Microfluidic Chip with Integrated Whole Blood Separation for Simultaneous Accurate Quantification of Multiple Chronic Kidney Disease Markers and Long-Term Monitoring

Chronic kidney disease (CKD) has become a public health burden, with a high mortality rate and a trend toward youthfulness. It is imperative to develop a home monitoring system for the early diagnosis and long-term monitoring of CKD serum biomarkers. However, due to the limitations of conventional centrifugation preprocessing of whole blood samples, the real-time detection platform cannot fully meet the requirement of obtaining quantitative results directly from whole blood. Herein, a novel smartphone-assisted microfluidic chip integration of a whole blood separation point-of-care testing (POCT) system was proposed to achieve accurate quantification of CKD biomarkers uric acid (UA), creatinine (CR), and albumin (Alb) based on 30 μL of whole blood (fingertip blood). The whole blood separation module allows rapid separation of plasma from whole blood samples by vertical flow. A smartphone App for automated image recognition and processing was developed, which was applied for at-home routine healthcare. The detection limits of UA, CR, and Alb were 0.1127 mmol/L, 0.2978 μmol/L, and 0.7696 mg/mL, respectively, meeting clinical requirements. Additionally, the quantitative performance of 83 clinical whole blood samples showed high consistency with the clinical analyzer (Beckman AU 5400 automatic biochemical analyzer). This system is simple to operate and user-friendly, providing an accurate, rapid, cost-effective, and reliable detection method for the early screening and real-time monitoring of CKD, which holds significant potential in enhancing home self-management of CKD.

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Publication Details

Journal
ACS Sensors
Published
2025-07-26
DOI
https://doi.org/10.1021/acssensors.5c00491
Citations
3
Primary Topic
3D Printing in Biomedical Research
Type
article
Field-Weighted Citation Impact
2.02

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article

Microfluidic Chip with Integrated Whole Blood Separation for Simultaneous Accurate Quantification of Multiple Chronic Kidney Disease Markers and Long-Term Monitoring

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3 citations
ACS Sensors
3D Printing in Biomedical Research
2.02
article

Microfluidic Chip with Integrated Whole Blood Separation for Simultaneous Accurate Quantification of Multiple Chronic Kidney Disease Markers and Long-Term Monitoring

Haiqin Li, Xiaoye Feng, Jing Yang, Xiaochun Li, Xiaojun Ren, Patricia L. Chang
article en
3 citations

Abstract

Chronic kidney disease (CKD) has become a public health burden, with a high mortality rate and a trend toward youthfulness. It is imperative to develop a home monitoring system for the early diagnosis and long-term monitoring of CKD serum biomarkers. However, due to the limitations of conventional centrifugation preprocessing of whole blood samples, the real-time detection platform cannot fully meet the requirement of obtaining quantitative results directly from whole blood. Herein, a novel smartphone-assisted microfluidic chip integration of a whole blood separation point-of-care testing (POCT) system was proposed to achieve accurate quantification of CKD biomarkers uric acid (UA), creatinine (CR), and albumin (Alb) based on 30 μL of whole blood (fingertip blood). The whole blood separation module allows rapid separation of plasma from whole blood samples by vertical flow. A smartphone App for automated image recognition and processing was developed, which was applied for at-home routine healthcare. The detection limits of UA, CR, and Alb were 0.1127 mmol/L, 0.2978 μmol/L, and 0.7696 mg/mL, respectively, meeting clinical requirements. Additionally, the quantitative performance of 83 clinical whole blood samples showed high consistency with the clinical analyzer (Beckman AU 5400 automatic biochemical analyzer). This system is simple to operate and user-friendly, providing an accurate, rapid, cost-effective, and reliable detection method for the early screening and real-time monitoring of CKD, which holds significant potential in enhancing home self-management of CKD.

ACS SensorsVol. 10(8)
Shanxi Medical University (CN), Shanxi Academy of Medical Sciences (CN), Taiyuan University of Technology (CN)
National Natural Science Foundation of China, Natural Science Foundation of Shanxi Province
Good health and well-being
Openalex Percentile: Top 13%
3D Printing in Biomedical Research
2.02
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