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Smartphone App Has Potential to Detect AFib In Patients with Known History

Key findings

  • A smartphone app, called the Cardiio Rhythm Mobile Application (CRMA), was previously shown to have high diagnostic accuracy as a screening tool for atrial fibrillation (AF) in the general population
  • In this prospective, single-center study, the CRMA was evaluated as a monitoring tool for patients with known intermittent AF
  • The CRMA successfully obtained recordings from all but one of 98 patients (technical success rate of 99.5%)
  • For AF detection the CRMA demonstrated a sensitivity of 93%, specificity of 91%, positive predictive value of 92% and negative predictive value of 92%
  • Following cardioversion, in the presence of atrial and ventricular premature complexes during sinus rhythm, the false-positive rate with the CRMA was 16.3%, suggesting more work is needed on the detection algorithm

Because atrial fibrillation (AF) is paroxysmal and sometimes asymptomatic, a large percentage of patients go undiagnosed by electrocardiography (ECG).

Working with researchers in Hong Kong, Cardiio Inc. of Cambridge, MA, recently developed a smartphone application that demonstrated high sensitivity and specificity as a screening tool for AF in the general population, which was reported in the Journal of the American Heart Association. The app, called Cardiio Rhythm Mobile Application (CRMA), uses a smartphone camera to measure slight variations in brightness produced by blood flow through vessels to extract a photoplethysmographic (PPG) waveform corresponding with the pulse.

In a prospective study, Jeremy Ruskin, MD, founder and director emeritus of the Telemachus & Irene Demoulas Family Foundation Center for Cardiac Arrhythmias at the Corrigan Minehan Heart Center at Massachusetts General Hospital, and colleagues determined that the app is also useful as a monitoring tool for patients with known intermittent AF. Their report appears in the American Journal of Cardiology.

The App

So far, the CRMA is designed to be used on an iPhone. The patient places an index finger against the phone's camera. An algorithm analyzes the degree of self-similarity of a PPG waveform over time to find repeating patterns, instead of simply assessing beat-to-beat changes in the PPG waveform.

Study Design

Ninety-eight eligible study participants were consecutive adults who were scheduled for elective direct-current cardioversion at Mass General. Using the app, 20-second pulse recordings were obtained for each patient three times before and three times after cardioversion. A 12-lead ECG, also obtained as part of the cardioversion procedure, was used as the standard for rhythm classification.

Two cardiologists interpreted the ECG recordings while blinded to the CRMA results and to each other's ECG interpretations.

Pre-cardioversion Results

At least one set of CRMA recordings was obtained from all but one of 98 enrolled subjects, representing a 99.5% success rate for the use of the CRMA.

Of the 97 subjects included in the pre-cardioversion analysis, ECG recordings were available for 94. Single-lead rhythm strips obtained from the CRMA were used to analyze the other three subjects. The ECG diagnosis, as confirmed by the cardiologist readers, was that 96 subjects had AF at the time of presentation for cardioversion.

One patient was found to be in normal sinus rhythm with frequent ventricular premature complexes (VPCs), which the CRMA incorrectly diagnosed as AF. According to the study, "the CRMA correctly identified the presenting rhythm in 92.7% (89 of 96) of the subjects who presented with AF."

Post-cardioversion Results

Post-cardioversion analysis was performed for 92 of the 97 patients. ECGs were available for 89 of those 92 patients and a single-lead rhythm strip was used for the analysis of the three others.

Following cardioversion, five of the 92 subjects remained in AF, 44 returned to normal sinus rhythm and 43 had sinus rhythm with atrial premature complexes (APCs) and VPCs. According to the study, "CRMA accurately labeled 80 of 87 tracings (92.0%) with normal sinus and paced rhythms," including all 44 patients with normal sinus rhythm and 36 of the 43 patients with APCs and VPCs.

The sensitivity of the CRMA for AF detection was 93% and the specificity was 91%. Both the positive predictive value and the negative predictive value were 92%.

Limitations of the Technology

In a different interpretation of the results, there was a 7/43 (16%) false-positive rate for patients with APCs and VPCs during sinus rhythm. The researchers call this a significant rate that suggests more work is needed on the detection algorithm.

The CRMA provides a snapshot of cardiac rhythm, rather than allowing continuous monitoring, which reduces the chance of detecting paroxysms of AF. The researchers note that to facilitate repeated screening or monitoring by the greatest number of patients, the application should be made usable on a wide range of mobile devices.

Learn more about the Telemachus & Irene Demoulas Family Foundation Center for Cardiac Arrhythmias

Refer a patient to the Corrigan Minehan Heart Center

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