Department of Laboratory Medicine, National Key Clinical Department of Laboratory Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, People's Republic of China.
Department of Laboratory Medicine, Wuxi Children's Hospital, The Affiliated Wuxi Children's Hospital of Nanjing Medical University, Wuxi, 214000, People's Republic of China.
Eur J Clin Microbiol Infect Dis. 2021 Feb;40(2):345-351. doi: 10.1007/s10096-020-04027-y. Epub 2020 Sep 18.
The optimized diagnosis algorithm of Clostridioides difficile infection (CDI) is worldwide concerns. The purpose of this study was to assess the toxigenic C. difficile test performance and propose an optimal laboratory workflow for the diagnosis of CDI in mild virulent epidemic areas. Diarrhea samples collected from patients were analyzed by glutamate dehydrogenase (GDH), toxin AB (CDAB), and nucleic acid amplification test (NAAT). We assessed the performance of GDH, the GDH-CDAB algorithm, and the GDH-NAAT algorithm using toxigenic culture (TC) as a reference method. In this study, 186 diarrhea samples were collected. The numbers of TC-positive and TC-negative samples were 39 and 147, respectively. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and kappa of the GDH assay were 100%, 80.3%, 57.4%, 100%, and 0.63; of the GDH-CDAB algorithm were 48.7%, 97.3%, 82.6%, 87.7%, and 0.54; and of the GDH-NAAT algorithm were 74.4%, 100%, 100%, 93.6%, and 0.82, respectively. The GDH-NAAT algorithm has great concordance with TC in detecting toxigenic C. difficile (kappa = 0.82), while the sensitivity of the GDH-CDAB algorithm was too low to meet the demand of CDI diagnosis clinically. GDH-NAAT algorithm is recommended for the detection of toxigenic C. difficile with high specificity, increased sensitivity, and cost-effective.
艰难梭菌感染（CDI）的优化诊断算法是全球关注的焦点。本研究旨在评估产毒艰难梭菌检测的性能，并提出在轻度毒力流行地区诊断 CDI 的最佳实验室工作流程。收集患者的腹泻样本，通过谷氨酸脱氢酶（GDH）、毒素 AB（CDAB）和核酸扩增试验（NAAT）进行分析。我们使用产毒培养（TC）作为参考方法，评估 GDH、GDH-CDAB 算法和 GDH-NAAT 算法的性能。本研究共收集了 186 份腹泻样本。TC 阳性和 TC 阴性样本的数量分别为 39 和 147。GDH 检测的敏感性、特异性、阳性预测值（PPV）、阴性预测值（NPV）和kappa 值分别为 100%、80.3%、57.4%、100%和 0.63；GDH-CDAB 算法分别为 48.7%、97.3%、82.6%、87.7%和 0.54；GDH-NAAT 算法分别为 74.4%、100%、100%、93.6%和 0.82。GDH-NAAT 算法与 TC 在检测产毒艰难梭菌方面具有很好的一致性（kappa 值=0.82），而 GDH-CDAB 算法的敏感性太低，无法满足临床 CDI 诊断的需求。推荐使用 GDH-NAAT 算法检测产毒艰难梭菌，具有高特异性、高敏感性和成本效益。
