| Popis: |
Determination of physiological concentrations of glucose in whole blood or blood serum using infrared (IR) spectrometry is complicated due to combined effects of spectral variations caused by fluctuations in temperature, pH and other blood constituents with overlapping spectra. In order to initiate systematic examination of these effects, we studied the effects of temperature and pH changes on the spectral variation of phosphate buffered saline (PBS) solutions and glucose doped PBS solutions in vitro. We observed that temperature and pH variations in the glucose doped PBS solutions cause significant changes in absorbance recorded with a Fourier transform infrared/attenuated total reflectance apparatus in the spectral region which contains information about glucose. Primary blood constituents which may interfere with the IR spectrophotometric measurement of glucose in serum were identified. Blood serum solutions were simulated by mixing glucose and the primary interfering constituents in their physiological concentrations with PBS. The feasibility of accurate prediction of physiological glucose concentration in simulated serum solutions covering physiological variations of blood constituents was assessed by applying univariate techniques, multivariate statistical methods and artificial neural networks (ANN) to their mid-IR spectra. Multivariate methods based on partial least squares, principal component regression and ANN produced calibration models with smaller standard errors of prediction (SEP) of 16.9, 18.8 and 18.8 mg dl -1 , respectively, compared with univariate methods based on peak height and area determinations which yielded a smallest SEP of 40.1 mg dl -1 . We conclude that in spite of physiological variations of major interfering constituents, physiological glucose concentration in aqueous multicomponent mixtures such as blood serum may be predicted with sufficient accuracy for clinical applications using multivariate chemometric techniques. |
