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Research ArticleArticles

Artificial Intelligence Tools for Preconception Cardiomyopathy Screening Among Women of Reproductive Age

Anja Kinaszczuk, Andrea Carolina Morales-Lara, Wendy Tatiana Garzon-Siatoya, Sara El-Attar, Adrianna D. Clapp, Ifeloluwa A. Olutola, Ryan Moerer, Patrick Johnson, Mikolaj A. Wieczorek, Zachi I. Attia, Francisco Lopez-Jimenez, Paul A. Friedman, Rickey E. Carter, Peter A. Noseworthy and Demilade Adedinsewo
The Annals of Family Medicine April 2025, 230627; DOI: https://doi.org/10.1370/afm.230627
Anja Kinaszczuk
Department of Family Medicine, Mayo Clinic, Jacksonville, Florida
DO
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Andrea Carolina Morales-Lara
Department of Cardiovascular Medicine, Mayo Clinic, Jacksonville, Florida
MD
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Wendy Tatiana Garzon-Siatoya
Department of Cardiovascular Medicine, Mayo Clinic, Jacksonville, Florida
MD
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Sara El-Attar
Department of Cardiovascular Medicine, Mayo Clinic, Jacksonville, Florida
MD
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Adrianna D. Clapp
Department of Family Medicine, Mayo Clinic, Jacksonville, Florida
MD
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Ifeloluwa A. Olutola
Department of Family Medicine, Mayo Clinic, Jacksonville, Florida
MD
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Ryan Moerer
Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, Florida
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Patrick Johnson
Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, Florida
MS
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Mikolaj A. Wieczorek
Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, Florida
MS
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Zachi I. Attia
Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota
PhD
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Francisco Lopez-Jimenez
Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota
MS, MD
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Paul A. Friedman
Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota
MD
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Rickey E. Carter
Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, Florida
PhD
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Peter A. Noseworthy
Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota
MD, MBA
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Demilade Adedinsewo
Department of Cardiovascular Medicine, Mayo Clinic, Jacksonville, Florida
MD, MPH
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Additional Files

  • SUPPLEMENTAL MATERIALS IN PDF FILE BELOW

    • Adedinsewo-Appendix_Tables_Figures.pdf -

      PDF file

  • VISUAL ABSTRACT IN PDF FILE BELOW

    • Adedinsewo_VA_23_3_Final_v2.pdf -

      PDF file

  • PLAIN-LANGUAGE SUMMARY

    Original Research

    AI-Enabled Tools for Cardiovascular Screening Show Promise in Identifying Heart Dysfunction in Women of Reproductive Age

    Background and Goal:Cardiomyopathy, a disease that weakens the heart muscle and makes it harder to pump blood, is a major health threat during pregnancy and accounts for 40% to 60% of late maternal deaths. 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 who were already scheduled for an echocardiogram. The second group of women had no indication for an echocardiogram and 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. In the second group, patients flagged with LVSD by the 12-lead ECG were then referred to an echocardiogram. 

    Main Results: 

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

    • 5% of women had LVSD.

    • Negative results were highly reliable, with the AI-ECG showing a negative predictive value of 96.8% and the AI-stethoscope achieving 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:Many women of reproductive age do not receive routine heart screening before pregnancy. 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.     

    Artificial Intelligence Tools for Preconception Cardiomyopathy Screening Among Women of Reproductive Age 

    Demilade Adedinsewo, MD, MPH, et al
    Department of Cardiovascular Diseases, Mayo Clinic, Jacksonville, Florida

    Visual Abstract:

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The Annals of Family Medicine: 23 (3)
The Annals of Family Medicine: 23 (3)
Vol. 23, Issue 3
May/June 2025
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Artificial Intelligence Tools for Preconception Cardiomyopathy Screening Among Women of Reproductive Age
Anja Kinaszczuk, Andrea Carolina Morales-Lara, Wendy Tatiana Garzon-Siatoya, Sara El-Attar, Adrianna D. Clapp, Ifeloluwa A. Olutola, Ryan Moerer, Patrick Johnson, Mikolaj A. Wieczorek, Zachi I. Attia, Francisco Lopez-Jimenez, Paul A. Friedman, Rickey E. Carter, Peter A. Noseworthy, Demilade Adedinsewo
The Annals of Family Medicine Apr 2025, 230627; DOI: 10.1370/afm.230627

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Artificial Intelligence Tools for Preconception Cardiomyopathy Screening Among Women of Reproductive Age
Anja Kinaszczuk, Andrea Carolina Morales-Lara, Wendy Tatiana Garzon-Siatoya, Sara El-Attar, Adrianna D. Clapp, Ifeloluwa A. Olutola, Ryan Moerer, Patrick Johnson, Mikolaj A. Wieczorek, Zachi I. Attia, Francisco Lopez-Jimenez, Paul A. Friedman, Rickey E. Carter, Peter A. Noseworthy, Demilade Adedinsewo
The Annals of Family Medicine Apr 2025, 230627; DOI: 10.1370/afm.230627
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Keywords

  • artificial intelligence
  • cardiomyopathy
  • electrocardiography
  • preconception care
  • primary health care

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