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Background: At present, the infection and prevalence rates of tuberculosis (TB) are still high in worldwide. The Xpert MTB/RIF technology has improved the diagnosis speed of Mycobacterium tuberculosis (MTB) and facilitated the rapid treatment of TB patients., Methods: We searched experimental data derived from Xpert MTB/RIF for detecting MTB in gastric aspirates in PubMed, Embase, Web Of Science, and the Cochrane Library databases between January 2012 to April 2019. A summary receiver operating characteristic curve (SROC curve) was used to analyze the pooled sensitivity, pooled specificity, PLR, NLR, and DOR for determining the accuracy of the test., Results: Our database search resulted in 10 relevant articles. The pooled sensitivity of Xpert MTB/RIF for detecting TB in GA was 86% (95% CI, 83-89%), and I2 = 93.4%. The pooled specificity was 92% (95% CI, 90-93%) and I2 = 97.8%. In addition, the positive LR was 12.12 (95% CI, 5.60-26.21), negative LR was 0.20 (95% CI, 0.11-0.36), and the diagnostic odds ratio (DOR) was 147.04 (95% CI, 37.20-581.19). Using the SROC curve, the AUC was 0.9730 and Q* was 0.9248 (SE = 0.0261). The publication bias was P=0.517 (P>0.05)., Conclusions: The Xpert MTB/RIF for detecting MTB in gastric aspirates was highly accurate. In addition, we observed that the publication bias in the present study was low. Hence, the Xpert MTB/RIF technology is highly accurate and has the advantage of rapid testing for MTB in clinical samples., (© 2020 The Author(s).)

Background: Candida is a fungus that causes various types of candidemia, which is the fourth major infectious disease of the blood system. MALDI-TOF-MS is a simple and rapid detection instrument. The aim of the present study was to verify the accuracy of MALDI-TOF-MS in detecting Candida., Method: A pooled analysis of articles on MALDI-TOF-MS for diagnosis of candidemia was performed. The quality of original research was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) guidelines. Stata 12.0 software was used to merge the correct identification rates of Candida and Candida subspecies and obtain pooled sensitivity and specificity of the diagnostic methods. Heterogeneity was found in the subgroup analysis of the included articles. Hence, we explored the factors causing the heterogeneity and its impact on the overall situation. Sensitivity analysis was used to examine the effect of Candida level on total response. Egger's test was used to evaluate the publication bias of the included articles., Results: A total of 16 articles in Pubmed, 79 articles in Embase, 1 article in Cochrane Library, 30 articles in Web of Science and 3 from other sources were identified, of which 10 articles were included based on the inclusion and exclusion criteria. The overall identification accuracy was 100%., Conclusion: The accuracy of MALDI-TOF-MS for the identification of Candida was 100%. Further research is necessary to determine whether MALDI-TOF-MS can be used as a clinical diagnostic standard for the identification of Candida., (© 2019 The Author(s).)

Streptococcus agalactiae is a major pathogenic bacterium causing perinatal infections in humans. In the present study, a novel real-time fluorescence loop-mediated isothermal amplification technology was successfully developed and evaluated for the detection of S. agalactiae in a single reaction. Six specific primers were designed to amplify the corresponding six regions of fbs B gene of S. agalactiae , using Bst DNA polymerase with DNA strand displacement activity at a constant temperature for 60 min. The presence of S. agalactiae was indicated by the fluorescence in real-time. Amplification of the targeted gene fragment was optimized with the primer 1 in the current setup. Positive result was only obtained for Sa by Real-LAMP among 10 tested relevant bacterial strains, with the detection sensitivity of 300 pg/µl. Real-LAMP was demonstrated to be a simple and rapid detection tool for S. agalactiae with high specificity and stability, which ensures its wide application and broad prospective utilization in clinical practice for the rapid detection of S. agalactiae ., (© 2019 The Author(s).)