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在导管实验室诊断心绞痛和非阻塞性冠心病患者。

Diagnosis of patients with angina and non-obstructive coronary disease in the catheter laboratory.

机构信息

The BHF Centre of Excellence and the NIHR Biomedical Research Centre at the School of Cardiovascular Medicine and Sciences, King's College London, London, UK.

British Heart Foundation Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.

出版信息

Heart. 2019 Oct;105(20):1536-1542. doi: 10.1136/heartjnl-2019-315042. Epub 2019 Jul 31.

Abstract

Around 40% of all patients undergoing angiography are found to have normal coronary arteries or non-obstructive coronary artery disease (NOCAD). Despite the high prevalence, this is a group who rarely receive a definitive diagnosis, are frequently labelled and managed inappropriately and by and large, continue to remain symptomatic. Half of this group will have coronary microvascular dysfunction (CMD), associated with a higher rate of major adverse cardiovascular events; identifying CMD represents a therapeutic target of unmet need. As the pressure wire has revolutionised our ability to interrogate epicardial coronary disease during the time of angiography, measuring flow can similarly classify NOCAD during a single procedure. Assessment of flow is a function that is already integral to some pressure wires and furthermore, the familiarity and usage of the combined Doppler and pressure wire is rapidly increasing-these are techniques that readily lend themselves to the skillset of a practising interventional cardiologist. We present a structured algorithm designed for cardiologists who frequently encounter NOCAD in the catheter laboratory, identifying specific disease phenotypes within this heterogeneous population with linked therapy. This review paper clearly explains the rationale for this algorithm and outlines its applicability to routine clinical practice and also, the importance of phenotyping for future research. Ultimately, personalised therapy could improve outcomes for both patients and healthcare providers; while these approaches in turn will need robust evaluation to ensure that they improve both clinical outcomes and health economic benefits, this proposal will provide a framework for future trials and evaluations.

摘要

大约 40%接受血管造影的患者被发现具有正常的冠状动脉或非阻塞性冠状动脉疾病(NOCAD)。尽管患病率很高,但这是一组很少得到明确诊断的患者,他们经常被错误地贴上标签和治疗,而且总的来说,他们仍然有症状。这群人中的一半会有冠状动脉微血管功能障碍(CMD),与更高的主要不良心血管事件率相关;确定 CMD 代表了一个未满足需求的治疗靶点。由于压力导丝改变了我们在血管造影时检查心外膜冠状动脉疾病的能力,因此在单次操作中测量血流也可以对 NOCAD 进行分类。评估血流是一些压力导丝的固有功能,此外,联合多普勒和压力导丝的熟悉程度和使用正在迅速增加——这些技术非常适合有经验的介入心脏病学家的技能。我们提出了一种针对经常在导管实验室遇到 NOCAD 的心脏病专家的结构化算法,根据该算法可以确定该异质人群中特定的疾病表型,并为其提供相关治疗。本文综述清楚地解释了该算法的基本原理,并概述了其在常规临床实践中的适用性,以及表型对未来研究的重要性。最终,个性化治疗可以改善患者和医疗保健提供者的预后;而这些方法反过来也需要进行严格的评估,以确保它们既改善临床结果,又改善健康经济效益,本方案将为未来的试验和评估提供框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0668/6839722/cd843691c957/heartjnl-2019-315042f01.jpg

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