Publications by authors named "B Bernhard"
Stress CMR Perfusion Imaging in the Medicare-Eligible Population: Insights From the SPINS Study.
JACC Cardiovasc Imaging
January 2025
Article Synopsis
- - Patients aged 65 and older have a higher risk of cardiovascular (CV) events, and this study aimed to evaluate the effectiveness of stress cardiac magnetic resonance (CMR) for predicting these events in this age group across multiple centers in the U.S.
- - The research involved 1,780 seniors, finding that those with inducible ischemia or late gadolinium enhancement (LGE) showed significantly higher rates of serious CV events over nearly 5 years, while those without these conditions had a low event rate.
- - The study concluded that both inducible ischemia and LGE are strong predictors of primary and secondary CV outcomes, indicating that CMR can be a valuable tool for risk assessment in older patients.
Background: The European Society of Cardiology (ESC), the American College of Cardiology, the American Heart Association, and expert consensus documents provide different diagnostic criteria for myocarditis. Their overlap and prognostic value have never been compared.
Objectives: This study aims to assess and compare the predictive value of ESC criteria for clinically suspected myocarditis, updated Lake-Louise criteria (LLC), American Heart Association criteria for probable acute myocarditis (pAM), and expert consensus criteria for acute myocarditis (AM) and complicated myocarditis (CM).
Background: Signs and symptoms of myocarditis may vary among men and women.
Objectives: This study aimed to analyze sex-specific differences in the presentation and outcomes of patients with suspected myocarditis.
Methods: Patients meeting clinical ESC criteria for suspected myocarditis were included from two tertiary centers between 2002 and 2021.
Article Synopsis
- This study investigates the use of artificial intelligence to detect transthyretin amyloid cardiomyopathy (ATTR-CM) in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve implantation (TAVI).
- Researchers analyzed a variety of data including clinical, lab, and imaging results to develop machine learning models for detection and outcome prediction.
- Results showed that while echocardiography and 4D-CT-strain had good to high detection performances, the multi-modality model incorporating various data types did not significantly outperform the 4D-CT-strain model alone.