P. Bhandare et al., GLUCOSE DETERMINATION IN SIMULATED BLOOD-SERUM SOLUTIONS BY FOURIER-TRANSFORM INFRARED-SPECTROSCOPY - INVESTIGATION OF SPECTRAL INTERFERENCES, Vibrational spectroscopy, 6(3), 1994, pp. 363-378
Determination of physiological concentrations of glucose in whole bloo
d or blood serum using infrared (IR) spectrometry is complicated due t
o combined effects of spectral variations caused by fluctuations in te
mperature, pH and other blood constituents with overlapping spectra. I
n order to initiate systematic examination of these effects, we studie
d the effects of temperature and pH changes on the spectral variation
of phosphate buffered saline (PBS) solutions and glucose doped PBS sol
utions in vitro. We observed that temperature and pH variations in the
glucose doped PBS solutions cause significant changes in absorbance r
ecorded with a Fourier transform infrared/attenuated total reflectance
apparatus in the spectral region which contains information about glu
cose. Primary blood constituents which may interfere with the IR spect
rophotometric measurement of glucose in serum were identified. Blood s
erum solutions were simulated by mixing glucose and the primary interf
ering constituents in their physiological concentrations with PBS. The
feasibility of accurate prediction of physiological glucose concentra
tion in simulated serum solutions covering physiological variations of
blood constituents was assessed by applying univariate techniques, mu
ltivariate statistical methods and artificial neural networks (ANN) to
their mid-IR spectra. Multivariate methods based on partial least squ
ares, principal component regression and ANN produced calibration mode
ls 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 yield a smallest SEP of 40.1
mg dl-1. We conclude that in spite of physiological variations of maj
or interfering constituents, physiological glucose concentration in aq
ueous multicomponent mixtures such as blood serum may be predicted wit
h sufficient accuracy for clinical applications using multivariate che
mometric techniques.