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Saccharide interferences such as Dextran, Galactose, etc. have a great potential to interfere with near infrared (NIR) glucose analysis since they have a similar spectroscopic fingerprint and are present physiologically at large relative concentrations. These can lead to grossly inappropriate interpretation of patient glucose levels and resultant treatment in critical care and hospital settings. This study describes a methodology to reduce this effect on glucose analysis using an NIR Fourier transform spectroscopy method combined with a multivariate calibration technique (PLS) using preprocessing by orthogonal signal correction (OSC). A mathematical approach based on the use of a single calibration based bias and slope correction was applied in addition to a standard OSC was investigated. This approach is combined with a factorial interferent calibration design to accommodate for interference effects. We named this approach as a slope and bias OSC (sbOSC). sbOSC differs from OSC in the way it handles the prediction. In sbOSC, statistics on slope and bias obtained from a set of calibration samples are then used as a validation parameter in the prediction set. Healthy human volunteer blood with different glucose (80 to 200 mg/dL) and hematocrit (24 to 48 vol.%) levels containing high expected levels of inteferents have been measured with a transmittance near-infrared Fourier transform spectrometer operates in the broadband spectral range of 1.25-2.5 μm (4000-8000 cm−1). The effect of six interferents compounds used in intensive care and operating rooms, namely Dextran, Fructose, Galactose, Maltose, Mannitol, and Xylose, were tested on blood glucose. A maximum interference effect (MIE) parameter was used to rank the significance for the individual interferent type on measurement error relative to the total NIR whole blood glucose measurement error. For comparison, a YSI (Yellow Springs Instrument) laboratory reference glucose analyzer and NIR data were collected at the same time as paired samples.
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