Hierarchical decision model for in vitro bilirubin content prediction from absorption spectrum of whole blood

基于全血吸收光谱的体外胆红素含量预测分层决策模型

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Abstract

SIGNIFICANCE: Bilirubin forms by the breakdown of heme proteins in the liver, but a newborn's sluggish liver can lead to elevated serum bilirubin levels that cross the blood-brain barrier and result in kernicterus. Earlier studies have used the 400 to 500 nm optical wavelength range to characterize the bilirubin content. There is not a universally established correlation among other wavelengths and the amount of bilirubin in clinical whole blood samples. AIM: We demonstrated that the amount of bilirubin could be quantified with  ∼ 82% accuracy in a label-free, self-referenced manner using only a few wavelengths, viz. 468, 492, 500, 560, 605, 645, 660, and 675 nm, wherein band-averaged absorption measurements are used. APPROACH: We addressed the above problem by conducting a preliminary study containing 50 neonates through an absorption spectrum measurement of whole blood in 3 to 5  μl samples from the neonates. We constructed a hierarchical decision method that first grossly divides the 30 neonates of the training set into  < 10  mg/dl and  ≥ 10  mg/dl bilirubin level cohorts. A subsequent boundary condition further divides the  ≥ 10  mg/dl group into two  > 15  mg/dl and  ≤ 15  mg/dl bilirubin level cohorts. A finer measure later predicted the bilirubin content of each of these groups as low ( < 10  mg/dl), medium (10 to 15  mg/dl), and high ( > 15  mg/dl). RESULTS: Using this hierarchical decision model statistical approach, we quantified the amount of bilirubin in the 20 testing set samples with 82% accuracy. CONCLUSIONS: We formulated a biostatistical model in which we automated the spectrometric determination of total bilirubin in the whole blood for patients of neonatal hyperbilirubinemia.

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