Therefore, MIPD of PIP using MAA implicates further optimisation of antibiotic exposure in critically ill patients, by improving predictive performance with only one sample available for Bayesian forecasting, safety, and usability in clinical practice.
Authors
- Michael Zöller (ORCID: https://orcid.org/0000-0002-5337-6509)
- Sebastian Greppmair (ORCID: https://orcid.org/0009-0008-6492-0486)
- Christoph Dorn (ORCID: https://orcid.org/0000-0002-2560-9598)
- Otto Roman Frey (ORCID: https://orcid.org/0000-0001-9482-5094)
- Anka C. Roehr
- Alexandra K. Kunzelmann (ORCID: https://orcid.org/0009-0007-9849-9901)
- Stefan Hagel (ORCID: https://orcid.org/0000-0003-2999-6131)
- Lea Marie Schatz (ORCID: https://orcid.org/0000-0002-2954-5130)
- Christina Scharf (ORCID: https://orcid.org/0000-0002-5310-4116)
- Alexander Brinkmann
- Sebastian G. Wicha (ORCID: https://orcid.org/0000-0002-8773-4845)
- Uwe Liebchen (ORCID: https://orcid.org/0000-0002-4375-0923)
- Johannes Starp (ORCID: https://orcid.org/0009-0002-9076-3943)
Institutions
- Universität Hamburg (DE)
- LMU Klinikum (DE)
- Jena University Hospital (DE)
- University of Regensburg (DE)
- Friedrich Schiller University Jena (DE)
- Ludwig-Maximilians-Universität München (DE)
Publication Details
- Journal
- International Journal of Antimicrobial Agents
- Published
- 2024-08-13
- DOI
- https://doi.org/10.1016/j.ijantimicag.2024.107305
- Citations
- 9
- Primary Topic
- Antibiotics Pharmacokinetics and Efficacy
- Type
- article
- Field-Weighted Citation Impact
- 4.03
Funders
- Deutsche Forschungsgemeinschaft