A Risk Prediction Model for New-Onset Chronic Kidney Disease in the Elderly
This study developed a simple yet effective risk prediction model for new-onset CKD among elderly populations. The model facilitates prompt identification of elderly individuals at risk of renal function decline in primary care, enabling timely interventions.
Authors
- Shaohua Yan (ORCID: https://orcid.org/0000-0002-3339-3184)
- Wenqing Nai
- Wei Luo (ORCID: https://orcid.org/0000-0001-6951-7698)
- Li Lei (ORCID: https://orcid.org/0000-0001-5429-9675)
- H. Liang (ORCID: https://orcid.org/0000-0002-3972-2049)
- Qiuxia Zhang (ORCID: https://orcid.org/0000-0001-6751-5699)
- Hongshan Chen (ORCID: https://orcid.org/0000-0003-4811-4552)
- Jiancheng Xiu (ORCID: https://orcid.org/0000-0003-2906-3278)
- Xinlu Zhang (ORCID: https://orcid.org/0009-0002-5585-062X)
- Yumiao Liu
- Min Xiao (ORCID: https://orcid.org/0000-0001-8202-8805)
- Xiong Gao
- Jinchuan Lai
Institutions
- Jinan University (CN)
- Southern University of Science and Technology (CN)
- Nanfang Hospital (CN)
- Tang Hospital (CN)
- Southern Medical University (CN)
Publication Details
- Journal
- American Journal of Nephrology
- Published
- 2024-09-23
- DOI
- https://doi.org/10.1159/000541510
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.71
Funders
- Southern Medical University
- Nanfang Hospital