دورية أكاديمية
أعرض في EDS

Screening for peripartum cardiomyopathies using artificial intelligence in Nigeria (SPEC-AI Nigeria): Clinical trial rationale and design.

التفاصيل البيبلوغرافية
العنوان: Screening for peripartum cardiomyopathies using artificial intelligence in Nigeria (SPEC-AI Nigeria): Clinical trial rationale and design.
المؤلفون: Adedinsewo DA; Department of Cardiovascular Medicine, Mayo Clinic, Jacksonville, FL. Electronic address: adedinsewo.demilade@mayo.edu., Morales-Lara AC; Department of Cardiovascular Medicine, Mayo Clinic, Jacksonville, FL., Dugan J; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN., Garzon-Siatoya WT; Department of Cardiovascular Medicine, Mayo Clinic, Jacksonville, FL., Yao X; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN; Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN., Johnson PW; Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL., Douglass EJ; Department of Cardiovascular Medicine, Mayo Clinic, Jacksonville, FL., Attia ZI; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN., Phillips SD; Department of Cardiovascular Medicine, Mayo Clinic, Jacksonville, FL., Yamani MH; Department of Cardiovascular Medicine, Mayo Clinic, Jacksonville, FL., Tobah YB; Department of Obstetrics and Gynecology, Mayo Clinic, Rochester, MN., Rose CH; Department of Obstetrics and Gynecology, Mayo Clinic, Rochester, MN., Sharpe EE; Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN., Lopez-Jimenez F; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN., Friedman PA; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN., Noseworthy PA; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN; Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN., Carter RE; Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL.
المصدر: American heart journal [Am Heart J] 2023 Jul; Vol. 261, pp. 64-74. Date of Electronic Publication: 2023 Mar 25.
نوع المنشور: Randomized Controlled Trial; Journal Article; Research Support, Non-U.S. Gov't; Research Support, N.I.H., Extramural
اللغة: English
بيانات الدورية: Publisher: Mosby Country of Publication: United States NLM ID: 0370465 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1097-6744 (Electronic) Linking ISSN: 00028703 NLM ISO Abbreviation: Am Heart J Subsets: MEDLINE
أسماء مطبوعة: Original Publication: St. Louis, MO : Mosby
مواضيع طبية MeSH: Cardiomyopathies*/diagnosis , Cardiomyopathies*/epidemiology , Cardiomyopathies*/etiology , Puerperal Disorders*/diagnosis , Puerperal Disorders*/epidemiology, Pregnancy ; Humans ; Female ; Ventricular Function, Left ; Stroke Volume ; Artificial Intelligence ; Nigeria/epidemiology ; Peripartum Period ; Prospective Studies
مستخلص: Background: Artificial intelligence (AI), and more specifically deep learning, models have demonstrated the potential to augment physician diagnostic capabilities and improve cardiovascular health if incorporated into routine clinical practice. However, many of these tools are yet to be evaluated prospectively in the setting of a rigorous clinical trial-a critical step prior to implementing broadly in routine clinical practice.
Objectives: To describe the rationale and design of a proposed clinical trial aimed at evaluating an AI-enabled electrocardiogram (AI-ECG) for cardiomyopathy detection in an obstetric population in Nigeria.
Design: The protocol will enroll 1,000 pregnant and postpartum women who reside in Nigeria in a prospective randomized clinical trial. Nigeria has the highest reported incidence of peripartum cardiomyopathy worldwide. Women aged 18 and older, seen for routine obstetric care at 6 sites (2 Northern and 4 Southern) in Nigeria will be included. Participants will be randomized to the study intervention or control arm in a 1:1 fashion. This study aims to enroll participants representative of the general obstetric population at each site. The primary outcome is a new diagnosis of cardiomyopathy, defined as left ventricular ejection fraction (LVEF) < 50% during pregnancy or within 12 months postpartum. Secondary outcomes will include the detection of impaired left ventricular function (at different LVEF cut-offs), and exploratory outcomes will include the effectiveness of AI-ECG tools for cardiomyopathy detection, new diagnosis of cardiovascular disease, and the development of composite adverse maternal cardiovascular outcomes.
Summary: This clinical trial focuses on the emerging field of cardio-obstetrics and will serve as foundational data for the use of AI-ECG tools in an obstetric population in Nigeria. This study will gather essential data regarding the utility of the AI-ECG for cardiomyopathy detection in a predominantly Black population of women and pave the way for clinical implementation of these models in routine practice.
Trial Registration: Clinicaltrials.gov: NCT05438576.
Competing Interests: Conflict of interest Mayo Clinic has licensed the underlying technology to EKO devices, a maker of digital stethoscopes with embedded electrocardiogram electrodes and to Anumana. Mayo Clinic may receive financial benefit from the use of this technology, but at no point will Mayo Clinic benefit financially from its use for the care of patients at Mayo Clinic. Drs Attia, Lopez-Jimenez, and Friedman may also receive financial benefit from this agreement.
(Copyright © 2023 Elsevier Inc. All rights reserved.)
فهرسة مساهمة: Keywords: Artificial intelligence; Cardiomyopathies; Clinical trial; Electrocardiogram; Heart Failure; Nigeria; Peripartum Period; Pregnancy
سلسلة جزيئية: ClinicalTrials.gov NCT05438576
تواريخ الأحداث: Date Created: 20230326 Date Completed: 20230526 Latest Revision: 20230702
رمز التحديث: 20230703
DOI: 10.1016/j.ahj.2023.03.008
PMID: 36966922
قاعدة البيانات: MEDLINE
الوصف
تدمد:1097-6744
DOI:10.1016/j.ahj.2023.03.008