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用于慢性冠状动脉综合征监测与管理的传感器技术进展

Advancements in Sensor Technology for Monitoring and Management of Chronic Coronary Syndrome.

作者信息

Cricco Riccardo, Segreti Andrea, Ferro Aurora, Beato Stefano, Castaldo Gaetano, Ciancio Martina, Sacco Filippo Maria, Pennazza Giorgio, Ussia Gian Paolo, Grigioni Francesco

机构信息

Department of Cardiovascular Sciences, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo 200, 00128 Rome, Italy.

Unit of Electronics for Sensor Systems, Campus Bio-Medico University, 00128 Rome, Italy.

出版信息

Sensors (Basel). 2025 Jul 24;25(15):4585. doi: 10.3390/s25154585.


DOI:10.3390/s25154585
PMID:40807750
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12349277/
Abstract

Chronic Coronary Syndrome (CCS) significantly impacts quality of life and increases the risk of adverse cardiovascular events, remaining the leading cause of mortality worldwide. The use of sensor technology in medicine is emerging as a promising approach to enhance the management and monitoring of patients across a wide range of diseases. Recent advancements in engineering and nanotechnology have enabled the development of ultra-small devices capable of collecting data on critical physiological parameters. Several sensors integrated in wearable and implantable devices, instruments for exhaled gas analysis, smart stents and tools capable of real time biochemical analysis have been developed, and some of them have demonstrated to be effective in CCS management. Their application in CCS could provide valuable insights into disease progression, ischemic events, and patient responses to therapy. Moreover, sensor technologies can support the personalization of treatment plans, enable early detection of disease exacerbations, and facilitate prompt interventions, potentially reducing the need for frequent hospital visits and unnecessary invasive diagnostic procedures such as coronary angiography. This review explores sensor integration in CCS care, highlighting technological advances, clinical potential, and implementation challenges.

摘要

慢性冠状动脉综合征(CCS)严重影响生活质量,并增加不良心血管事件的风险,仍然是全球范围内的主要死因。医学中传感器技术的应用正在成为一种有前景的方法,可加强对各种疾病患者的管理和监测。工程学和纳米技术的最新进展使得能够开发出能够收集关键生理参数数据的超小型设备。已经开发了集成在可穿戴和植入式设备中的几种传感器、呼出气体分析仪器、智能支架以及能够进行实时生化分析的工具,其中一些已证明在CCS管理中有效。它们在CCS中的应用可以为疾病进展、缺血事件以及患者对治疗的反应提供有价值的见解。此外,传感器技术可以支持治疗计划的个性化,实现疾病恶化的早期检测,并促进及时干预,有可能减少频繁住院的需求以及诸如冠状动脉造影等不必要的侵入性诊断程序。本综述探讨了CCS护理中的传感器集成,强调了技术进步、临床潜力和实施挑战。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3510/12349277/034f6c1d9158/sensors-25-04585-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3510/12349277/4f31d5b5feff/sensors-25-04585-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3510/12349277/034f6c1d9158/sensors-25-04585-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3510/12349277/4f31d5b5feff/sensors-25-04585-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3510/12349277/034f6c1d9158/sensors-25-04585-g002.jpg

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本文引用的文献

[1]
Machine learning-assisted point-of-care diagnostics for cardiovascular healthcare.

Bioeng Transl Med. 2025-2-3

[2]
Artificial Intelligence and Its Role in the Diagnosis and Prediction of Adverse Events in Acute Coronary Syndrome: A Narrative Review of the Literature.

Life (Basel). 2025-3-21

[3]
AI Applications for Chronic Condition Self-Management: Scoping Review.

J Med Internet Res. 2025-4-8

[4]
Practicality meets precision: Wearable vest with integrated multi-channel PCG sensors for effective coronary artery disease pre-screening.

Comput Biol Med. 2025-5

[5]
A smartphone-guided secondary prevention digital health application reduces systolic blood pressure in patients with chronic coronary syndrome and insufficient blood pressure control.

Front Cardiovasc Med. 2025-2-10

[6]
Machine Learning Model Discriminate Ischemic Heart Disease Using Breathome Analysis.

Biomedicines. 2024-12-11

[7]
Rapid prediction of acute thrombosis via nanoengineered immunosensors with unsupervised clustering for multiple circulating biomarkers.

Sci Adv. 2024-12-13

[8]
Enhanced CAD Detection Using Novel Multi-Modal Learning: Integration of ECG, PCG, and Coupling Signals.

Bioengineering (Basel). 2024-10-30

[9]
Implementing sensor-based digital health technologies in clinical trials: Key considerations from the eCOA Consortium.

Clin Transl Sci. 2024-11

[10]
Breath Analysis via Gas Chromatography-Mass Spectrometry (GC-MS) in Chronic Coronary Syndrome (CCS): A Proof-of-Concept Study.

J Clin Med. 2024-10-1

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