Precision in practice.
The Zio service helps you accomplish your program goals by delivering superior clinical accuracy while reducing the cost of care. The service is comprised of:
- A single use monitor that patients prefer, with 99% patient compliance1
- Advanced AI in cardiac monitoring2
- A curated patient report, built by Certified Cardiographic Technicians, with 99% physician agreement3
Come join us at ACC.24 in booth #1131 and speak with our team.
Find Zio by iRhythm at ACC.24:
Expo Dates: April 6-8, 2024
Georgia World Congress Center| Atlanta, GA
Booth #1131 | ExpoSuite #ES1453
Exhibit Hours:
Saturday, April 6: 9:00 a.m. – 4:45 p.m.
Sunday, April 7: 9:00 a.m. – 4:45 p.m.
Monday, April 8: 9:00 a.m. – 2:00 p.m
Industry Expert Theater
Sunday, April 7th | 3:30-4:30p.m. | Theater IET3
Contemporary Challenges in Arrhythmia Monitoring and Management: From AF to VT
Speakers
Rod Passman, MD, MSCE, FACC, FHRS, FAHA
Director, Northwestern University Center for Arrhythmia Research
Associate Director, Cardiac Electrophysiology,
Northwestern University, Feinberg School of Medicine
Renato Delascio Lopes, MD, MHS, PhD, FACC
Professor of Medicine of the Department of Medicine, Cardiology
Duke University Medical Center
Christine Albert, MD, MPH, FHRS, FACC
Professor of Cardiology
Chair, Department of Cardiology
Cedars-Sinai
ACC.24 badge required for entry.
This event is not part of ACC.24, as planned by its Program Committee, and does not qualify for continuing medical education (CME), continuing nursing education (CNE) or continuing education (CE) credit.
Abstract Presentation
Sunday, April 7 | 11:15 a.m. – 12:00 p.m. | Presentation #1391-202
Hannah Schwennesen, M.D., Duke Clinical Research Institute
Extended Ambulatory Monitoring and Prediction of Heart Failure Events in Treated and Untreated Patients
Schedule a meeting
1. Data on file. iRhythm Technologies, 2019
2. Over 4 million patient records, over 1 billion hours of heart rhythm data, 34 layer deep neural network.
Data on file. iRhythm Technologies, 2022.
Hannun, AY. et al. Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network. Nature Medicine, 2019.
FDA 510K clearance.
Deep learned algorithm is only available in the United States.
3. 99% of physicians agree with the comprehensive final patient report. Based on a review of all online Zio XT and AT final patient reports. Data on file. iRhythm Technologies, 2021.