Association between the changing trends of platelet distribution width and in-hospital mortality in critically ill patients with sepsis: a multicenter study based on machine learning
Based on PDW trajectories, we identified and validated four distinct sepsis subphenotypes, each characterized by significant variations in inflammatory marker levels and clinical outcomes.
Authors
- Dehua Zhuang (ORCID: https://orcid.org/0000-0002-9370-8619)
- Dayong Gu (ORCID: https://orcid.org/0000-0002-9547-8474)
- Xinxing Lei (ORCID: https://orcid.org/0000-0002-4443-616X)
- Shijie Su (ORCID: https://orcid.org/0000-0003-2784-9832)
- Hao Deng (ORCID: https://orcid.org/0000-0003-3749-2275)
- Jing Zhang (ORCID: https://orcid.org/0000-0002-2488-5021)
- Bin Wang (ORCID: https://orcid.org/0000-0002-4774-8476)
- Lian Yu
- Tianjing Wei
- Yinjing Xie (ORCID: https://orcid.org/0000-0001-6313-5808)
- Xiaoning Zhang (ORCID: https://orcid.org/0000-0002-5544-4405)
- Yuzhong Xu
- Shaorong Qiu
- Xiaopeng Yuan
- Hao Wu (ORCID: https://orcid.org/0000-0002-6638-169X)
Institutions
- Jinan University (CN)
- Southern University of Science and Technology (CN)
- ShenZhen People’s Hospital (CN)
- Shenzhen Bao'an District People's Hospital (CN)
- Shenzhen Second People's Hospital (CN)
Publication Details
- Journal
- BMC Infectious Diseases
- Published
- 2025-09-26
- DOI
- https://doi.org/10.1186/s12879-025-11525-x
- Citations
- 1
- Primary Topic
- Sepsis Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 1.35