Prediction of teicoplanin plasma concentration in critically ill patients: a combination of machine learning and population pharmacokinetics
Our study offers a non-invasive, fast and cost-effective prediction model of teicoplanin plasma concentration in critically ill patients. The model serves as a fundamental tool for clinicians to determine the effective plasma concentration range of teicoplanin and formulate individualized dosing regimens accordingly.
Authors
- Jing Liu (ORCID: https://orcid.org/0000-0001-6526-7054)
- Yongchuan Chen (ORCID: https://orcid.org/0000-0003-0274-5797)
- Jiangfan Wu (ORCID: https://orcid.org/0000-0002-0565-7760)
- Shenglan Shang (ORCID: https://orcid.org/0000-0002-2771-6100)
- Wenrui Gu
- Mengchen Yu (ORCID: https://orcid.org/0009-0003-1260-985X)
- Ruixiang Liu (ORCID: https://orcid.org/0009-0007-0779-4535)
- Pan Ma (ORCID: https://orcid.org/0000-0002-0121-0769)
- Ying Li
- Yuzhu Dong
Institutions
- Army Medical University (CN)
- Third People 's Hospital of Chongqing (CN)
- The Affiliated Yongchuan Hospital of Chongqing Medical University (CN)
- Central Hospital of Wuhan (CN)
- Wuhan General Hospital of Guangzhou (CN)
- General Hospital of Central Theater Command
- Chongqing Medical University (CN)
Publication Details
- Journal
- Journal of Antimicrobial Chemotherapy
- Published
- 2024-08-29
- DOI
- https://doi.org/10.1093/jac/dkae292
- Citations
- 7
- Primary Topic
- Antibiotics Pharmacokinetics and Efficacy
- Type
- article
- Field-Weighted Citation Impact
- 3.13
Funders
- China Postdoctoral Science Foundation