Electronic Health Record-Based Prediction Model to Predict Primary Aldosteronism Risk in People With Hypertension
This electronic health record-based prediction model achieved moderate discriminative performance, identifying primary aldosteronism in 29% of patients within the highest-risk decile, suggesting potential clinical utility for prioritizing screening efforts.
Authors
- Jacob Kohlenberg (ORCID: https://orcid.org/0000-0002-7157-0524)
- Kidmealem Zekarias (ORCID: https://orcid.org/0000-0001-6787-5846)
- Sisi Ma (ORCID: https://orcid.org/0000-0003-2956-6844)
- Meng Xu (ORCID: https://orcid.org/0000-0002-2218-6737)
Institutions
- University of Minnesota (US)
- University of Minnesota Medical Center (US)
- Minnesota Department of Health (US)
Publication Details
- Journal
- Endocrine Practice
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1016/j.eprac.2025.12.004
- Primary Topic
- Hormonal Regulation and Hypertension
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health
- National Institute of Diabetes and Digestive and Kidney Diseases