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Smartphone-based rapid quantitative detection of serum creatinine: Performance validation and exploration of potential application in chronic kidney disease monitoring

Medicine (Baltimore). 2025 May 16;104(20):e42508. doi: 10.1097/MD.0000000000042508.

ABSTRACT

Chronic kidney disease is a progressive condition, and serum creatinine (CR) levels are closely associated with the glomerular filtration rate, serving as a key indicator of renal function and disease progression. This study aimed to develop a smartphone-based colorimetric analysis system for the efficient and rapid quantification of serum CR and validate its performance to determine whether the method meets clinical testing standards. The CR standard solution was analyzed using a smartphone, and the R, G, and B values were plotted against the concentration. The precision, accuracy, detection limit, linear range, and clinically reportable range of the smartphone detection system were evaluated according to the National Committee for Clinical Laboratory Standards guidelines. Subsequently, 65 serum samples from healthy individuals and 26 serum samples from nephropathy patients were collected and tested using the smartphone system and an automated biochemical analyzer, respectively, to further validate the feasibility of the method. Among all the color channels, the G value showed the strongest correlation with CR concentration, and therefore was used to establish the standard curve. The validation of the assay system demonstrated that its precision and accuracy met clinical standards. The limit of blank, limit of detection, and limit of quantification were 29.95 μmol/L, 32.39 μmol/L, and 36.61 μmol/L, respectively. The linear range was 36.75 to 200.46 μmol/L, whereas the clinical reporting range spanned from 36.61 to 801.84 μmol/L. Furthermore, the results obtained from the 2 methods were statistically analyzed, revealing a strong correlation between the 2 sets of data. Smartphone-based serum CR testing meets clinical standards, and its portability and efficiency position it as a valuable tool for screening and monitoring chronic kidney disease.

PMID:40388728 | DOI:10.1097/MD.0000000000042508

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