Advancing Precision Medicine for Hypertensive Nephropathy: A Novel Prognostic Model Incorporating Pathological Indicators
In this study, the RSF algorithm was employed to identify the risk factors affecting the prognosis of HN patients, and a clinical prognostic RSF model was constructed to predict the adverse outcomes of HN patients based on renal pathology. Compared to the traditional Cox regression model, the RSF model offers superior performance and can provide valuable new insights for clinical diagnosis and treatment strategies.
Authors
- Xiaoxuan Ning (ORCID: https://orcid.org/0000-0002-5367-707X)
- Yan Xing (ORCID: https://orcid.org/0000-0002-8076-0805)
- Yunlong Qin (ORCID: https://orcid.org/0000-0002-9442-4650)
- Zhao Wei (ORCID: https://orcid.org/0000-0001-5103-3871)
- Zixian Yu (ORCID: https://orcid.org/0000-0002-0990-7691)
- Anjing Wang
- Panpan Liu (ORCID: https://orcid.org/0000-0002-0142-0600)
- Yuwei Wang (ORCID: https://orcid.org/0000-0001-8819-3844)
- Meng Liu (ORCID: https://orcid.org/0000-0001-5841-5872)
- Zhao Jin
- Shiren Sun (ORCID: https://orcid.org/0000-0001-5322-1454)
- M C Han
- Yueqing Hui
Institutions
- Bethune International Peace Hospital (CN)
- Xijing Hospital (CN)
- Air Force Medical University (CN)
Publication Details
- Journal
- Kidney & Blood Pressure Research
- Published
- 2025-03-29
- DOI
- https://doi.org/10.1159/000545524
- Primary Topic
- Chronic Kidney Disease and Diabetes
- Type
- article
- Field-Weighted Citation Impact
- 0.00