Direct measurements of blood glucose concentration in the presence of saccharide interferences using slope and bias orthogonal signal correction and Fourier transform near-infrared spectroscopy

摘要

Saccharide interferences such as Dextran, Galactose, etc. have a great potential to interfere with nearninfrared (NIR) glucose analysis since they have a similar spectroscopic fingerprint and are present physiologicallynat large relative concentrations. These can lead to grossly inappropriate interpretation of patient glucose levelsnand resultant treatment in critical care and hospital settings. This study describes a methodology to reduce thisneffect on glucose analysis using an NIR Fourier transform spectroscopy method combined with a multivariatencalibration technique (PLS) using preprocessing by orthogonal signal correction (OSC). A mathematical approachnbased on the use of a single calibration based bias and slope correction was applied in addition to a standardnOSC was investigated. This approach is combined with a factorial interferent calibration design to accommodatenfor interference effects. We named this approach as a slope and bias OSC (sbOSC). sbOSC differs from OSCnin the way it handles the prediction. In sbOSC, statistics on slope and bias obtained from a set of calibrationnsamples are then used as a validation parameter in the prediction set. Healthy human volunteer blood withndifferent glucose (80 to 200 mg/dL) and hematocrit (24 to 48 vol.%) levels containing high expected levels ofninteferents have been measured with a transmittance near-infrared Fourier transform spectrometer operates in thenbroadband spectral range of 1.25–2.5 μm (4000–8000 cm−1). The effect of six interferents compounds used innintensive care and operating rooms, namely Dextran, Fructose, Galactose, Maltose, Mannitol, and Xylose, werentested on blood glucose. A maximum interference effect (MIE) parameter was used to rank the significance fornthe individual interferent type on measurement error relative to the total NIR whole blood glucose measurementnerror. For comparison, a YSI (Yellow Springs Instrument) laboratory reference glucose analyzer and NIR data werencollected at the same time as paired samples.MIE results obtained by sbOSC were compared with several standardnspectral preprocessing approaches and show a substantial reduced effect of saccharide interferences. NIR glucosenmeasurement results are substantially improved when comparing standard error of prediction from validationnsamples; and resulting MIE values are small.