Issue 13, 2023

A fluorescence-based sweat test sensor in a proof-of-concept clinical study for COVID-19 screening diagnosis

Abstract

During the corona virus disease 2019 (COVID-19) pandemic period, rapid screening of covid-19 patients has been of great interest by developing a fluorescent sensor for complexation with nonanal, which is a marker for Covid-19 detection in sweat. Solid phase micro-extraction gas chromatography-mass spectrometry (SPME GC-MS) was initially used to quantify nonanal in armpit sweat samples based on an external calibration curve. A sample containing a nonanal content above the threshold of 1.04 μL is expected to be COVID-19 positive with a sensitivity and specificity of 87% and 89%, respectively, validated by comparison with RT-PCR results. For more practical applications, helicene dye-encapsulated ethyl cellulose, namely EC@dyeNH, was applied to screen 140 sweat samples collected from the foreheads of volunteers. The mixed sensor and sweat solution droplets were then visualized and imaged under blacklight. The COVID-19 positive droplets exhibited yellow fluorescence emission, the brightness of which could be measured by using ImageJ in the grey scale. With the optimum color intensity of >73 for positive results, the screening performance was observed with a sensitivity and specificity of 96% and 93%, respectively. The overall test time of this method is approximately less than 15 min. This alternative method offers a promising practical screening approach for the diagnosis of COVID-19 in sweat.

Graphical abstract: A fluorescence-based sweat test sensor in a proof-of-concept clinical study for COVID-19 screening diagnosis

Supplementary files

Article information

Article type
Paper
Submitted
20 Mar 2023
Accepted
19 May 2023
First published
02 Jun 2023

Analyst, 2023,148, 2956-2964

A fluorescence-based sweat test sensor in a proof-of-concept clinical study for COVID-19 screening diagnosis

I. Thaveesangsakulthai, J. Jongkhumkrong, K. Chatdarong, P. Torvorapanit, W. Sukbangnop, T. Sooksimuang, C. Kulsing and B. Tomapatanaget, Analyst, 2023, 148, 2956 DOI: 10.1039/D3AN00429E

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