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Determination of glycated hemoglobin using near-infrared spectroscopy combined with equidistant combination partial least squares
被引:32
|作者:
Han, Yun
[1
]
Chen, Jiemei
[2
]
Pan, Tao
[1
]
Liu, Guisong
[3
]
机构:
[1] Jinan Univ, Dept Optoelect Engn, Guangzhou 510632, Guangdong, Peoples R China
[2] Jinan Univ, Dept Biol Engn, Guangzhou 510632, Guangdong, Peoples R China
[3] Jinan Univ, Dept Math, Guangzhou 510632, Guangdong, Peoples R China
基金:
中国国家自然科学基金;
关键词:
Glycated hemoglobin;
Near-infrared spectroscopic analysis;
Equidistant combination PLS;
Competitive adaptive reweighted sampling combined with PLS;
Monte Carlo uninformative variable elimination by PLS;
WAVEBAND SELECTION STABILITY;
MULTIVARIATE CALIBRATION;
OPTIMIZATION;
PREDICTION;
NITROGEN;
GLUCOSE;
MODELS;
SERUM;
SOIL;
D O I:
10.1016/j.chemolab.2015.04.015
中图分类号:
TP [自动化技术、计算机技术];
学科分类号:
0812 ;
摘要:
A novel near-infrared-spectroscopy-based quantification method for glycated hemoglobin (HbA1c), a major clinical diagnosis indicator of diabetes, was developed on the basis of simultaneous determination of hemoglobin (Hb) and absolute HbA1c content (Hb center dot HbA1c) in human hemolysate samples. Equidistant combination partial least squares (EC-PLS) method was proposed to perform wavelengths selection. Competitive adaptive reweighted sampling PIS (CARS-PLS) and Monte Carlo uninformative variable elimination PLS (MC-UVE-PLS) methods were also conducted for comparison. A randomness and stability dependent rigorous process of calibration, prediction, and validation was performed to produce objective and stable models. The search range covered the unsaturated region (780-1880 nm, 2090-2330 nm). For Hb and Hb center dot HbA1c, only 6 and 14 wavelengths were selected with EC-PLS, 23 and 30 wavelengths were selected with CARS-PLS, and 100 and 120 wavelengths were selected with MC-UVE-PLS, respectively. The predicted values of relative percentage HbA1c were calculated from the predicted Hb and Hb center dot HbA1c values. The sensitivity and specificity for diabetes were 93.5% and 97.1% with EC-PLS, 913% and 94.1% with CARS-PLS, and 89.1% and 76.5% with MC-UVE-PLS, respectively. In three methods, EC-PLS not only employed the least wavelengths but also produced the best quantification accuracy for HbA1c. EC-PIS also achieved the highest classification accuracy for negative and positive samples for diabetes. The results confirm the feasibility of HbA1c quantification based on the simultaneous analysis of Hb and Hb center dot HbA1c with NIR spectroscopy. This technique is rapid and simple when compared with conventional methods, and is a promising tool for screening diabetes in large populations. (C) 2015 Elsevier B.V. All rights reserved.
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页码:84 / 92
页数:9
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