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首页> 外文期刊>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?元精度分析

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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之后,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个分离株),AuxaColor(1,740个分离株)和Vitek 2(2,853个分离株)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系统的CI为95%,从0.89至0.96)(异质性为 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子分析表明,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(合并比率为0.76 [95%CI,0.67至0.84])(相对于异种而言, P 为<0.05)。对非Candida酵母(即隐球菌,Rhodotorula,Saccharomyces和Trichosporon)进行的子分析研究显示,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%显着的低或零异质性水平( P

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