Clinical Characteristics and the Effect of Timing for Metagenomic Next-Generation Sequencing in Critically Ill Patients with Sepsis

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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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He, D., Liu, M., Chen, Q., Liu, Y., Tang, Y., Shen, F., … Liu, X. (2022). Clinical Characteristics and the Effect of Timing for Metagenomic Next-Generation Sequencing in Critically Ill Patients with Sepsis. Infection and Drug Resistance, 15, 7377–7387. https://doi.org/10.2147/IDR.S390256

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