ArticleUrolithiasis2016
The potential of at-home prediction of the formation of urolithiasis by simple multi-frequency electrical conductivity of the urine and the comparison of its performance with urine ion-related indices, color and specific gravity.
Article in Urolithiasis, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Development of a readout circuit and platform for uric acid measurement for urolithiasis application.Frontiers in bioengineering and biotechnology · 2026Article
- Estimated Osmolality by Measured Conductivity in 24 h Urine Renal Stone Patients: A Useful Tool for Monitoring Dietary Sodium and Protein Excess.Journal of clinical medicine · 2025Article
- Urine and stone analysis for the investigation of the renal stone former: a consensus conference.Urolithiasis · 2021Article
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Authors and funding
7 authors.
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Abstract
It is important to control daily diet, water intake and life style as well as monitor the quality of urine for urolithiasis prevention. For decades, many ion-related indices have been developed for predicting the formation of urinary stones or urolithiasis, such as EQUILs, relative supersaturation (RSS), Tiselius indices (TI), Robertson risk factor algorithms (RRFA) and more recently, the Bonn risk index. However, they mostly demand robust laboratory analysis, are work-intensive, and even require complex computational programs to get the concentration patterns of several urine analytes. A simple and fast platform for measuring multi-frequency electrical conductivity (MFEC) of morning spot urine (random urine) to predict the onset of urolithiasis was implemented in this study. The performance thereof was compared to ion-related indices, urine color and specific gravity. The concentrations of relevant ions, color, specific gravity (SG) and MFEC (MFEC tested at 1, 10, 100, 5001 KHz and 1 MHz) of 80 random urine samples were examined after collection. Then, the urine samples were stored at 4 °C for 24 h to determine whether sedimentation would occur or not. Ion-activity product index of calcium oxalate (AP(CaOx) EQ2) was calculated. The correlation between AP(CaOx) EQ2, urine color, SG and MFEC were analyzed. AP(CaOx) EQ2, urine color and MFEC (at 5 frequencies) all demonstrated good prediction (p = 0.01, 0.01, 0.01, respectively) for stone formation. The positive correlation between AP(CaOx) EQ2 and MFEC is also significant (p = 0.01). MFEC provides a good metric for predicting the onset of urolithiasis, which is comparable to conventional ion-related indices and urine color. This technology can be implemented with much ease for objectively monitoring the quality of urine at points-of-care or at home.
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