دورية أكاديمية
أعرض في EDS

Detecting cardiomyopathies in pregnancy and the postpartum period with an electrocardiogram-based deep learning model.

التفاصيل البيبلوغرافية
العنوان: Detecting cardiomyopathies in pregnancy and the postpartum period with an electrocardiogram-based deep learning model.
المؤلفون: Adedinsewo DA; Department of Cardiovascular Medicine, Mayo Clinic, 4500 San Pablo Rd, Jacksonville, FL 32224, USA., Johnson PW; Department of Quantitative Health Sciences, Mayo Clinic, 4500 San Pablo Rd, Jacksonville, FL 32224, USA., Douglass EJ; Department of Cardiovascular Medicine, Mayo Clinic, 4500 San Pablo Rd, Jacksonville, FL 32224, USA., Attia IZ; Department of Cardiovascular Medicine, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA., Phillips SD; Department of Cardiovascular Medicine, Mayo Clinic, 4500 San Pablo Rd, Jacksonville, FL 32224, USA., Goswami RM; Department of Transplant Medicine, Mayo Clinic, 4500 San Pablo Rd, Jacksonville, FL 32224, USA., Yamani MH; Department of Cardiovascular Medicine, Mayo Clinic, 4500 San Pablo Rd, Jacksonville, FL 32224, USA., Connolly HM; Department of Cardiovascular Medicine, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA., Rose CH; Department of Maternal and Fetal Medicine, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA., Sharpe EE; Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA., Blauwet L; Department of Cardiovascular Diseases, Olmsted Medical Center, 210 Ninth Street SE Rochester, MN 55904, USA., Lopez-Jimenez F; Department of Cardiovascular Medicine, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA., Friedman PA; Department of Cardiovascular Medicine, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA.; Department of Physiology and Biomedical Engineering, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA., Carter RE; Department of Quantitative Health Sciences, Mayo Clinic, 4500 San Pablo Rd, Jacksonville, FL 32224, USA., Noseworthy PA; Department of Cardiovascular Medicine, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA.
المصدر: European heart journal. Digital health [Eur Heart J Digit Health] 2021 Aug 27; Vol. 2 (4), pp. 586-596. Date of Electronic Publication: 2021 Aug 27 (Print Publication: 2021).
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: Oxford University Press Country of Publication: England NLM ID: 101778323 Publication Model: eCollection Cited Medium: Internet ISSN: 2634-3916 (Electronic) Linking ISSN: 26343916 NLM ISO Abbreviation: Eur Heart J Digit Health Subsets: PubMed not MEDLINE
أسماء مطبوعة: Original Publication: [Oxford] : Oxford University Press, [2020]-
مستخلص: Aims: Cardiovascular disease is a major threat to maternal health, with cardiomyopathy being among the most common acquired cardiovascular diseases during pregnancy and the postpartum period. The aim of our study was to evaluate the effectiveness of an electrocardiogram (ECG)-based deep learning model in identifying cardiomyopathy during pregnancy and the postpartum period.
Methods and Results: We used an ECG-based deep learning model to detect cardiomyopathy in a cohort of women who were pregnant or in the postpartum period seen at Mayo Clinic. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. We compared the diagnostic probabilities of the deep learning model with natriuretic peptides and a multivariable model consisting of demographic and clinical parameters. The study cohort included 1807 women; 7%, 10%, and 13% had left ventricular ejection fraction (LVEF) of 35% or less, <45%, and <50%, respectively. The ECG-based deep learning model identified cardiomyopathy with AUCs of 0.92 (LVEF ≤ 35%), 0.89 (LVEF < 45%), and 0.87 (LVEF < 50%). For LVEF of 35% or less, AUC was higher in Black (0.95) and Hispanic (0.98) women compared to White (0.91). Natriuretic peptides and the multivariable model had AUCs of 0.85 to 0.86 and 0.72, respectively.
Conclusions: An ECG-based deep learning model effectively identifies cardiomyopathy during pregnancy and the postpartum period and outperforms natriuretic peptides and traditional clinical parameters with the potential to become a powerful initial screening tool for cardiomyopathy in the obstetric care setting.
(© The Author(s) 2021. Published by Oxford University Press on behalf of the European Society of Cardiology.)
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معلومات مُعتمدة: K12 HD065987 United States HD NICHD NIH HHS
فهرسة مساهمة: Keywords: Artificial intelligence; Cardiomyopathy; ECG; Heart failure; Peripartum; Pregnancy
تواريخ الأحداث: Date Created: 20220107 Latest Revision: 20221013
رمز التحديث: 20231215
مُعرف محوري في PubMed: PMC8715757
DOI: 10.1093/ehjdh/ztab078
PMID: 34993486
قاعدة البيانات: MEDLINE
الوصف
تدمد:2634-3916
DOI:10.1093/ehjdh/ztab078