首页> 美国卫生研究院文献>Journal of Clinical Microbiology >Are the Conventional Commercial Yeast Identification Methods Still Helpful in the Era of New Clinical Microbiology Diagnostics? A Meta-Analysis of Their Accuracy
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Are the Conventional Commercial Yeast Identification Methods Still Helpful in the Era of New Clinical Microbiology Diagnostics? A Meta-Analysis of Their Accuracy

机译:在新的临床微生物学诊断学时代常规的商业酵母鉴定方法仍然有用吗?他们的准确性的荟萃分析

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摘要

Accurate identification of pathogenic species is important for early appropriate patient management, but growing diversity of infectious species/strains makes the identification of clinical yeasts increasingly difficult. Among conventional methods that are commercially available, the API ID32C, AuxaColor, and Vitek 2 systems are currently the most used systems in routine clinical microbiology. We performed a systematic review and meta-analysis to estimate and to compare the accuracy of the three systems, in order to assess whether they are still of value for the species-level identification of medically relevant yeasts. After adopting rigorous selection criteria, we included 26 published studies involving Candida and non-Candida yeasts that were tested with the API ID32C (674 isolates), AuxaColor (1,740 isolates), and Vitek 2 (2,853 isolates) systems. The random-effects pooled identification ratios at the species level were 0.89 (95% confidence interval [CI], 0.80 to 0.95) for the API ID32C system, 0.89 (95% CI, 0.83 to 0.93) for the AuxaColor system, and 0.93 (95% CI, 0.89 to 0.96) for the Vitek 2 system (P for heterogeneity, 0.255). Overall, the accuracy of studies using phenotypic analysis-based comparison methods was comparable to that of studies using molecular analysis-based comparison methods. Subanalysis of studies conducted on Candida yeasts showed that the Vitek 2 system was significantly more accurate (pooled ratio, 0.94 [95% CI, 0.85 to 0.99]) than the API ID32C system (pooled ratio, 0.84 [95% CI, 0.61 to 0.99]) and the AuxaColor system (pooled ratio, 0.76 [95% CI, 0.67 to 0.84]) with respect to uncommon species (P for heterogeneity, <0.05). Subanalysis of studies conducted on non-Candida yeasts (i.e., Cryptococcus, Rhodotorula, Saccharomyces, and Trichosporon) revealed pooled identification accuracies of ≥98% for the Vitek 2, API ID32C (excluding Cryptococcus), and AuxaColor (only Rhodotorula) systems, with significant low or null levels of heterogeneity (P > 0.05). Nonetheless, clinical microbiologists should reconsider the usefulness of these systems, particularly in light of new diagnostic tools such as matrix-assisted laser desorption ionization–time of flight (MALDI-TOF) mass spectrometry, which allow for considerably shortened turnaround times and/or avoid the requirement for additional tests for species identity confirmation.
机译:准确识别病原体对于及早进行适当的患者管理很重要,但是传染性物种/菌株的多样性不断增长,使得临床酵母的识别越来越困难。在可商购的常规方法中,API ID32C,AuxaColor和Vitek 2系统目前是常规临床微生物学中使用最多的系统。我们进行了系统的综述和荟萃分析,以评估和比较这三个系统的准确性,以便评估它们是否仍对医学相关酵母菌的种级鉴定具有价值。在采用严格的选择标准后,我们​​纳入了26项涉及念珠菌和非念珠菌的已发表研究,这些研究分别通过API ID32C(674株),AuxaColor(1,740株)和Vitek 2(2,853株)系统进行了测试。对于API ID32C系统,物种级别的随机效应汇总识别率分别为0.89(95%置信区间[CI],0.80至0.95),AuxaColor系统为0.89(95%CI,0.83至0.93)和0.93( Vitek 2系统为95%CI(0.89至0.96)(异质性P为0.255)。总体而言,使用基于表型分析的比较方法进行研究的准确性与使用基于分子分析的比较方法进行研究的准确性相当。对念珠菌进行的研究的亚分析显示,Vitek 2系统比API ID32C系统(池比率0.84 [95%CI,0.61至0.99]准确得多(池比率0.94 [95%CI,0.85至0.99])。 ])和AuxaColor系统(池比率0.76 [95%CI,0.67至0.84])(相对于异种而言)(异质性P,<0.05)。对非Candida酵母(即隐球菌,Rhodotorula,Saccharomyces和Trichosporon)进行的研究亚分析显示,Vitek 2,API ID32C(不包括隐球菌)和AuxaColor(仅Rhodotorula)系统的合并识别准确度≥98%异质性水平显着低或为零(P> 0.05)。尽管如此,临床微生物学家仍应重新考虑这些系统的实用性,尤其是考虑到诸如矩阵辅助激光解吸电离-飞行时间(MALDI-TOF)质谱之类的新诊断工具,这可以大大缩短周转时间和/或避免对物种身份确认进行额外测试的要求。

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