Cardiometabolic-Kidney Indices and Machine Learning Model for Predicting All-Cause Mortality in Patients with Cardiovascular-Kidney-Metabolic Syndrome: A Longitudinal Cohort Study
Cardiometabolic-kidney indices significantly associated with prognosis in CKM patients, highlighting the importance of heart-kidney-metabolism crosstalk. Combining easily accessible biomarkers with the XGBoost model may facilitate risk stratification.
Authors
- Lin Wang (ORCID: https://orcid.org/0000-0001-5994-4880)
- Yi Lu (ORCID: https://orcid.org/0000-0002-7348-8903)
- Jin Deng (ORCID: https://orcid.org/0000-0001-7656-5911)
- Jiayuan Wu (ORCID: https://orcid.org/0000-0002-4626-2773)
- Lin Zhu (ORCID: https://orcid.org/0000-0003-2463-1686)
- Junfeng Ge (ORCID: https://orcid.org/0000-0001-8435-0443)
- Fengying Dong
Institutions
- University of South China (CN)
Publication Details
- Journal
- American Journal of Nephrology
- Published
- 2025-11-25
- DOI
- https://doi.org/10.1159/000549578
- Citations
- 1
- Primary Topic
- Chronic Kidney Disease and Diabetes
- Type
- article
- Field-Weighted Citation Impact
- 1.43