Abstract
Metagenomic next-generation sequencing (mNGS) is a new method that combines high-throughput sequencing and bioinformatics analysis. However, it has not become as popular due to the limited testing equipment and high costs and lack of family awareness with not much relevant intensive care unit (ICU) research data. To explore the clinical use and value of metagenomics next-generation sequencing (mNGS) in patients with sepsis in the ICU. We conducted a retrospective analysis of 102 patients with sepsis admitted to the ICU of Peking University International Hospital from January 2018 to January 2022. Based on whether mNGS was performed, the identified patients were divided into the observation group (n= 51) and the control group (n= 51), respectively. Routine laboratory tests, including routine blood test, C-reactive protein, procalcitonin, and culture of suspicious lesion specimens were performed in both groups within 2 hours after admission to the ICU, while mNGS tests were performed in the observation group. Patients in both groups were routinely given initial anti-infective, anti-shock, and organ support treatment. Antibiotic regimens were optimized in a timely manner according to the etiological results. Relevant clinical data were collected. The testing cycle of mNGS was shorter than that of the conventional culture (30.79 ± 4.01 h vs. 85.38 ± 9.94h, P< 0.001), while the positive rate of mNGS was higher than that of the conventional culture (82.35% vs. 45.1%, P< 0.05), with obvious superiority in the detection of viruses and fungus. There were significant differences in the optimal time of antibiotics (48 h vs.100 h) and length of ICU stay (11 d vs. 16 d) between the observation group and control group (P< 0.01) respectively, with no difference in 28-day mortality (33.3% vs. 41.2%, P> 0.05). mNGS is useful in the detection of sepsis-causing pathogens in the ICU with the advantages of short testing time and high positive rate. There was no difference in the 28-day outcome between the two groups, which may be related to other confounding factors such as small sample size. Additional studies with extended sample size are needed.
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More From: Technology and health care : official journal of the European Society for Engineering and Medicine
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