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MEKC-LIF for Sensitive Discrimination of Six Potential Risk Predictors for Auxiliary Diagnosis of Anesthesia Complications in Clinical Urine Fluids

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An Erratum to this article was published on 21 January 2017

Abstract

Biochemical analysis of the abnormalities of urinary metabolites is a powerful auxiliary method for diagnosis of anesthesia complications (AC). It is a cost-effective, time-saving, and complementary diagnosis method that can quickly generate clinical examination results. The current study describes a rapid and sensitive assay for simultaneous determination of six naturally occurring marker metabolites, namely dopamine (DPM), epinephrine (EPR), kynurenine (KNR), anthranilic acid (ATRA), hydroxylproline (OHP), and asymmetric dimethylarginine (ADMA), in urine fluids of diverse AC patients. This novel assay was based on micellar electrokinetic capillary chromatography (MEKC) coupled with highly sensitive laser-induced fluorescence (LIF) detection and high-throughput built-in 96-well microplate (96-μ) precolumn derivatization. 5-Carboxyfluorescein succinimidyl ester (CFSE) was chosen as the fluorescence labeling reagent. After full optimization of the derivatization and separation conditions, the quantization of six target analyses was achieved with good linearity (R 2 > 0.998) with a linear range of 0.01–5 μM. The limits of detection (LODs, at S/N > 3) and limits of quantitation (LOQs, at S/N > 10) were determined to be 0.14–1.25 and 0.58–3.61 nM, respectively. The precision data of migration time and peak area, evaluated as relative standard derivations (RSDs), were less than 2.8 and 3.2 % for intraday assay (n = 6), and less than 4.2 and 4.5 % for interday assay (n = 6), respectively, indicating that the proposed method was highly reproducible. Satisfactory recoveries obtained were in the range of 97–106 %, in addition to the good stability of the CFSE derivative products. The feasibility of the proposed method was fully validated by applying quantitative analysis of the target analytes in substantial urine fluids from diverse AC patients.

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Acknowledgments

The authors thank the financial support from the Natural Science Foundation of Shanghai (No. 13ZR1408400).

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    Authors and Affiliations

    1. Department of Anesthesia, The Second Affiliated Hospital of Soochow University, Soochow, 215004, China

      Fuwei Qi, Zhong Zheng, Yanhong Shang & Xiuhua Zhao

    2. Taicang Affiliated Hospital of Soochow University, Taicang, 215400, China

      Hong Xie

    3. Department of Anesthesiology, Changhai Hospital, The Second Military Medical University, Shanghai, 200433, China

      Xiaohua Fan

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    1. Fuwei Qi
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    2. Hong Xie
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    3. Zhong Zheng
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    4. Yanhong Shang
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    Corresponding authors

    Correspondence to Xiaohua Fan or Xiuhua Zhao.

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    The authors have declared no conflict of interest.

    Informed consent

    Informed consent was obtained from all patients included in this study. All procedures followed in this study were in accordance with ethical standards of the responsible committee on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008 (5).

    Additional information

    F. Qi and H. Xie contributed equally to this study.

    An erratum to this article is available at http://dx.doi.org/10.1007/s10337-017-3239-9.

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    Qi, F., Xie, H., Zheng, Z. et al. MEKC-LIF for Sensitive Discrimination of Six Potential Risk Predictors for Auxiliary Diagnosis of Anesthesia Complications in Clinical Urine Fluids. Chromatographia 79, 1665–1670 (2016). https://doi.org/10.1007/s10337-016-3175-0

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    • DOI: https://doi.org/10.1007/s10337-016-3175-0

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