Non-invasive detection of COVID-19 using a microfluidic-based colorimetric sensor array sensitive to urinary...

Area of Science:

• Biomedical Engineering
• Analytical Chemistry
• Point-of-Care Diagnostics

Background:

• Current COVID-19 detection methods can be costly and time-consuming.
• There is a need for rapid, accessible diagnostic tools for infectious diseases and metabolic disorders.

Purpose of the Study:

• To develop and evaluate a colorimetric sensor array for detecting COVID-19 using urine metabolites.
• To assess the sensor's potential for identifying other diseases like chronic kidney disease, liver disorder, and diabetes.

Main Methods:

• A microfluidic paper-based sensor array utilizing gold/silver nanoparticles, metalloporphyrins, metal ion complexes, and pH indicators was designed.
• Urine samples from COVID-19 patients, healthy controls, and cured individuals were analyzed.
• Color changes were visually observed and quantified using image analysis software and principal component analysis-discriminant analysis.

Main Results:

• The sensor array generated distinct color patterns ('fingerprints') for different participant groups.
• The assay achieved sensitivities of 73.3% for COVID-19 patients, 74.5% for healthy controls, and 66.6% for cured individuals.
• The sensor demonstrated potential for detecting other metabolic disorders beyond COVID-19.

Conclusions:

• The developed sensor array offers a feasible, rapid, and cost-effective alternative for disease detection.
• Further studies with larger sample sizes are needed to validate the sensor's performance for various diseases.
• This technology holds promise for point-of-care diagnostics of infectious and metabolic diseases.