Efficacy of LAMP assay for Mycobacterial spp. detection to prevent treatment delays and onset of drug resistance: a systematic review and meta-analysis

医学 背景(考古学) 环介导等温扩增 肺结核 结核分枝杆菌 罗氏诊断公司 抗药性 人口 诊断准确性 重症监护医学 分子诊断学 病理 生物信息学 内科学 环境卫生 生物 微生物学 DNA 古生物学 遗传学
作者
Gurvinder Singh Bumbrah,Sarika Jain,Zeeshan Fatima,Saif Hameed
出处
期刊:Drug Target Insights [SAGE Publishing]
卷期号:17: 78-89 被引量:2
标识
DOI:10.33393/dti.2023.2596
摘要

Background: Tuberculosis (TB) remains a deadly disease affecting one-third population globally. Long turnaround time and poor sensitivity of the conventional diagnostics are the major impediments for faster diagnosis of Mycobacterial spp to prevent drug resistance. To overcome these issues, molecular diagnostics have been developed. They offer enhanced sensitivity but require sophisticated infrastructure, skilled manpower and remain expensive. Methods: In that context, loop-mediated isothermal amplification (LAMP) assay, recommended by the WHO in 2016 for TB diagnosis, sounds as a promising alternative that facilitates visual read outs. Therefore, the aim of the present study is to conduct a meta-analysis to assess the diagnostic efficiency of LAMP for the detection of a panel of Mycobacterium spp. following PRISMA guidelines using scientific databases. From 1600 studies reported on the diagnosis of Mycobacterium spp., a selection of 30 articles were identified as eligible to meet the criteria of LAMP based diagnosis. Results: It was found that most of the studies were conducted in high disease burden nations such as India, Thailand, and Japan with sputum as the most common specimen to be used for LAMP assay. Furthermore, IS6110 gene and fluorescence-based detections ranked as the most used target and method respectively. The accuracy and precision rates mostly varied between 79.2% to 99.3% and 73.9% to 100%, respectively. Lastly, a quality assessment based on QUADAS-2 of bias and applicability was conducted. Conclusion: LAMP technology could be considered as a feasible alternative to current diagnostics considering high burden for rapid testing in low resource regions.

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