Department of Medical Microbiology, University of Manitoba, Winnipeg, Manitoba ; Diagnostic Services of Manitoba, Winnipeg, Manitoba.
Department of Medical Microbiology, University of Manitoba, Winnipeg, Manitoba.
Can J Infect Dis Med Microbiol. 2013 Summer;24(2):89-92. doi: 10.1155/2013/934945.
There has been a growing interest in developing an appropriate laboratory diagnostic algorithm for Clostridium difficile, mainly as a result of increases in both the number and severity of cases of C difficile infection in the past decade. A C difficile diagnostic algorithm is necessary because diagnostic kits, mostly for the detection of toxins A and B or glutamate dehydrogenase (GDH) antigen, are not sufficient as stand-alone assays for optimal diagnosis of C difficile infection. In addition, conventional reference methods for C difficile detection (eg, toxigenic culture and cytotoxin neutralization [CTN] assays) are not routinely practiced in diagnostic laboratory settings.
To review the four-step algorithm used at Diagnostic Services of Manitoba sites for the laboratory diagnosis of toxigenic C difficile.
One year of retrospective C difficile data using the proposed algorithm was reported. Of 5695 stool samples tested, 9.1% (n=517) had toxigenic C difficile. Sixty per cent (310 of 517) of toxigenic C difficile stools were detected following the first two steps of the algorithm. CTN confirmation of GDH-positive, toxin A- and B-negative assays resulted in detection of an additional 37.7% (198 of 517) of toxigenic C difficile. Culture of the third specimen, from patients who had two previous negative specimens, detected an additional 2.32% (12 of 517) of toxigenic C difficile samples.
Using GDH antigen as the screening and toxin A and B as confirmatory test for C difficile, 85% of specimens were reported negative or positive within 4 h. Without CTN confirmation for GDH antigen and toxin A and B discordant results, 37% (195 of 517) of toxigenic C difficile stools would have been missed. Following the algorithm, culture was needed for only 2.72% of all specimens submitted for C difficile testing.
The overview of the data illustrated the significance of each stage of this four-step C difficile algorithm and emphasized the value of using CTN assay and culture as parts of an algorithm that ensures accurate diagnosis of toxigenic C difficile.
由于过去十年中艰难梭菌感染的病例数量和严重程度都有所增加,因此人们越来越有兴趣开发一种合适的实验室诊断艰难梭菌的算法。艰难梭菌诊断算法是必要的,因为诊断试剂盒主要用于检测毒素 A 和 B 或谷氨酸脱氢酶(GDH)抗原,作为单独的检测方法不足以对艰难梭菌感染进行最佳诊断。此外,艰难梭菌检测的常规参考方法(例如,产毒培养和细胞毒素中和[CTN]检测)在诊断实验室环境中并未常规应用。
回顾曼尼托巴诊断服务站点用于产毒艰难梭菌实验室诊断的四步算法。
报告了使用所提出的算法进行的为期一年的回顾性艰难梭菌数据。在检测的 5695 份粪便样本中,有 9.1%(n=517)为产毒艰难梭菌。在算法的前两步检测到 60%(310/517)的产毒艰难梭菌粪便。GDH 阳性、毒素 A 和 B 阴性检测的 CTN 确认结果使另外 37.7%(198/517)的产毒艰难梭菌得到检测。从之前有两个阴性样本的患者中培养第三个样本,又检测到另外 2.32%(12/517)的产毒艰难梭菌样本。
使用 GDH 抗原作为艰难梭菌的筛选,毒素 A 和 B 作为确认试验,85%的样本在 4 小时内报告为阴性或阳性。如果没有 CTN 确认 GDH 抗原和毒素 A 和 B 不一致的结果,将有 37%(195/517)的产毒艰难梭菌粪便漏检。按照该算法,仅需对提交进行艰难梭菌检测的所有样本中的 2.72%进行培养。
该数据概述说明了该四步艰难梭菌算法各个阶段的重要性,并强调了在确保准确诊断产毒艰难梭菌时使用 CTN 检测和培养作为算法的一部分的重要性。