College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110819, China.
Haigang hospital, Qinhuangdao, Hebei Province 066000, China.
Spectrochim Acta A Mol Biomol Spectrosc. 2017 May 5;178:192-197. doi: 10.1016/j.saa.2017.02.002. Epub 2017 Feb 3.
Reagent-free determination of multiple analytes is an active and promising field of research in clinical analysis. In this work, the determination of glucose and cholesterol in whole blood using Fourier transform infrared (FTIR) spectroscopy equipped with an attenuated total reflectance (ATR) accessory was performed. A comprehensive sample selection rule in multi space based on SPXY was proposed, termed C-SPXY. The core idea is to make full use of different derivative spectra space to construct the calibration set which preserves the more effective information. On this basis, a partial least squares (PLS) regression fusion modeling method was also presented aiming at improving prediction accuracy of glucose and cholesterol concentration in whole blood samples. Compared with other methods based on single spectra space, the proposed fusion model based on multi spectra space C-SPXY method provides smaller RMSEP values. Experimental results demonstrate that the proposed method and model provides superior predictive power and holds a good application prospect in the field of clinical analysis.
无试剂分析是临床分析中一个活跃而有前途的研究领域。在这项工作中,使用配备衰减全反射(ATR)附件的傅里叶变换红外(FTIR)光谱法对全血中的葡萄糖和胆固醇进行了测定。提出了一种基于 SPXY 的多空间综合样本选择规则,称为 C-SPXY。其核心思想是充分利用不同的导数光谱空间来构建保留更有效信息的校准集。在此基础上,还提出了一种偏最小二乘(PLS)回归融合建模方法,旨在提高全血样本中葡萄糖和胆固醇浓度的预测精度。与基于单一光谱空间的其他方法相比,基于多光谱空间 C-SPXY 方法的提出的融合模型提供了更小的 RMSEP 值。实验结果表明,该方法和模型具有优越的预测能力,在临床分析领域具有良好的应用前景。