The results, published in JAMA Cardiology, suggest AI-augmented ECG (AI-ECG) analysis could be a potential low-cost strategy for identifying patients who have underlying impairment in heart function.
The team recruited nearly 6,000 patients seeking routine clinical care from eight health care facilities in Kenya to receive AI-ECG.
A subset of this group, totaling 1,444 patients, also received echocardiograms to verify their AI-ECG results.
AI-ECG had a 99.1% negative predictive value, meaning nearly all patients whose results reflected no evidence of LVSD were confirmed negative by echocardiography.
Positive AI-ECG screening in the study was strongly associated with other markers of adverse cardiac remodeling, including left ventricular hypertrophy and diastolic dysfunction.
The algorithm demonstrated a high level of sensitivity, correctly identifying 95.6% of people who had LVSD, while also showing high specificity in accurately identifying 79.4% of people who did not have the condition.
The authors said their findings support the use of AI-ECG as a screening tool for LVSD in resource-limited settings where systematic echocardiographic screening is not feasible.
【MORE】