Application Of Artificial Intelligence To The Standard 12 Lead Ecg To Identify People With Left Ventricular Dysfunction

Asymptomatic left ventricular dysfunction (ALVD) is present in 2-9% of the population, is associated with reduced longevity and is treatable when found. Inexpensive, reliable, in office screening is not available. The area under the curve (AUC) for a BNP screening blood test is 0.79 to 0.89. We hypothesized that use of artificial intelligence (AI) would enable the ECG, a ubiquitous, inexpensive test, to identify ALVD. Of the 51,979 patients tested, 4,064 (8%) had an EF< 35%. The AUC of the ROC was 0.93 (Fig). The sensitivity, specificity and accuracy were 85%, 86% and 86%, respectively. In patients with an abnormal AI screen but normal EF (false positives, 1317), 153 had at least one abnormal EF in the future (5 year incidence 10.1%). This five-fold increased risk of developing a future low EF suggests that the network may be detecting early, subclinical, metabolic or structural abnormalities that manifest in the ECG.