E.Co.Tech 呼吸分析仪:针对轻度和非吸烟者的无创 COVID-19 诊断工具试点研究

Ivneet Banga, Kordel France, Anirban Paul and Shalini Prasad*, 
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引用次数: 0

摘要

呼出气体分析是了解人体新陈代谢状态的一种无创方法。本研究的重点是创新型电化学手持式呼吸分析仪 COVID-19 传感技术(E.Co.Tech)在预测 COVID-19 感染方面的功效,尤其是在从不吸烟或曾经吸烟的人群中。该设备采用的电化学鼻技术旨在分辨呼出一氧化氮水平的变化,而一氧化氮水平的变化与 COVID-19 相关的呼吸道炎症有关。该方法将该设备与基于机器学习的算法相结合,该算法是在来自感染者和非感染者的不同呼吸曲线数据集上训练出来的。研究人员招募了 46 名参与者,其中包括从不吸烟或曾经吸烟的人。每位参与者都使用 E.Co.Tech 原型设备和 iHealth COVID-19 抗原快速检测仪进行了测试。通过计算灵敏度、特异性、阳性预测值和阴性预测值 (NPV) 来评估该设备的性能。结果表明,该设备在这一人群中的特异性(91.11%)和 NPV(97.62%)都很高。该案例研究强调了 E.Co.Tech 作为 COVID-19 床旁诊断的重要工具的潜力,尤其是在有特殊吸烟史的人群中。该技术灵敏度高、特异性强、结果迅速,因此很有希望在资源有限的环境和及时检测对有效公共卫生管理至关重要的情况下应用。有必要进一步开展大规模临床试验和实际验证,以确定该设备在不同人群中的实用性。
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E.Co.Tech Breathalyzer: A Pilot Study of a Non-invasive COVID-19 Diagnostic Tool for Light and Non-smokers

Analysis of exhaled breath offers a noninvasive approach to understanding the metabolic state of the body. This study focuses on the efficacy of an innovative Electrochemical Hand-held Breathalyzer COVID-19 Sensing Technology (E.Co.Tech) for predicting COVID-19 infection, specifically in populations of never or former light smokers. The electrochemical nose technology used in this device aims to discriminate changes in exhaled nitric oxide levels, which are associated with COVID-19-linked respiratory inflammation. The methodology combines the device with a machine learning-based algorithm trained on a diverse data set of breath profiles from both infected and noninfected individuals. A cohort of 46 participants, consisting of never or former light smokers, was recruited. Each participant was tested using the E.Co.Tech prototype device and an iHealth COVID-19 antigen rapid test. The performance of the device was assessed by calculating sensitivity, specificity, positive predictive value, and negative predictive value (NPV). The results demonstrated high specificity (91.11%) and NPV (97.62%) for the device in this demographic group. This case study underscores the potential of E.Co.Tech as a valuable tool for point-of-care COVID-19 diagnosis, particularly in populations with unique smoking histories. The technology’s high sensitivity and specificity, along with its rapid results, make it a promising candidate for deployment in resource-limited settings and situations where timely detection is crucial for effective public health management. Further large-scale clinical trials and real-world validations are necessary to establish the device’s utility across diverse population groups.

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来源期刊
ACS Measurement Science Au
ACS Measurement Science Au 化学计量学-
CiteScore
5.20
自引率
0.00%
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0
期刊介绍: ACS Measurement Science Au is an open access journal that publishes experimental computational or theoretical research in all areas of chemical measurement science. Short letters comprehensive articles reviews and perspectives are welcome on topics that report on any phase of analytical operations including sampling measurement and data analysis. This includes:Chemical Reactions and SelectivityChemometrics and Data ProcessingElectrochemistryElemental and Molecular CharacterizationImagingInstrumentationMass SpectrometryMicroscale and Nanoscale systemsOmics (Genomics Proteomics Metabonomics Metabolomics and Bioinformatics)Sensors and Sensing (Biosensors Chemical Sensors Gas Sensors Intracellular Sensors Single-Molecule Sensors Cell Chips Arrays Microfluidic Devices)SeparationsSpectroscopySurface analysisPapers dealing with established methods need to offer a significantly improved original application of the method.
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