Preparation of Urine Samples for Trace Metal Determination: A Study with Aluminium Analysis by Inductively Coupled Plasma Optical Emission Spectrometry

Abstract

Urinary analysis of trace metals forms a significant role in clinical chemistry, but the optimal preparation and analysis of urine samples has not been investigated. Human urine is generally supersaturated with dissolved solids. Therefore, samples often precipitate following collection. X-ray microanalysis showed that this precipitate was predominantly rich in calcium and phosphorus but could include some trace metals from urine, potentially lowering their concentrations in solution. Hence, the precipitate must be fully redissolved for accurate analysis of trace metals in urine. Methods are emphasized for the best collection and preparation of urine samples for subsequent trace metal analysis; in this work inductively coupled plasma optical emission spectrometry (ICPOES) was used for the analysis of aluminium. For optimal accuracy, peak profiles were collected over 396.147 nm-396.157 nm. Urinary aluminium levels were investigated from 10 healthy volunteers and concentrations were obtained using either aqueous, pooled or individual urine-based standard curves. Since urine has a highly variable matrix, individual sample-based standards, which are unique to that particular sample, gave the most accurate results. However, where sample size is small or sample numbers are unfeasibly large, pooled sample-based standards give good approximations to within 15% and, with appropriate validation, other elements as internal standards could also be used for approximations. Aqueous standards should be avoided. Spike-recovery experiments confirmed these data since individual sample based standards showed optimal recovery [99.3 (4.4)%], while pooled sample-based standards were a close proxy [101.6 (9.2)%] but aqueous standards were inappropriate [137.4 (12.8)%]. Postprandial urinary aluminium levels of the 10 volunteers were [7.2 (3.7)μg/L] after analysis using individual sample-based standard curves.