Atrial fibrillation (AF) is the most common sustained arrhythmia and carries a 5-fold increased risk of stroke. AF is common in the elderly, and previously unrecognized AF is estimated to occur in 1-2% of those over 65. A significant proportion of ischemic strokes are due to previously unrecognized AF, which is largely asymptomatic, and may therefore require community screening to detect the arrhythmia. Until now, community ECG screening has not been considered a feasible approach for AF detection.
Smartphones are important tools for physicians and patients. This study is a comparison of accuracy between an ECG lead I from a conventional 12-lead ECG and an iPhone-based device, which is a low cost phone case with 2 metal electrodes (Figure 1A). When the electrodes are held by both hands, a lead I rhythm strip is recorded and uploaded by the integrated software with easy provider access for review. ]
A novel iPhone application suitable for community use (AliveCor), which records and sends a high quality single-lead ECG to a server for automated analysis, and subsequent interpretation by a physician to diagnose AF was tested
A single-lead ECG was recorded using an iPhone in 109 patients (70 sinus rhythm and 39 AF) soon after a 12-lead ECG had been performed. iPhone ECGs were uploaded to the AliveCor server for subsequent interpretation by two cardiologists blinded to the rhythm diagnosis. The iPhone ECG was also processed on the server to provide an automated diagnosis of sinus rhythm or AF. Results were compared with the 12-lead ECG diagnosis by a third cardiologist.
Sensitivity and specificity of the iPhone single lead ECG for AF diagnosis, overall accuracy and kappa () were 100%, 90%, 94%, 0.87 for cardiologist A; 95%, 94%, 95%, 0.88 for cardiologist B, and 87%, 97%, 94%, 0.86 for the automated algorithm respectively. After algorithm optimization to enhance sensitivity, results for automated analysis were 100%, 96%, 97%, 0.94 respectively.
A high quality single-lead ECG can be rapidly and simply recorded using an iPhone with the AliveCor application, to accurately diagnose AF, making this an ideal enabling technology for community screening programs to detect silent AF. Screening programs utilizing this device could have a substantial impact on reducing ischemic stroke related to previously undiagnosed AF.