Key clinical point: Use of a noninvasive artificial intelligence device at point of care can identify potentially undetected atrial fibrillation.
Major finding: An artificial intelligence–enabled ECG identified atrial fibrillation with an overall accuracy of 83.3%.
Study details: The data come from 180,922 adults aged 18 years or older with at least one normal sinus rhythm.
Disclosures: The researchers had no financial conflicts to disclose.
Attia ZI et al. Lancet. 2019 Aug 1. doi. org/10.1016/S0140-6736(19)31721-0.
This artificial intelligence-enabled ECG interpretation is groundbreaking in creating an algorithm to reveal the likelihood of atrial fibrillation in ECGs showing sinus rhythm.
AFib is now considered a global pandemic and needs to be detected not only to manage the arrhythmia but also to prevent comorbidities and death.
A 10-second, 12-lead ECG in current clinical practice is unlikely to reveal possible AFib if not present in this short monitoring time. However, the findings have clinical importance, particularly in identifying silent AFib and may have important implications for secondary prevention of patients with embolic stroke of undetermined source in terms of providing appropriate oral anticoagulation to prevent recurrences of stroke. The AI-enabled algorithm would require further validation in a different patient cohort, testing a healthier out-of-hospital population, as well as a rigorous prospective clinical trial assessment.
Future research areas include combining ECG algorithms with demographic variables, clinical features, and biomarkers, as well as exploring the use of wearable devices linking these variables and AI for smart monitoring to diagnose AFib.
Jeroen Hendriks, MD, of the University of Adelaide (Australia), and Larissa Fabritz, MD, of the University of Birmingham (England), made these comments in an accompanying editorial. Dr. Hendriks disclosed lecture or consulting fees from Medtronic and Pfizer/Bristol-Myers Squibb. Dr. Fabritz is the inventor of two patents and disclosed research grants and nonfinancial support from European research institutions and Gilead.