ArticleVirology journal2026
Metagenomic next-generation sequencing of cerebrospinal fluid reveals pathogen spectrum and mortality predictors among patients with advanced HIV-1 disease at a tertiary hospital in China.
Article in Virology journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundCentral nervous system (CNS) infections remain the major causes of morbidity and mortality among people living with HIV-1 (PLWH), particularly in resource-limited settings. However, the clinical characteristics and prognostic indicators of PLWH with suspected CNS infections are not well defined. In this study, we aim to characterize the spectrum of CNS pathogens, clinical characteristics, in-hospital mortality, and factors associated with death among people with advanced HIV-1 disease (AHD) in Guangxi, China.
methodsMetagenomic next-generation sequencing (mNGS) was performed to analyze types of infection in cerebrospinal fluid (CSF) from 61 treatment-naive PLWH with suspected CNS infections. Clinical data, routine laboratory tests, and biochemical tests were collected and analyzed.
resultsAmong the 61 CSF samples, primarily with AHD, a total of 206 pathogens were identified. Viral pathogens predominated, with Epstein-Barr virus being the most frequently identified, followed by cytomegalovirus. Compared with patients with single-pathogen infection, those with multiple infections (viral, bacterial, and fungal) exhibited significantly lower CD4 T cell counts, higher C-reactive protein levels, and markedly reduced lipid metabolism parameters. However, infection types were not significantly associated with in-hospital death. Multivariate logistic regression analysis identified plasma low density lipoprotein (LDL) and CSF lactate dehydrogenase (LDH) as independent predictors of in-hospital death.
conclusionIn PLWH with AHD and suspected CNS infections, multiple pathogens frequently coexist in the CSF. Plasma LDL and CSF LDH levels were independent predictors of death, indicating their potential value as early risk stratification in AHD.
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