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心脏淀粉样变性:病理生理学、诊断方法、人工智能应用及管理策略的全面综述

Cardiac Amyloidosis: A Comprehensive Review of Pathophysiology, Diagnostic Approach, Applications of Artificial Intelligence, and Management Strategies.

作者信息

Ahammed Md Ripon, Ananya Fariha Noor

机构信息

Internal Medicine, Icahn School of Medicine at Mount Sinai/New York City Health and Hospitals Queens, New York City, USA.

Internal Medicine, Dhaka Medical College and Hospital, Dhaka, BGD.

出版信息

Cureus. 2024 Jul 2;16(7):e63673. doi: 10.7759/cureus.63673. eCollection 2024 Jul.

Abstract

Cardiac amyloidosis (CA) is a serious and often fatal condition caused by the accumulation of amyloid fibrils in the heart, leading to progressive heart failure. It involves the misfolding of normally soluble proteins into insoluble amyloid fibrils, with transthyretin and light-chain amyloidosis being the most common forms affecting the heart. Advances in diagnostics, especially cardiac magnetic resonance imaging and non-invasive techniques, have improved early detection and disease management. Artificial intelligence has emerged as a diagnostic tool for cardiac amyloidosis, improving accuracy and enabling earlier intervention through advanced imaging analysis and pattern recognition. Management strategies include volume control, specific pharmacotherapies like tafamidis, and addressing arrhythmias and advanced heart failure. However, further research is needed for novel therapeutic approaches, the long-term effectiveness of emerging treatments, and the optimization of artificial intelligence applications in clinical practice for better patient outcomes. The article aims to provide an overview of CA, outlining its pathophysiology, diagnostic advancements, the role of artificial intelligence, management strategies, and the need for further research.

摘要

心脏淀粉样变性(CA)是一种严重且往往致命的疾病,由淀粉样原纤维在心脏中积聚所致,会导致进行性心力衰竭。它涉及正常可溶性蛋白质错误折叠成不溶性淀粉样原纤维,其中转甲状腺素蛋白和轻链淀粉样变性是影响心脏的最常见形式。诊断方面的进展,尤其是心脏磁共振成像和非侵入性技术,改善了早期检测和疾病管理。人工智能已成为心脏淀粉样变性的诊断工具,通过先进的成像分析和模式识别提高了准确性并实现了更早干预。管理策略包括容量控制、使用如塔非酰胺等特定药物治疗,以及处理心律失常和晚期心力衰竭。然而,对于新型治疗方法、新兴治疗的长期有效性以及优化人工智能在临床实践中的应用以获得更好的患者预后,仍需要进一步研究。本文旨在概述CA,阐述其病理生理学、诊断进展、人工智能的作用、管理策略以及进一步研究的必要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e7a/11293487/4daf3857ed7a/cureus-0016-00000063673-i01.jpg

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