Diagnostic accuracy of the metagenomic next-generation sequencing (mNGS) for detection of bacterial meningoencephalitis: a systematic review and meta-analysis.

Abstract

The early diagnosis of bacterial meningoencephalitis (BM/E) is difficult, and delay in diagnosis can cause complications leading to neurological impairment/death. In cases of unexplained BM/E, the metagenomic NGS (mNGS) offers an advantage over conventional methods, especially when a rare pathogen is implicated or the patient is on antibiotics. This study aims to evaluate and compare the diagnostic efficacy of mNGS for the diagnosis of BM/E using cerebrospinal fluid (CSF) specimens versus a composite reference standard (CRS). The electronic databases (Embase, PubMed, and Web of Science) were searched up to 15 June 2021. Studies such as cohort, case-control, prospective, or retrospective studies that assessed the diagnostic efficacy of mNGS in suspected bacterial meningitis/encephalitis cases were included. Ten studies met the inclusion criteria, including three retrospective and seven prospective studies. The sensitivity of mNGS for diagnosis of BM/E from CSF samples ranged from 33 (95% CI: 13-62) to 98% (95% CI: 76-99). The specificity of mNGS ranged from 67 (95% CI: 55-78) to 98% (95% CI: 95-99). The estimated AUC (area under curve) by hierarchical summary receiver operating characteristic (HSROC) of the studies being analyzed was 0.912. The meta-regression analysis demonstrated that the different types of studies (single-center vs. multi-center) had an effect on the specificity of mNGS for BM/E compared with CRS (90% vs. 96%, meta-regression P < 0.05). The current analysis revealed moderate diagnostic accuracy of mNGS. This approach can be helpful, especially in cases of undiagnosed BM/E by identification of organism and subsequently accelerating the patient management.