Classifications of heart muscle diseases have proved to be exceedingly complex and in many respects contradictory. Indeed, the precise language used to describe these diseases is profoundly important. A new contemporary and rigorous classification of cardiomyopathies (with definitions) is proposed here. This reference document affords an important framework and measure of clarity to this heterogeneous group of diseases. Of particular note, the present classification scheme recognizes the rapid evolution of molecular genetics in cardiology, as well as the introduction of several recently described diseases, and is unique in that it incorporates ion channelopathies as a primary cardiomyopathy.
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http://dx.doi.org/10.1161/CIRCULATIONAHA.106.174287 | DOI Listing |
Nat Rev Cardiol
January 2025
Cardioncology Unit, Cardioncology and Second Opinion Division, European Institute of Oncology, Istituto di Ricovero e Cura a Carattere Scientifico, Milan, Italy.
Anthracyclines are the cornerstone of treatment for many malignancies. However, anthracycline cardiotoxicity is a considerable concern given that it can compromise the clinical effectiveness of the treatment and patient survival despite early discontinuation of therapy or dose reduction. Patients with cancer receiving anthracycline treatment can have a reduction in their quality of life and likelihood of survival due to cardiotoxicity, irrespective of their oncological prognosis.
View Article and Find Full Text PDFCureus
December 2024
Cardiology, Riverside Community Hospital, Riverside, USA.
Background: Methamphetamine abuse is a public health problem across the world, and the cardiovascular system experiences a significant effect on the myocardium over time. Methamphetamine is a common cause of heart failure with preserved ejection fraction (HFpEF) and heart failure with reduced ejection fraction (HFrEF). The prevalence and risk factors for HFpEF and HFrEF in this patient population remain unclear.
View Article and Find Full Text PDFComput Biol Med
January 2025
Department of Electrical and Electronics Engineering, Sri Sivasubramaniya Nadar College of Engineering, Chennai, India. Electronic address:
Cardiovascular disease (CVD) is caused by the abnormal functioning of the heart which results in a high mortality rate across the globe. The accurate and early prediction of various CVDs from the electrocardiogram (ECG) is vital for the prevention of deaths caused by CVD. Artificial intelligence (AI) is used to categorize and accurately predict various CVDs.
View Article and Find Full Text PDFJ Clin Med
January 2025
Guthrie Cortland Medical Center, Cortland, NY 13045, USA.
Artificial intelligence (AI) in echocardiography represents a transformative advancement in cardiology, addressing longstanding challenges in cardiac diagnostics. Echocardiography has traditionally been limited by operator-dependent variability and subjective interpretation, which impact diagnostic reliability. This study evaluates the role of AI, particularly machine learning (ML), in enhancing the accuracy and consistency of echocardiographic image analysis and its potential to complement clinical expertise.
View Article and Find Full Text PDFAutoimmun Rev
January 2025
Department of Clinical Laboratory, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China,. Electronic address:
Background: Dilated cardiomyopathy (DCM) is a prevalent myocardial disorder characterized by impaired cardiac function affecting either the left ventricle or both ventricles. Accumulating evidence suggests that autoimmunity represents a key mechanism implicated in its pathogenesis, as several abundant autoantibodies have been identified in patients with the condition. However, the prevalence of these antibodies (Abs) in patients with DCM compared to that in both healthy controls (HCs) and those with ischemic cardiomyopathy (ICM), as well as their potential association with DCM, remains unclear.
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