Institute of Chemical Technologies and Analytics, Vienna University of Technology, Getreidemarkt 9/164AC, 1060 Vienna, Austria.
Analyst. 2013 Jul 21;138(14):4022-8. doi: 10.1039/c3an00300k.
We present a semi-automated point-of-care (POC) sensor approach for the simultaneous and reagent-free determination of clinically relevant parameters in blood plasma. The portable sensor system performed direct mid-infrared (MIR) transmission measurements of blood plasma samples using a broadly tunable external-cavity quantum cascade laser source with high spectral power density. This enabled the use of a flow cell with a long path length (165 μm) which resulted in high signal-to-noise ratios and a rugged system, insensitive to clogging. Multivariate calibration models were built using well established Partial-Least-Squares (PLS) regression analysis. Selection of spectral pre-processing procedures was optimized by an automated evaluation algorithm. Several analytes, including glucose, lactate, triglycerides, cholesterol, total protein as well as albumin, were successfully quantified in routinely taken blood plasma samples from 67 critically ill patients. Although relying on a spectral range from 1030 cm(-1) to 1230 cm(-1), which is optimal for glucose and lactate but rather unusual for protein analysis, it was possible to selectively determine the albumin and total protein concentrations with sufficient accuracy for POC application.
我们提出了一种半自动的即时护理(POC)传感器方法,用于在血浆中同时且无需试剂的情况下确定临床相关参数。该便携式传感器系统使用具有高光谱功率密度的宽调谐外腔量子级联激光源对血浆样品进行直接中红外(MIR)透射测量。这使得可以使用具有长光程(165μm)的流通池,从而实现了高信噪比和坚固的系统,不易堵塞。多元校准模型使用成熟的偏最小二乘(PLS)回归分析进行构建。通过自动评估算法优化了光谱预处理程序的选择。在从 67 名危重症患者常规采集的血浆样本中,成功定量了几种分析物,包括葡萄糖、乳酸、甘油三酯、胆固醇、总蛋白以及白蛋白。尽管依赖于葡萄糖和乳酸最佳但蛋白质分析不太常见的 1030cm(-1) 至 1230cm(-1) 光谱范围,但可以以足够的 POC 应用精度选择性地确定白蛋白和总蛋白浓度。