Correction to: A pooled analysis of the LAMP assay for the detection of Neisseria meningitidis.

An amendment to this paper has been published and can be accessed via the original article.

A pooled analysis of the LAMP assay for the detection of Neisseria meningitidis.

BACKGROUND: Neisseria meningitidis is a major cause of bacterial meningitis, and these infections are associated with a high mortality rate. Rapid and reliable diagnosis of bacterial meningitis is critical in clinical practice. However, this disease often occurs in economically depressed areas, so an inexpensive, easy to use, and accurate technology is needed. We performed a pooled-analysis to assess the potential of the recently developed loop-mediated isothermal amplification (LAMP) assay for detection of meningococcus. METHODS: Pubmed, Embase, and Web of Science were searched to identify original studies that used the LAMP assay to detect meningococcus. After pooling of data, the sensitivity and specificity were calculated, a summary receiver operating characteristic (SROC) curve was determined, and the area under the SROC curve was computed to determine diagnostic accuracy. Publication bias was assessed using Deek's funnel plot. RESULTS: We examined 14 studies within 6 publications. The LAMP assay had high sensitivity (94%) and specificity (100%) in the detection of meningococcus in all studies. The area under the SROC curve (0.980) indicated high overall accuracy of the LAMP assay. There was no evidence of publication bias. DISCUSSION: The LAMP assay has accuracy comparable to bacterial culture and PCR for detection of meningococcus, but is less expensive and easier to use. We suggest the adoption of the LAMP assay to detect meningococcus, especially in economically depressed areas.

Diagnostic Accuracy of Xpert Xpress Flu/RSV for the Detection of Influenza and Respiratory Syncytial Viruses.

Xpert Xpress Flu/RSV is a fast and automated real-time nucleic acid amplification tool for detecting influenza virus and respiratory syncytial virus (RSV). The aim of this study was to verify the accuracy of Xpert Xpress Flu/RSV for detecting influenza virus and RSV. PubMed, EMBASE, Cochrane Library, and Web of Science databases were searched up to October 2020. The quality of the original research was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 guidelines. Meta-DiSc 1.4 software was used to analyze the sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and summary receiver operating characteristic curve. Deek's funnel plot asymmetry test was used to evaluate the publication bias using the Stata 12.0 software. Ten studies with 25 fourfold tables were included in the analysis. The sensitivity of Xpert Xpress Flu/RSV for detecting influenza A, influenza B, and RSV were 0.97, 0.98, and 0.96, respectively, and the specificities were 0.97, 1.00, and 1.00, respectively. Compared with other common clinical real-time reverse transcription-polymerase chain reaction (RT-PCR), Xpert Xpress Flu/RSV is a valuable tool for diagnosing influenza virus and RSV with high sensitivity and specificity.

An integrative bioinformatics analysis for identifying hub genes associated with infection of lung samples in patients infected with SARS-CoV-2.

BACKGROUND: At the end of 2019, the world witnessed the emergence and ravages of a viral infection induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Also known as the coronavirus disease 2019 (COVID-19), it has been identified as a public health emergency of international concern (PHEIC) by the World Health Organization (WHO) because of its severity. METHODS: The gene data of 51 samples were extracted from the GSE150316 and GSE147507 data set and then processed by means of the programming language R, through which the differentially expressed genes (DEGs) that meet the standards were screened. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed on the selected DEGs to understand the functions and approaches of DEGs. The online tool STRING was employed to construct a protein-protein interaction (PPI) network of DEGs and, in turn, to identify hub genes. RESULTS: A total of 52 intersection genes were obtained through DEG identification. Through the GO analysis, we realized that the biological processes (BPs) that have the deepest impact on the human body after SARS-CoV-2 infection are various immune responses. By using STRING to construct a PPI network, 10 hub genes were identified, including IFIH1, DDX58, ISG15, EGR1, OASL, SAMD9, SAMD9L, XAF1, IFITM1, and TNFSF10. CONCLUSION: The results of this study will hopefully provide guidance for future studies on the pathophysiological mechanism of SARS-CoV-2 infection.

Evaluation of Xpert Carba-R Assay for the Detection of Carbapenemase Genes in Gram-Negative Bacteria.

INTRODUCTION: High mortality associated with carbapenemase-producing Gram-negative bacteria (CP-GNB) has evolved into a global health threat. Rapid and accurate detection as well as prompt treatment are of great significance in this case. Xpert Carba-R, a multiple qualitative analysis designed to detect five clinically relevant carbapenem-resistant gene families within one hour, is regarded as reliable, accurate, and easy-to-operate. This study is to present a systematic evaluation of the performance of Xpert Carba-R in detecting carbapenemase genes in GNB suspected for carbapenemase production. METHODS: We searched and screened the literature on "Xpert Carba-R" in the database of PubMed, Web of Science, Embase, and Cochrane Library, employing two independent evaluators to collect data, respectively. Then, statistical analysis of the data obtained was performed by the Stata 12.0 software to measure the accuracy of Xpert Carba-R assay in detecting the carbapenemase genes in GNB. RESULTS: We screened a total of 1767 Gram-negative bacillus isolates documented in 9 articles. The precision of the detection of OXA-48 carbapenemase genes was 100%; that of NDM = 100%; that of VIM = 100%. When it came to KPC, the precision rate was 100%; that of IMP = 99%. The overall accuracy of the detection of carbapenemase genes was 100%. CONCLUSIONS: Xpert Carba-R assay demonstrates a 100% precision in identifying carbapenemase genes in GNB. It can be seen that Xpert Carba-R method is an effective tool for early clinical detection, which is suitable for the detection of carbapenase gene in GNB.

The clinical diagnostic value of Xpert MTB/RIF for the detection of Mycobacterium tuberculosis in gastric aspirates.

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.

Pooled analysis of the Xpert MTB/RIF assay for diagnosing tuberculous meningitis.

BACKGROUND: Tuberculous meningitis (TBM) is one of the most serious types of extrapulmonary tuberculosis. However, low sensitivity of culture of cerebrospinal fluid (CSF) increases the difficulty in clinical diagnosis, leading to diagnostic delay, and misdiagnosis. Xpert MTB/RIF assay is a rapid and simple method to detect tuberculosis. However, the efficacy of this technique in diagnosing TBM remains unclear. Therefore, a meta-analysis was conducted to evaluate the diagnostic efficacy of Xpert MTB/RIF for TBM, which may enhance the development of early diagnosis of TBM. METHODS: Relevant studies in the PubMed, Embase, and Web of Science databases were retrieved using the keywords 'Xpert MTB/RIF', 'tuberculous meningitis (TBM)'. The pooled sensitivity, pooled specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, summary receiver operator characteristic curve, and area under the curve (AUC) of Xpert MTB/RIF were determined and analyzed. RESULTS: A total of 162 studies were enrolled and only 14 met the criteria for meta-analysis. The overall pooled sensitivity of Xpert MTB/RIF was 63% [95% confidence interval (CI), 59-66%], while the overall pooled specificity was 98.1% (95% CI, 97.5-98.5%). The pooled values of positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 20.91% (12.71-52.82%), 0.40% (0.32-0.50%), and 71.49% (32.64-156.56%), respectively. The AUC was 0.76. CONCLUSIONS: Xpert MTB/RIF exhibited high specificity in diagnosing TBM in CSF samples, but its sensitivity was relatively low. It is necessary to combine other high-sensitive detection methods for the early diagnosis of TBM. Moreover, the centrifugation of CSF samples was found to be beneficial in improving the sensitivity.

Evaluation of the Diagnostic Efficacy of Xpert CT/NG for Chlamydia trachomatis and Neisseria gonorrhoeae.

BACKGROUND: Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) are widely spread across the world. Asymptomatic or inconspicuous CT/NG infections are difficult to diagnose and treat. Traditional methods have the disadvantages of low detection rate, inaccurate results, and long detection time. However, Xpert CT/NG makes up for the aforementioned shortcomings and has research value and popularization significance. METHODS: PubMed, Embase, Cochrane Library, and Web of Science were systematically searched, and studies were screened using Xpert CT/NG for diagnosing CT/NG. QUADAS-2 was used to evaluate the quality of the eligible studies. Then, two groups of researchers independently extracted data from these studies. Meta-analyses of sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the area under the curve (AUC) of the summary receiver operating characteristic (SROC) curve were conducted using Meta-DiSc 1.4. Finally, Deek's funnel plots were made using Stata 12.0 to evaluate publication bias. RESULTS: 14 studies were identified, and 46 fourfold tables were extracted in this meta-analysis. The pooled SEN, SPE, PLR, NLR, DOR, and AUC in diagnosing CT were 0.94 (95% confidence interval (CI): 0.93-0.95), 0.99 (95% CI: 0.99-1.00), 97.17 (95% CI: 56.76-166.32), 0.07 (95% CI: 0.04-0.12), 1857.25 (95% CI: 943.78-3654.86), and 0.9960, respectively. The pooled SEN, SPE, PLR, NLR, DOR, and AUC in diagnosing NG were 0.95 (95% CI: 0.93-0.96), 1.00 (95% CI: 1.00-1.00), 278.15 (95% CI: 152.41-507.63), 0.08 (95% CI: 0.06-0.12), 4290.70 (95% CI: 2161.78-8516.16), and 0.9980, respectively. CONCLUSIONS: Xpert CT/NG had high diagnostic sensitivity and specificity for CT and NG. However, more evidence is required to confirm that Xpert CT/NG might serve as the primary method for detecting CT and NG and even the gold standard for diagnosis in the future.

Accuracy of matrix-assisted LASER desorption ionization-time of flight mass spectrometry for identification of Candida.

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.