Suppr超能文献

高血压领域的争议:支持使用人工智能进行高血压诊断和管理的观点

Controversy in Hypertension: Pro-Side of the Argument Using Artificial Intelligence for Hypertension Diagnosis and Management.

作者信息

Armoundas Antonis A, Ahmad Faraz S, Attia Zachi I, Doudesis Dimitrios, Khera Rohan, Kyriakoulis Konstantinos G, Stergiou George S, Tang W H Wilson

机构信息

Cardiovascular Research Center, Massachusetts General Hospital and Broad Institute, Massachusetts Institute of Technology, Boston (A.A.A.).

Division of Cardiology, Department of Medicine, Northwestern University, Feinberg School of Medicine, Chicago, IL (F.S.A.).

出版信息

Hypertension. 2025 Jun;82(6):929-944. doi: 10.1161/HYPERTENSIONAHA.124.22349. Epub 2025 Mar 17.

Abstract

Hypertension presents the largest modifiable public health challenge due to its high prevalence, its intimate relationship to cardiovascular diseases, and its complex pathogenesis and pathophysiology. Low awareness of blood pressure elevation and suboptimal hypertension diagnosis serve as the major hurdles in effective hypertension management. Advances in artificial intelligence in hypertension have permitted the integrative analysis of large data sets including omics, clinical (with novel sensor and wearable technologies), health-related, social, behavioral, and environmental sources, and hold transformative potential in achieving large-scale, data-driven approaches toward personalized diagnosis, treatment, and long-term management. However, although the emerging artificial intelligence science may advance the concept of precision hypertension in discovery, drug targeting and development, patient care, and management, its clinical adoption at scale today is lacking. Recognizing that clinical implementation of artificial intelligence-based solutions need evidence generation, this opinion statement examines a clinician-centric perspective of the state-of-art in using artificial intelligence in the management of hypertension and puts forward recommendations toward equitable precision hypertension care.

摘要

高血压因其高患病率、与心血管疾病的密切关系以及复杂的发病机制和病理生理学,成为最大的可改变的公共卫生挑战。血压升高的知晓率低和高血压诊断不理想是有效管理高血压的主要障碍。高血压领域人工智能的进展使得对包括组学、临床(借助新型传感器和可穿戴技术)、健康相关、社会、行为和环境数据来源在内的大数据集进行综合分析成为可能,并在实现大规模、数据驱动的个性化诊断、治疗和长期管理方面具有变革潜力。然而,尽管新兴的人工智能科学可能在发现、药物靶点和开发、患者护理及管理方面推进精准高血压的概念,但目前其在临床上的大规模应用仍很缺乏。认识到基于人工智能的解决方案的临床应用需要生成证据,本观点声明从临床医生的角度审视了在高血压管理中使用人工智能的最新进展,并提出了实现公平的精准高血压护理的建议。

相似文献

1
Controversy in Hypertension: Pro-Side of the Argument Using Artificial Intelligence for Hypertension Diagnosis and Management.
Hypertension. 2025 Jun;82(6):929-944. doi: 10.1161/HYPERTENSIONAHA.124.22349. Epub 2025 Mar 17.
2
Artificial Intelligence in Hypertension: Seeing Through a Glass Darkly.
Circ Res. 2021 Apr 2;128(7):1100-1118. doi: 10.1161/CIRCRESAHA.121.318106. Epub 2021 Apr 1.
4
Future Direction for Using Artificial Intelligence to Predict and Manage Hypertension.
Curr Hypertens Rep. 2018 Jul 6;20(9):75. doi: 10.1007/s11906-018-0875-x.
5
Artificial Intelligence and Hypertension: Recent Advances and Future Outlook.
Am J Hypertens. 2020 Nov 3;33(11):967-974. doi: 10.1093/ajh/hpaa102.
6
Applications of artificial intelligence for hypertension management.
J Clin Hypertens (Greenwich). 2021 Mar;23(3):568-574. doi: 10.1111/jch.14180. Epub 2021 Feb 3.
7
Precision Hypertension.
Hypertension. 2024 Apr;81(4):702-708. doi: 10.1161/HYPERTENSIONAHA.123.21710. Epub 2023 Dec 19.
8
Perspective of artificial intelligence in healthcare data management: A journey towards precision medicine.
Comput Biol Med. 2023 Aug;162:107051. doi: 10.1016/j.compbiomed.2023.107051. Epub 2023 May 30.
10
Personalized medicine-a modern approach for the diagnosis and management of hypertension.
Clin Sci (Lond). 2017 Nov 6;131(22):2671-2685. doi: 10.1042/CS20160407. Print 2017 Nov 15.

引用本文的文献

1
Machine learning based, subject-specific, gender and race independent, non-invasive estimation of the arterial blood pressure.
NPJ Cardiovasc Health. 2025;2(1):41. doi: 10.1038/s44325-025-00075-5. Epub 2025 Aug 1.
2
Access to digital health technologies: personalized framework and global perspectives.
Nat Rev Cardiol. 2025 Jul 16. doi: 10.1038/s41569-025-01184-5.

本文引用的文献

1
Impact of Social Determinants of Health on Cardiovascular Disease.
J Am Heart Assoc. 2025 Mar 4;14(5):e039031. doi: 10.1161/JAHA.124.039031.
2
Identification of novel hypertension biomarkers using explainable AI and metabolomics.
Metabolomics. 2024 Nov 3;20(6):124. doi: 10.1007/s11306-024-02182-3.
4
5
Barriers to Optimal Clinician Guideline Adherence in Management of Markedly Elevated Blood Pressure: A Qualitative Study.
JAMA Netw Open. 2024 Aug 1;7(8):e2426135. doi: 10.1001/jamanetworkopen.2024.26135.
7
Brief Review and Primer of Key Terminology for Artificial Intelligence and Machine Learning in Hypertension.
Hypertension. 2025 Jan;82(1):26-35. doi: 10.1161/HYPERTENSIONAHA.123.22347. Epub 2024 Jul 16.
8
Data Interoperability for Ambulatory Monitoring of Cardiovascular Disease: A Scientific Statement From the American Heart Association.
Circ Genom Precis Med. 2024 Jun;17(3):e000095. doi: 10.1161/HCG.0000000000000095. Epub 2024 May 23.
9
Identification of the Molecular Components of Enhancer-Mediated Gene Expression Variation in Multiple Tissues Regulating Blood Pressure.
Hypertension. 2024 Jul;81(7):1500-1510. doi: 10.1161/HYPERTENSIONAHA.123.22538. Epub 2024 May 15.
10
Application of artificial intelligence in hypertension.
Clin Hypertens. 2024 May 1;30(1):11. doi: 10.1186/s40885-024-00266-9.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验