Clinical value of macrogenome next-generation sequencing on infections

Intracranial infection (ICI) is a frequent and serious complication after neurosurgery. Macrogenome next-generation sequencing (mNGS) technology can provide reference for clinical diagnosis and treatment of ICI. This work aimed to explore the application value of mNGS technology in analyzing the clinical characteristics of human immunodeficiency virus (HIV) infection and ICI after neurosurgery. A total of 60 patients with ICI were enrolled as the research objects, all patients underwent routine cerebrospinal fluid analysis and traditional pathogen detection, followed by mNGS genome analysis. Using clinical diagnosis of ICI as the gold standard, the sensitivity, specificity, positive predictive value, and negative predictive value for both detection methods were calculated. Receiver operating characteristic curves were constructed to assess the area under the curve (AUC) for evaluating the clinical value of mNGS in suspected intracranial infectious pathogen diagnosis. Results showed a positivity rate of 71.67% (43 cases) with mNGS compared to 28.33% (17 cases) with traditional pathogen detection methods, demonstrating a significant difference (P < 0.05). The sensitivity of mNGS for detecting ICIs was 83.7%, significantly higher than the 34.88% observed with traditional methods (P < 0.05). The pathogen detection rate of mNGS was higher than traditional methods (P = 0.002), with an AUC of 0.856 (95% CI: 0.638–0.967), significantly greater than the AUC of 0.572 (95% CI: 0.350–0.792) for traditional methods (P < 0.05). mNGS successfully identified microorganisms such as Cryptococcus, Propionibacterium, Staphylococcus, Corynebacterium, Micrococcus, and Candida associated with ICIs. These findings underscore the clinical applicability of mNGS technology in analyzing the characteristics of HIV infection and ICI post-neurosurgical procedures. This technology enables more accurate diagnosis and treatment of ICIs, providing valuable insights for developing effective therapeutic strategies.