本文由小咖机器人翻译整理

期刊来源：Lancet

原文链接：https://doi.org/10.1016/S0140-6736(23)02754-X

摘要内容如下：

瓣膜性心脏病（VHD）在老龄化人群中越来越普遍，给诊断和管理带来了挑战。这个由两部分组成的系列对VHD中不断变化的概念进行了全面的回顾，包括诊断、干预时机、新的管理策略和研究现状。第一篇论文强调了在成像和经导管技术方面取得的显著进展，有效地解决了治疗悖论，即VHD风险最高的人群往往接受最少的治疗。这些进展吸引了临床医生、研究人员、工程师、设备制造商和投资者的注意，导致了基于病理生理学和多学科策略的VHD管理治疗方法的探索和建议。本系列论文重点关注涉及计算、药理学和生物工程方法的创新，这些方法正在改变VHD患者的诊断和管理。人工智能和数字方法正在增强筛查、诊断和计划程序，成像和临床数据的整合正在改善VHD严重程度的分类。人工智能技术的出现，包括所谓的数字双胞胎（如计算机生成的心脏复制品），正在帮助开发增强风险分层、预测和个体化治疗靶向的新策略。各种新的分子靶点和新的药理学策略正在开发中，包括多组学，即用于整合复杂生物大数据的分析方法，以找到阻止VHD进展的新途径。此外，已经进行了努力来设计心脏瓣膜组织并提供能够生长和生物整合的活瓣膜导管。总体而言，这些进展强调了早期检测、个性化管理和尖端干预的重要性，以在不断发展的VHD环境中优化结果。尽管必须克服一些挑战，但这些突破代表着推进以患者为中心的研究的机会。

英文原文如下：

Abstracts

Valvular heart disease (VHD) is becoming more prevalent in an ageing population, leading to challenges in diagnosis and management. This two-part Series offers a comprehensive review of changing concepts in VHD, covering diagnosis, intervention timing, novel management strategies, and the current state of research. The first paper highlights the remarkable progress made in imaging and transcatheter techniques, effectively addressing the treatment paradox wherein populations at the highest risk of VHD often receive the least treatment. These advances have attracted the attention of clinicians, researchers, engineers, device manufacturers, and investors, leading to the exploration and proposal of treatment approaches grounded in pathophysiology and multidisciplinary strategies for VHD management. This Series paper focuses on innovations involving computational, pharmacological, and bioengineering approaches that are transforming the diagnosis and management of patients with VHD. Artificial intelligence and digital methods are enhancing screening, diagnosis, and planning procedures, and the integration of imaging and clinical data is improving the classification of VHD severity. The emergence of artificial intelligence techniques, including so-called digital twins-eg, computer-generated replicas of the heart-is aiding the development of new strategies for enhanced risk stratification, prognostication, and individualised therapeutic targeting. Various new molecular targets and novel pharmacological strategies are being developed, including multiomics-ie, analytical methods used to integrate complex biological big data to find novel pathways to halt the progression of VHD. In addition, efforts have been undertaken to engineer heart valve tissue and provide a living valve conduit capable of growth and biological integration. Overall, these advances emphasise the importance of early detection, personalised management, and cutting-edge interventions to optimise outcomes amid the evolving landscape of VHD. Although several challenges must be overcome, these breakthroughs represent opportunities to advance patient-centred investigations.

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