Abstract
This work presents a low-cost, simple and adequately reliable voltammetric alternative to the determination of uric acid (UA) in human serum by the enzymatic colorimetric standard method. UA is an organic molecule of great biomedical interest since its level is used in the diagnosis of several diseases. The quality of the electrochemical measurements was evaluated by comparing their expanded uncertainty with a target (i.e. maximum admissible) value of 0.56 mg dL−1 (one eighth of UA ranges of healthy individuals) and by analysing spiked serum and human serum samples measured by the standard method. The modified working electrode has 25 % lignin, 60 % nanocarbon, 15 % mineral oil and a copper electrodeposit. Due to the vulnerability of voltammetric techniques to matrix effects and to the small amount of serum samples, it is used the standard addition method with cumulative analyte additions for electrode calibration. The measurement uncertainty was estimated by the “bottom-up” approach where uncertainty components were combined using either the uncertainty propagation law or the numerical Kragten method. The analytical procedure was successfully applied to the analysis of physiological serums spiked at 1.0 mg dL−1, 3.0 mg dL−1, 5.0 mg dL−1, 7.0 mg dL−1 or 9.0 mg dL−1 of UA and two human serum samples. The results of analysed serums estimated by the voltammetric procedure have adequately low uncertainty and are metrologically equivalent (i.e. compatible) to the reference values estimated by the spiking process or by the standard method. Therefore, the developed voltammetric measurement procedure is a promising alternative to the standard procedure.
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The laboratory of clinical analysis of the Fundação Educacional de Fernandópolis, the Fundação para a Ciência e a Tecnologia (FCT) and the Universidade Estadual Paulista (IBILCE/UNESP) is acknowledged.
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Dadamos, T.R.L., Damaceno, A.J., Fertonani, F.L. et al. Standard addition method with cumulative spikes: uric acid determination in human serum by voltammetry with optimized uncertainty. Accred Qual Assur 23, 337–348 (2018). https://doi.org/10.1007/s00769-018-1350-8
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DOI: https://doi.org/10.1007/s00769-018-1350-8