Developing and validating a machine learning model to predict multidrug-resistant Klebsiella pneumoniae-related septic shock
This study presents a validated, high-performing predictive model for MDR-KP-associated septic shock, offering a valuable tool for early clinical decision-making. Prospective, multi-center studies are recommended to further evaluate its clinical applicability and effectiveness in diverse settings.
Authors
- Shengnan Pan (ORCID: https://orcid.org/0009-0004-9266-0635)
- Yabin Yu
- Jinling Ji
- Chang Li (ORCID: https://orcid.org/0000-0002-7857-1028)
- Kai Wang (ORCID: https://orcid.org/0000-0002-0511-8038)
- Kun Jiang (ORCID: https://orcid.org/0000-0003-4995-7244)
- Ting Shi
Institutions
- Xuzhou Medical College (CN)
- Huaian First People’s Hospital (CN)
- Second People’s Hospital of Huai’an (CN)
- Nanjing Medical University (CN)
Publication Details
- Journal
- Frontiers in Immunology
- Published
- 2025-01-10
- DOI
- https://doi.org/10.3389/fimmu.2024.1539465
- Citations
- 4
- Primary Topic
- Antibiotic Resistance in Bacteria
- Type
- article
- Field-Weighted Citation Impact
- 2.36
Funders
- Nanjing Medical University