Predicting potassium trajectories for risk monitoring in outpatients with heart failure, diabetes mellitus or chronic kidney disease
We propose a blueprint of a decision support tool which predicts potassium concentration longitudinally by updating the predictions based on accumulating data. Our findings demonstrate that dynamically reassessing predictors can aid in estimating potassium levels over multiple months with reasonable accuracy in the outpatient setting.
Authors
- David Czock (ORCID: https://orcid.org/0000-0003-1217-5134)
- Hanna M. Seidling (ORCID: https://orcid.org/0000-0002-1215-634X)
- Tobias Dreischulte (ORCID: https://orcid.org/0000-0003-2345-5377)
- Andreas H. Groll (ORCID: https://orcid.org/0000-0003-1188-393X)
- Marietta Rottenkolber
- Andreas D. Meid (ORCID: https://orcid.org/0000-0003-3537-3205)
- Camilo Scherkl (ORCID: https://orcid.org/0009-0008-8569-1694)
- Jacob Grytzka
Institutions
- TU Dortmund University (DE)
- Heidelberg University (DE)
- University Hospital Heidelberg (DE)
- LMU Klinikum (DE)
- Ludwig-Maximilians-Universität München (DE)
Publication Details
- Journal
- British Journal of Clinical Pharmacology
- Published
- 2025-08-28
- DOI
- https://doi.org/10.1002/bcp.70250
- Primary Topic
- Potassium and Related Disorders
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- ASCRS Research Foundation
- Deutsche Forschungsgemeinschaft