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Dysfunctional Implantable Pulmonary Artery Sensor Device (CardioMEMS) in Group 2 Pulmonary Hypertension.
JACC Case Rep
January 2025
Krannert Institute of Cardiology, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Implantable hemodynamic devices like the CardioMEMS HF System are commonly used to manage fluid status in patients with heart failure (HF) by measuring pulmonary pressures. Although CardioMEMS has been shown to reduce HF hospitalizations, rare complications (eg, device endothelialization) can occur and warrant clinical attention. A 67-year-old woman with HF with preserved ejection fraction and group 2 pulmonary hypertension experienced recurrent HF exacerbations.
View Article and Find Full Text PDFMultiorgan Dysfunction and its Association With Congestion and Outcome in Aortic Stenosis Treated With TAVI.
JACC Adv
February 2025
Department of Internal Medicine II, Medical University of Vienna, Vienna, Austria.
Background: Degenerative severe aortic stenosis (AS) is treated by valve replacement to improve outcome. Despite diagnostic advancements, many AS patients are still diagnosed late with advanced heart failure.
Objectives: The aim of the study was to assess multiorgan dysfunction in severe AS using blood biomarkers and their association with quantitative fluid levels and clinical outcomes after transcatheter aortic valve implantation (TAVI).
The Mechanical and Perfusion Basis of Exercise Limitation in Apical Hypertrophic Cardiomyopathy.
JACC Adv
February 2025
Barts Heart Centre, Department of Cardiac Diagnostics and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, London, United Kingdom.
Diversity Recruitment in Cardiovascular Specialties: Barriers and Opportunities in Postgraduate Training Programs.
JACC Adv
February 2025
Frank H. Netter School of Medicine, Quinnipiac University, Hamden, Connecticut, USA.
Background: Diversity in postgraduate training programs can be increased through program-based recruitment strategies. Prospective applicants often examine website content to determine if training programs are inclusive and offer a good fit. Poor overlap between program director recruitment goals and program website content as a barrier to recruiting a diverse physician workforce has not extensively been studied.
View Article and Find Full Text PDFDeep Learning-Based Identification of Echocardiographic Abnormalities From Electrocardiograms.
JACC Asia
January 2025
Department of Frontier Cardiovascular Science, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Background: Heart failure should be diagnosed as early as possible. Although deep learning models can predict one or more echocardiographic findings from electrocardiograms (ECGs), such analyses are not comprehensive.
Objectives: This study aimed to develop a deep learning model for comprehensive prediction of echocardiographic findings from ECGs.
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