Development and validation of an advanced electrochemical sensor for the fast and cheap determination of hydrochlorothiazide in urine samples using the Monte-Carlo method for uncertainty evaluation.

This work describes the development, optimization, and validation of an electrochemical method for the determination of hydrochlorothiazide (HCTZ) in urine. The method allows fast, cheap and reliable determinations of recent administrations of this diuretic that can be used in doping control in sport. The response of the sensor was determined by differential pulse voltammetry (DPV). The glassy carbon electrode was modified with multiwall carbon nanotubes (MWCNT) and gold nanoparticles. The sensor is calibrated in the analysed sample matrix by the cumulative standard addition method. The method validation was based on the bottom-up evaluation of the measurement uncertainty were components were combined using the Monte Carlo Method (MCM) applicable with no restrictions regarding components uncertainty value and measurement function linearity. The developed metrological models were implemented in MS-Excel spreadsheets. The adequacy of the electrochemical measurements was assessed by comparing their relative standard uncertainty with a target value of 20% and by evaluating the compatibility of measurements with determinations performed by a reference procedure. The tools developed for the construction and optimization of working electrodes are applicable to measurements of other analytes and matrices. The used cumulative standard addition method and respective measurement uncertainty models are applicable to any kind of non-destructive chemical measurement of a solution.

Standard addition method with cumulative additions: Monte Carlo uncertainty evaluation.

The cumulative standard addition method allows the calibration of an instrument affected by matrix effects when a small sample volume is available. Recently, it was developed and validated a metrologically sound procedure to estimate the uncertainty of these measurements based on the modelling of the uncertainty of the extrapolation of the calibration curve by the linear least squares regression model. However, this procedure is only applicable when the uncertainty of cumulative sample dilutions and analyte mass additions are negligible given the uncertainty of the total solution volume (v) times the instrumental signal (I) (i.e. v∙I). This work developed a measurement uncertainty model, not limited by this assumption of the quality of calibrators preparation, based on Monte Carlo simulations. This method was successfully applied to the voltammetric measurements of uric acid in human serum, using a working nanocarbon electrode modified with Cu-nanocarbon-lignin, since the uncertainty model adapts to the uncertainty of cumulative volume additions. The validated procedure was checked through the analysis of spiked physiological serum samples and human serum samples, by assessing the metrological compatibility between estimated and reference values. The measurements are reported with an expanded uncertainty not larger than a target value of 0.56 mg dL-1. The used spreadsheet is made available as supplementary material.