Coarctation duration and severity predict risk of hypertension precursors in a preclinical model and hypertensive status among patients.

Ghorbannia, Arash; Jurkiewicz, Hilda; Nasif, Lith; Ahmed, Abdillahi; Co-Vu, Jennifer; Maadooliat, Mehdi; Woods, Ronald K; LaDisa, John F

Ghorbannia, Arash; Jurkiewicz, Hilda; Nasif, Lith; Ahmed, Abdillahi; Co-Vu, Jennifer; Maadooliat, Mehdi; Woods, Ronald K; LaDisa, John F.

Afiliación

Ghorbannia A; Department of Pediatrics - Division of Cardiology, Herma Heart Institute, Children's Wisconsin and the Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Jurkiewicz H; Department of Biomedical Engineering, Marquette University and the Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Nasif L; Pratt School of Engineering, Duke University, Durham, NC USA.
Ahmed A; Department of Pediatrics - Division of Cardiology, Herma Heart Institute, Children's Wisconsin and the Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Co-Vu J; Pediatric Cardiology, University of Florida Health Congenital Heart Center, Gainesville, Florida, USA.
Maadooliat M; Pediatric Cardiology, University of Florida Health Congenital Heart Center, Gainesville, Florida, USA.
Woods RK; Pediatric Cardiology, University of Florida Health Congenital Heart Center, Gainesville, Florida, USA.
LaDisa JF; Department of and Statistical Sciences, Marquette University, Milwaukee, Wisconsin, USA.

medRxiv ; 2024 Mar 19.

Article en En | MEDLINE | ID: mdl-37961634

Palabras clave

Coarctation of the aorta; echocardiography; machine learning; severity assessment; treatment guidelines

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: MedRxiv Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

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