A new survival prediction model and exploration of hemodialysis quality control indicators in incident hemodialysis patients
Integrating ALP and machine-derived BC into a Cox model significantly improves risk stratification in incident HD patients and facilitates the implementation of automated quality control.
Authors
- D. Y. Shen
- Huaiwen Chang (ORCID: https://orcid.org/0000-0002-8283-7925)
- Jun Yi Shi (ORCID: https://orcid.org/0000-0002-6879-2716)
- Ni Li (ORCID: https://orcid.org/0000-0001-5530-7745)
- Ping Cheng (ORCID: https://orcid.org/0000-0002-0962-8609)
- Jing Qian (ORCID: https://orcid.org/0000-0002-1642-9202)
- Jing Chen
- Chuhan Lu
- Xiaofeng Wang
- Mengjing Wang
Institutions
- Fudan University (CN)
- Huashan Hospital (CN)
Publication Details
- Journal
- PLoS ONE
- Published
- 2026-01-21
- DOI
- https://doi.org/10.1371/journal.pone.0340994
- Primary Topic
- Dialysis and Renal Disease Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Shanghai Municipal Health Commission
- National Natural Science Foundation of China
- Fudan University
- Huashan Hospital