Diagnostic accuracy of nanopore sequencing for the rapid diagnosis of pulmonary tuberculosis: A protocol for a systematic review and meta-analysis

纳米孔测序在肺结核快速诊断中的诊断准确性:系统评价和荟萃分析方案

阅读:1

Abstract

BACKGROUND: Pulmonary tuberculosis (PTB) is the most common type of tuberculosis (TB). Rapid diagnosis of PTB can help in TB control. Although the use of molecular tests (such as the GeneXpert MTB/RIF) has improved the ability to rapidly diagnose PTB, there is still room for improvement. Nanopore sequencing is a novel means of rapid TB detection. The purpose of this study was to establish a systematic review and meta-analysis protocol for evaluating the accuracy of nanopore sequencing for the rapid diagnosis of PTB. METHODS: We completed this protocol according to the Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) statement and registered on the PROSPERO platform. We will screen studies related to nanopore sequencing for diagnosis of PTB by searching through PubMed, EMBASE, the Cochrane Library using English, and Wanfang database, CNKI (China National Knowledge Infrastructure) using Chinese. Eligible studies will be screened according to the inclusion and exclusion criteria established in the study protocol. We will evaluate the methodological quality of the individual included studies using Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). We will use Stata (version 15.0) with the midas command and RevMan (version 5.3) for meta-analysis and forest plots and SROC curves generation. A p < 0.05 was treated as a statistically significant difference. When significant heterogeneity exists between studies, we will explore sources of heterogeneity through meta-regression analysis and subgroup analysis. CONCLUSION: To the best of our knowledge, this will be the first systematic review and meta-analysis of nanopore sequencing for the diagnosis of PTB. We hope that this study will find a new and effective tool for the early diagnosis of PTB. PROSPERO REGISTRATION NUMBER: CRD42023495593.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。