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The fast and reliable determination of concentrations of blood, plasma or serum constituents is a major requirement in clinical chemistry. We explored Raman spectroscopy as a reagent-free tool for predicting the concentrations of different parameters in serum and serum ultrafiltrate. In an investigation using samples from 247 blood donors (which we believe to be the largest study on Raman spectroscopy of serum so far) the concentrations of glucose, triglycerides, urea, total protein, cholesterol, high density lipoprotein, low density lipoprotein and uric acid were determined with an accuracy within the clinically interesting range. After training a multivariate algorithm for data analysis, using 148 samples, concentrations were predicted blindly for the remaining 99 serum samples based solely on the Raman spectra. Relative errors of prediction around 12% were obtained. Moreover, to the best of our knowledge, differentiation between HDL and LDL cholesterol as well as the quantification of uric acid was for the first time successfully accomplished for serum-based Raman spectroscopy. Finally, we showed that ultrafiltration can efficiently reduce fluorescent light background to improve prediction accuracy such that the relative coefficient of variation was reduced for glucose and urea in ultrafiltrate by more than a factor of 2 when compared to serum.
Rohleder et al. (Thu,) studied this question.
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