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Be Prepared for the AF Epidemic

New White Paper Features Latest Research on Portable Heart Monitors

Atrial Fibrillation (AF) contributes to an estimated 130,000 deaths in the United States each year, and its diagnosis, especially Paroxysmal AF (PAF), is frequently missed. Which type of mobile cardiac monitoring device can best detect AF, and what should cardiologists look for in selecting a monitoring system that will improve diagnostic yield (DY)?

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Research: Offline Vs Online Monitoring to Diagnose Paroxysmal AF

Marek Dziubinski, Ph.D., CEO of Medicalgorithmics and the inventor of PocketECG, will present “Monitoring Duration Vs Diagnostic Yield in Patients with Paroxysmal Atrial Fibrillation: Is Online Monitoring Better than Offline?” (Abstract #9300) May 10 at 9:30 a.m. during Poster Session 2 in the poster section of the exhibition hall. We hope you’ll join us.

Paroxysmal AF is a form of arrhythmia that is often difficult to diagnose because of its intermittent nature. It can lead to heart-related complications including blood clots, stroke, and heart failure. Left untreated, AF more broadly can double the risk of heart-related death and increase the risk of stroke by as much as five times.

16 595

mobile cardiac telemetry studies conducted during 2016  were analyzed

Kaplan-Meier estimator

was used to calculate the cumulative diagnostic yield for various AF burdens

Online vs Offline

  monitoring solutions were compared in the analysis

The study was based on the analysis of diagnostic summary reports from 16,595 mobile cardiac telemetry studies conducted between Jan. 1 and Dec. 31, 2016 by Medi-Lynx Cardiac Monitoring, a US-based, certified cardiac monitoring service provider. Our arrhythmia diagnostic solution, PocketECG, was used to capture continuous and fully labeled recordings, lasting between 1 and 30 days (mean duration: 18.1 ± 9.9 days), to determine the monitoring duration required to detect the first AF episode for various AF burdens (AFBs). The most common symptoms or reasons for monitoring were:

  • Palpitations (R00.2): 8457 (51% of all patients), out of which 15.2% (1288) were diagnosed with AF
  • Syncope and Collapse (R55): 2859 (17.2% of all patients), out of which 12.4% (355) where diagnosed with AF
  • Dizziness and Giddiness (R42): 2140 (12.9% of all patients), out of which 13.2% (283) where diagnosed with AF
  • Dyspnea (R06.00; R06.09): 1250 (7.5% of all patients), out of which 18.6% (232) were diagnosed with AF.
  • Tachycardia (R00.00): 902 (5% of all patients), out of which 15.4% (139) were diagnosed with AF.

Research also evaluated the impact of monitoring duration on diagnostic yield (DY) in patients with PAF (for AFB ≤ 1% and AFB ≤ 10%) and analyzed the difference in DY between the online method (up to 30 days) and simulated offline methods (24 and 48 hours Holter and multiday patch).

 

Results

The ability to shorten or extend monitoring duration based on the ongoing results transmitted by online ECG monitoring can improve diagnostic yield over fixed offline methods.

For AF burden ≤ 1 %, online monitoring with PocketECG showed:

  • DY 6 times higher than the first 24h of Holter monitoring
  • DY 3.5 times higher than the first 48h of Holter monitoring
  • DY higher by 36 % than the first 11 days with the offline patch
  • DY higher by 14 % than the first 18 days with the offline patch

For AF burden ≤ 10 %, the online method showed:

  • DY 4 times higher than the first 24h of Holter monitoring
  • DY 2.5 times higher than the first 48h of Holter monitoring
  • DY higher by 25 % than the first 11 days with the offline patch
  • DY higher by 10 % than the first 18 days with the offline patch

Interested in detailed research results ?