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射血分数保留的心力衰竭的超声心动图报告:德尔菲共识研究

Echocardiography reporting in heart failure with preserved ejection fraction: Delphi consensus study.

作者信息

Paton Maria F, Barton Carys, Baruah Resham, Hartshorne-Evans Nick, Jenkins Geraint H, Potter Andrew, Robinson Shaun, Thakkar Raj, Zakeri Rosita, Taylor Clare J

机构信息

Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK.

Leeds Teaching Hospitals NHS Trust, Leeds, UK.

出版信息

Open Heart. 2025 Mar 28;12(1):e003063. doi: 10.1136/openhrt-2024-003063.

DOI:10.1136/openhrt-2024-003063
PMID:40154975
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11956303/
Abstract

BACKGROUND

Heart failure with preserved ejection fraction (HFpEF) is a complex clinical syndrome in which signs and symptoms of heart failure (HF) occur despite a normal left ventricular ejection fraction. Transthoracic echocardiography (TTE) is the first-line imaging modality but disparities in patient pathways across the UK can lead to delayed diagnosis and treatment. We aimed to develop and validate a consistent, clinically appropriate and practical approach for reporting the echocardiographic suspicion of HFpEF.

METHODS

Using the Delphi method, a steering group of nine UK experts identified key domains for discussion and generated consensus statements relevant to the echocardiographic detection of HFpEF. Using a four-point scale, a survey including all statements was disseminated among a wider audience of healthcare professionals to determine agreement. A consensus threshold of 75% agreement was defined as 'strong' and ≥90% as 'very strong'.

RESULTS

A total of 34 consensus statements were generated in seven domains: (1) challenges in the system approach to HFpEF; (2) enhancing referral for specialist review including echocardiography; (3) confidence in using a summary statement in an echo report; (4) identifying HFpEF and its underlying aetiology; (5) HF awareness, training and education; (6) refining multidisciplinary team roles in decision-making; (7) optimising patient experience.135 UK specialists experienced in managing HF participated in the survey, including physiologists/clinical scientists (n=43), HF specialist nurses (n=35), cardiologists (n=34), general practitioners (n=12), pharmacists (n=4) and others (n=7). 20 of 34 (59%) statements achieved very strong agreement, 10 of 34 (29%) achieved strong agreement and 4 of 34 (12%) did not meet the consensus threshold.

CONCLUSIONS

Diagnosis of HFpEF requires access to essential diagnostic tools. Establishing standardised pathways for specialist assessment and referral, including TTE reporting of HFpEF, may help eliminate diagnostic delays and geographical disparities. Further education and awareness are crucial for improving detection rates, prompt referral and patient experience.

摘要

背景

射血分数保留的心力衰竭(HFpEF)是一种复杂的临床综合征,尽管左心室射血分数正常,但仍会出现心力衰竭(HF)的体征和症状。经胸超声心动图(TTE)是一线成像方式,但英国各地患者就医途径的差异可能导致诊断和治疗延迟。我们旨在制定并验证一种一致、临床适用且实用的方法,用于报告超声心动图对HFpEF的怀疑。

方法

采用德尔菲法,由九名英国专家组成的指导小组确定了关键讨论领域,并生成了与HFpEF超声心动图检测相关的共识声明。使用四点量表,将包含所有声明的调查问卷分发给更广泛的医疗保健专业人员群体,以确定共识程度。将75%的共识阈值定义为“强”,≥90%定义为“非常强”。

结果

在七个领域共生成了34条共识声明:(1)HFpEF系统方法中的挑战;(2)加强包括超声心动图在内的专科评估转诊;(3)在超声报告中使用总结声明的信心;(4)识别HFpEF及其潜在病因;(5)HF意识、培训和教育;(6)完善多学科团队在决策中的作用;(7)优化患者体验。135名有HF管理经验的英国专家参与了调查,包括生理学家/临床科学家(n = 43)、HF专科护士(n = 35)、心脏病专家(n = 34)、全科医生(n = 12)、药剂师(n = 4)和其他人员(n = 7)。34条声明中有20条(59%)达成了非常强的共识,34条中有10条(29%)达成了强共识,34条中有4条(12%)未达到共识阈值。

结论

HFpEF的诊断需要使用必要的诊断工具。建立标准化的专科评估和转诊途径,包括HFpEF的TTE报告,可能有助于消除诊断延迟和地域差异。进一步的教育和意识对于提高检出率、及时转诊和患者体验至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f1b/11956303/0313d26694c8/openhrt-12-1-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f1b/11956303/6a56b8601940/openhrt-12-1-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f1b/11956303/6ef5d294b63a/openhrt-12-1-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f1b/11956303/0313d26694c8/openhrt-12-1-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f1b/11956303/6a56b8601940/openhrt-12-1-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f1b/11956303/6ef5d294b63a/openhrt-12-1-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f1b/11956303/0313d26694c8/openhrt-12-1-g003.jpg

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本文引用的文献

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Automated Echocardiographic Detection of Heart Failure With Preserved Ejection Fraction Using Artificial Intelligence.使用人工智能自动超声心动图检测射血分数保留的心力衰竭
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