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Background: Numerous studies on in-house real-time PCR (hRT-PCR) assay for the detection of Mycobacterium tuberculosis (Mtb) have been reported. To assess the overall accuracy of the test in diagnosing pulmonary and extra-pulmonary Mtb infection, a systematic review and meta-analysis was performed.
Methods: Various databases like PUBMED, EMBASE, Web of Science, and Cochrane were searched for studies that estimated diagnostic sensitivity and specificity with the hRT-PCR assay in samples from pulmonary and extra-pulmonary Mtb infected patients, with Mtb culture as the reference standard. Bivariate random effect models were used to provide pooled estimation of diagnostic accuracy. Further, subgroup and meta-regression analyses were performed to explore sources of heterogeneity. The risk of bias was assessed by the QUADAS-2 tool.
Results: Out of the 3589 studies, 18 studies met the inclusion criteria., The pooled sensitivity and specificity of hRT-PCR assay were 0.96 and 0.92, respectively when compared to Mtb culture data. The diagnostic odds ratio (DOR) was 192.96 (95% CI 68.46, 543.90), and the area under the summary ROC curve (AUC) was 0.9791. There was significant heterogeneity in sensitivity and specificity among the enrolled studies (p < 0.001). The studies with high-quality assessment and involving respiratory specimen were associated with better accuracy.
Conclusions: The results suggest the usefulness of hRT-PCR assay for the diagnosis of TB with high sensitivity and specificity in low-income/high-burden settings
"Real-time PCR assay for Mycobacterium tuberculosis: a systematic review and meta-analysis", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 12, page no.20 - 29, December-2022, Available :http://www.ijrti.org/papers/IJRTI2212005.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator