AI tools show promise in detecting early heart dysfunction in women

Background and goal: This study evaluated the performance of an artificial intelligence–enabled electrocardiogram (AI-ECG) and an AI-powered digital stethoscope to see how well they could detect early signs of heart dysfunction in women of reproductive age.

Study approach: In this cross-sectional pilot study, researchers examined two groups of women aged 18 to 49 who were considering pregnancy. Women who were currently pregnant or within one year postpartum were also included. The first group included 100 women already scheduled for an echocardiogram. The second group of women with no indication for an echocardiogram were seen at a primary care appointment for routine care. All participants received two tests: a standard 10-second 12-lead electrocardiogram (ECG) and a digital stethoscope recording that captured a 15-second, single-lead ECG and phonocardiogram (heart sounds) from up to three locations on the chest. AI models analyzed the ECG and stethoscope recordings to estimate each participant's risk of having left ventricular systolic dysfunction (LVSD), a type of heart dysfunction. 

Main results: 

Group 1 (diagnostic cohort, women scheduled for echocardiograms):

• Five percent of women had LVSD.

• The AI-ECG showed a negative predictive value of 96.8% and the AI-stethoscope achieved 100%.

• Among women who screened positive using the AI tools, 33.3% (using the AI-ECG) and 22.7% (using the AI-stethoscope) truly had LVSD.

Group 2 (screening cohort, women seen during routine primary care visits):

• Using the AI-ECG, only 1% of women in this low-risk sample screened positive. A follow-up echocardiogram in that patient showed a normal ventricular ejection fraction. With the AI-stethoscope, 3.2% of the sample had a positive screen.

Why it matters: The findings from this study highlight the potential of quick, low-cost AI tools to help detect early signs of heart dysfunction during regular primary care visits.