ArticleInfection and drug resistance2022
Clinical Characteristics and the Effect of Timing for Metagenomic Next-Generation Sequencing in Critically Ill Patients with Sepsis.
Article in Infection and drug resistance, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- Effects of a clinical metagenomics intervention on clinical outcomes, healthcare costs, and health-related quality of life in patients with sepsis or septic shock: results of the randomized-controlled DigiSep trial.Intensive care medicine · 2026Trial
- Recent advances in early screening and diagnosis of sepsis: a narrative review.Frontiers in cellular and infection microbiology · 2026Review
- The value of metagenomic next-generation sequencing in the diagnosis of fever of unknown origin.Scientific reports · 2025Article
- Clinical application value of simultaneous plasma and bronchoalveolar lavage fluid metagenomic next generation sequencing in patients with pneumonia-derived sepsis.BMC infectious diseases · 2024Article
- Application of metagenomic next-generation sequencing technology in the etiological diagnosis of peritoneal dialysis-associated peritonitis.Open life sciences · 2024Article
- Clinical Value of Sampling Time of Metagenomic Next-Generation Sequencing in Patients with Severe Pneumonia.Infection and drug resistance · 2023Article
- Diagnostic performance and clinical impact of blood metagenomic next-generation sequencing in ICU patients suspected monomicrobial and polymicrobial bloodstream infections.Frontiers in cellular and infection microbiology · 2023Article
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Authors and funding
8 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Background: Metagenomic next-generation sequencing (mNGS) has a good performance for the identification of pathogens in infectious diseases, but few studies on the clinical characteristics of mNGS and the effect of timing for mNGS in critically ill patients with sepsis. Methods: We retrospectively included all patients diagnosed with sepsis after admission to the intensive care unit (ICU) of a university-affiliated hospital between Aug 1, 2019 and Apr 1, 2021. During the study period, pathogens for all enrolled subjects were obtained by mNGS. We analyzed the composition and positive rate of different samples type for mNGS. And then we used the univariable and multivariable logistic regression to explore the risk factors associated with all-cause mortality at 28 days. Results: A total of 87 patients were included and 87 samples were analyzed among these patients. The most common sample for mNGS was bronchoalveolar lavage fluid (BALF), about 84% (73/87). The positive rate of pathogens identification by mNGS was higher than conventional culture (92% vs 36%, p < 0.001). In addition to the pathogens detected by conventional culture, mNGS can detect more viruses and fungi. Based on the mNGS report, clinicians made adjustments to the antibiotic regimen for 72% patients. The multivariate binary logistic regression analysis suggested that age (OR, 1.036; 95% CI, 1.005-1.067; p = 0.021) and the sequential organ failure assessment (SOFA) score on the day of mNGS sampling were independent risk factors of death at 28 days (OR, 1.204; 95% CI, 1.038-1.397; p = 0.014). Conclusion: In critically ill patients with sepsis, the most common sample type for mNGS was BALF, and the positive rate of mNGS is higher than conventional cultures, especially in viruses and fungi. Meanwhile, mNGS can guide clinicians in adjusting antibiotic regimens. Age and the SOFA score on the day of mNGS sampling were independent risk factors for death.
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