A passive flow microreactor for urine creatinine test.

Chronic kidney disease (CKD) significantly affects people's health and quality of life and presents a high economic burden worldwide. There are well-established biomarkers for CKD diagnosis. However, the existing routine standard tests are lab-based and governed by strict regulations. Creatinine is commonly measured as a filtration biomarker in blood to determine estimated Glomerular Filtration Rate (eGFR), as well as a normalization factor to calculate urinary Albumin-to-Creatinine Ratio (uACR) for CKD evaluation. In this study, we developed a passive flow microreactor for colorimetric urine creatinine measurement (uCR-Chip), which is highly amenable to integration with our previously developed microfluidic urine albumin assay. The combination of the 2-phase pressure compensation (2-PPC) technique and microfluidic channel network design accurately controls the fluidic mixing ratio and chemical reaction. Together with an optimized observation window (OW) design, a uniform and stable detection signal was achieved within 7 min. The color signal was measured by a simple USB microscope-based platform to quantify creatinine concentration in the sample. The combination of the custom in-house photomask production techniques and dry-film photoresist-based lithography enabled rapid iterative design optimization and precise chip fabrication. The developed assay achieved a dynamic linear detection range up to 40 mM and a lower limit of detection (LOD) of 0.521 mM, meeting the clinical precision requirements (comparable to existing point-of-care (PoC) systems). The microreactor was validated using creatinine standards spiked into commercial artificial urine that mimics physiological matrix. Our results showed acceptable recovery rate and low matrix effect, especially for the low creatinine concentration range in comparison to a commercial PoC uACR test. Altogether, the developed uCR-Chip offers a viable PoC test for CKD assessment and provides a potential platform technology to measure various disease biomarkers.