Mortality Risk Stratification Utilizing Artificial Intelligence Electrocardiogram for Hyperkalemia in Cardiac Intensive Care Unit Patients
AI-ECG-based prediction of hyperkalemia, even with a normal laboratory potassium value, was associated with higher in-hospital mortality and lower 1-year survival in CICU patients. This study demonstrated that AI-ECG probability of hyperkalemia may enable rapid individualized risk stratification in critically ill patients beyond laboratory value alone.
Authors
- Jacob Colin Jentzer (ORCID: https://orcid.org/0000-0002-6366-2859)
- John Dillon (ORCID: https://orcid.org/0000-0002-2164-4476)
- David Harmon (ORCID: https://orcid.org/0000-0002-8102-3380)
- Paul A. Friedman (ORCID: https://orcid.org/0000-0001-5052-2948)
- Rickey E. Carter (ORCID: https://orcid.org/0000-0002-0818-273X)
- Zachi Itzhak Attia (ORCID: https://orcid.org/0000-0002-9706-7900)
- KIANOUSH B KASHANI (ORCID: https://orcid.org/0000-0003-2184-3683)
- C Heinrich
Institutions
- Mayo Clinic (US)
- Jacksonville College (US)
- Mayo Clinic in Arizona (US)
- Mayo Clinic in Florida (US)
Publication Details
- Journal
- JACC Advances
- Published
- 2024-08-23
- DOI
- https://doi.org/10.1016/j.jacadv.2024.101169
- Citations
- 8
- Primary Topic
- Heart Failure Treatment and Management
- Type
- article
- Field-Weighted Citation Impact
- 3.22