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肺炎的当前诊断技术:范围综述。

Current Diagnostic Techniques for Pneumonia: A Scoping Review.

机构信息

College of Speech, Language, and Hearing Sciences, Ziauddin University, Karachi 75000, Pakistan.

Faculty of Computing and Applied Sciences, Sir Syed University of Engineering and Technology, Karachi 75300, Pakistan.

出版信息

Sensors (Basel). 2024 Jul 1;24(13):4291. doi: 10.3390/s24134291.

Abstract

Community-acquired pneumonia is one of the most lethal infectious diseases, especially for infants and the elderly. Given the variety of causative agents, the accurate early detection of pneumonia is an active research area. To the best of our knowledge, scoping reviews on diagnostic techniques for pneumonia are lacking. In this scoping review, three major electronic databases were searched and the resulting research was screened. We categorized these diagnostic techniques into four classes (i.e., lab-based methods, imaging-based techniques, acoustic-based techniques, and physiological-measurement-based techniques) and summarized their recent applications. Major research has been skewed towards imaging-based techniques, especially after COVID-19. Currently, chest X-rays and blood tests are the most common tools in the clinical setting to establish a diagnosis; however, there is a need to look for safe, non-invasive, and more rapid techniques for diagnosis. Recently, some non-invasive techniques based on wearable sensors achieved reasonable diagnostic accuracy that could open a new chapter for future applications. Consequently, further research and technology development are still needed for pneumonia diagnosis using non-invasive physiological parameters to attain a better point of care for pneumonia patients.

摘要

社区获得性肺炎是最致命的传染病之一,尤其是对婴儿和老年人而言。鉴于病原体种类繁多,准确的早期肺炎检测是一个活跃的研究领域。据我们所知,目前缺乏针对肺炎诊断技术的范围综述。在本次范围综述中,我们检索了三个主要的电子数据库,并对检索结果进行了筛选。我们将这些诊断技术分为四类(即基于实验室的方法、基于影像学的技术、基于声学的技术和基于生理测量的技术),并总结了它们的最新应用。主要研究偏向于基于影像学的技术,尤其是在 COVID-19 之后。目前,在临床环境中,胸部 X 光检查和血液检查是最常用的诊断工具;然而,我们需要寻找更安全、非侵入性和更快速的诊断技术。最近,一些基于可穿戴传感器的非侵入性技术实现了合理的诊断准确性,这为未来的应用开辟了新篇章。因此,使用非侵入性生理参数进行肺炎诊断仍需要进一步的研究和技术开发,以实现更好的肺炎患者护理点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d337/11244398/d88a681c05b5/sensors-24-04291-g001.jpg

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