Using Atrial Fibrillation Burden Trends and Machine Learning to Predict Near-Term Risk of Cardiovascular Hospitalization
Trends in atrial fibrillation were strongly associated with near-term CVH, especially above-average burden coupled with low patient activity. This approach could provide actionable information to guide treatment and reduce CVH.
Authors
- ROD S. PASSMAN (ORCID: https://orcid.org/0000-0001-8718-1534)
- Jonathan Paul Piccini (ORCID: https://orcid.org/0000-0003-0772-2404)
- Dhanunjaya Lakkireddy (ORCID: https://orcid.org/0000-0002-1492-2693)
- Suneet Mittal (ORCID: https://orcid.org/0000-0002-8003-7254)
- Mellanie True Hills (ORCID: https://orcid.org/0000-0001-8298-4418)
- Lawrence C. Johnson (ORCID: https://orcid.org/0000-0001-8547-072X)
- Dana Soderlund
- Rahul Kanwar (ORCID: https://orcid.org/0000-0002-4575-8654)
- James M. Peacock (ORCID: https://orcid.org/0000-0002-5022-0461)
- Evan J. Stanelle (ORCID: https://orcid.org/0009-0007-7781-356X)
- Elaine M. Hylek (ORCID: https://orcid.org/0000-0001-8263-8304)
- Andrea M. Russo (ORCID: https://orcid.org/0000-0002-3129-6161)
Institutions
- Boston University (US)
- Northwestern University (US)
- Heart Rhythm Society (US)
- Boston Medical Center (US)
- Cooper University Hospital (US)
- University Medical Center (US)
- Medtronic (Ireland) (IE)
- Medtronic (United States) (US)
- Valley Health System (US)
- White Plains Hospital (US)
- HOPE Clinic (US)
- Duke Medical Center (US)
Publication Details
- Journal
- Circulation Arrhythmia and Electrophysiology
- Published
- 2024-10-24
- DOI
- https://doi.org/10.1161/circep.124.012991
- Citations
- 5
- Primary Topic
- Blood Pressure and Hypertension Studies
- Type
- article
- Field-Weighted Citation Impact
- 2.01