Analysis of fecal microbiota and related clinical indicators in ICU patients with sepsis.

Background: To analyze the characteristics of fecal microbiota disturbance in the intensive care unit (ICU) patients with sepsis and the correlation with related clinical indicators. Methods: This study included 31 patients with sepsis admitted to the emergency ICU ward between September 2019 and December 2021. They were divided into Group without septic shock (ND_NS group, 7 cases) and Group with septic shock (ND_S group, 24 cases) according to the presence or absence of septic shock. Furthermore, we divided these 31 sepsis patients into Clinical Improvement group (21 cases) and Death or DAMA group (10 cases) based on clinical outcome, 15 cases of Physical Examiner recruited in the same period were included as control group: ND_HC group (15 cases). The fecal samples of the patients with sepsis within 24 h of admission and random fecal samples of the control group were collected and analyzed by 16S rDNA gene sequencing used for the analysis of fecal microbiota. At the same time, the relevant clinical data of these patients with sepsis were also collected for analysis. Results: There were 15 cases with drug-resistant bacteria in the ND_S group and only 2 cases in the ND_NS group (P = 0.015). There were significant differences in APACHE II score, length of ICU stay, lactate level, and oxygenation index of patients between the Death or DAMA group and Clinical Improvement group (all P < 0.05). For phylum level, the abundance of Firmicutes, Actinobacteria, and Bacteroidetes decreased in the ND group compared with the ND_HC group, while the abundance of Proteobacteria increased (P < 0.05). For genus level, the relative abundance of Escherichia-Shigella and Klebsiella were significantly increased in the ND group compared with the ND_HC group (P < 0.05). The top six genera in relative abundance in the ND_S group were Escherichia-Shigella, Enterococcus, Bifidobacterium, Lactobacillus, Akkermansia, and Klebsiella. Compared with the Clinical Improvement group, the relative abundance of Escherichia-Shigella and Klebsiella in the Death or DAMA group showed an increasing trend with no significant significance, while the relative abundance of Enterococcus and Faecalibacterium decreased in the Death or DAMA group (P < 0.05). Alpha diversity analysis showed that compared with the ND_HC group, the alpha diversity of the fecal microbiota in the ND group decreased. There were significant differences in the Observed_species index, Chao1 index, and ACE index of patients between the ND_HC group and ND group (all P < 0.05). Moreover, compared with the ND_NS group, the Alpha diversity of the ND_S group was more abundant. PCoA analysis showed significant differences in microbial community structure between the ND group and ND_HC group (P = 0.001). There also were significant differences in microbial community structure between the ND_S group and ND_NS group (P = 0.008). LEfSe analysis showed that compared with the ND_HC group, there were significant differences in the species of the ND group, including Enterobacteriaceae, Escherichia-Shigella, Enterococcus, Elizabethkingia, and Family_XIII_AD3011_group. Conclusions: ICU patients with sepsis suffered intestinal microecological disturbances with significantly decreased abundance of fecal microbiota, diversity, and beneficial symbiotic bacteria. For these patients, the ratio of pathogenic bacteria, including Escherichia-Shigella and Klebsiella increased and became the main bacterial genus in some samples. Moreover, the increasing trend of these two pathogenic bacteria may be correlated with the development of septic shock and the risk of death in patients with sepsis.

Gene signature for the prediction of the trajectories of sepsis-induced acute kidney injury.

BACKGROUND: Acute kidney injury (AKI) is a common complication in sepsis. However, the trajectories of sepsis-induced AKI and their transcriptional profiles are not well characterized. METHODS: Sepsis patients admitted to centres participating in Chinese Multi-omics Advances In Sepsis (CMAISE) from November 2020 to December 2021 were enrolled, and gene expression in peripheral blood mononuclear cells was measured on Day 1. The renal function trajectory was measured by the renal component of the SOFA score (SOFArenal) on Days 1 and 3. Transcriptional profiles on Day 1 were compared between these renal function trajectories, and a support vector machine (SVM) was developed to distinguish transient from persistent AKI. RESULTS: A total of 172 sepsis patients were enrolled during the study period. The renal function trajectory was classified into four types: non-AKI (SOFArenal = 0 on Days 1 and 3, n = 50), persistent AKI (SOFArenal > 0 on Days 1 and 3, n = 62), transient AKI (SOFArenal > 0 on Day 1 and SOFArenal = 0 on Day 3, n = 50) and worsening AKI (SOFArenal = 0 on Days 1 and SOFArenal > 0 on Day 3, n = 10). The persistent AKI group showed severe organ dysfunction and prolonged requirements for organ support. The worsening AKI group showed the least organ dysfunction on day 1 but had higher serum lactate and prolonged use of vasopressors than the non-AKI and transient AKI groups. There were 2091 upregulated and 1,902 downregulated genes (adjusted p < 0.05) between the persistent and transient AKI groups, with enrichment in the plasma membrane complex, receptor complex, and T-cell receptor complex. A 43-gene SVM model was developed using the genetic algorithm, which showed significantly greater performance predicting persistent AKI than the model based on clinical variables in a holdout subset (AUC: 0.948 [0.912, 0.984] vs. 0.739 [0.648, 0.830]; p < 0.01 for Delong's test). CONCLUSIONS: Our study identified four subtypes of sepsis-induced AKI based on kidney injury trajectories. The landscape of host response aberrations across these subtypes was characterized. An SVM model based on a gene signature was developed to predict renal function trajectories, and showed better performance than the clinical variable-based model. Future studies are warranted to validate the gene model in distinguishing persistent from transient AKI.

Clinical efficacy of intravenous immunoglobulin therapy in critical ill patients with COVID-19: a multicenter retrospective cohort study.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) outbreak is a major challenge all over the world, without acknowledged treatment. Intravenous immunoglobulin (IVIG) has been recommended to treat critical coronavirus disease 2019 (COVID-19) patients in a few reviews, but the clinical study evidence on its efficacy in COVID-19 patients was lacking. METHODS: 325 patients with laboratory-confirmed critical COVID-19 were enrolled from 4 government-designated COVID-19 treatment centres in southern China from December 2019 to March 2020. The primary outcomes were 28- and 60-day mortality, and the secondary outcomes were the total length of in-hospital and the total duration of the disease. Subgroup analysis was carried out according to clinical classification of COVID-19, IVIG dosage and timing. RESULTS: In the enrolled 325 patients, 174 cases used IVIG and 151 cases did not. The 28-day mortality was improved with IVIG after adjusting confounding in overall cohort (P = 0.0014), and the in-hospital and the total duration of disease were longer in the IVIG group (P < 0.001). Subgroup analysis showed that only in patients with critical type, IVIG could significantly reduce the 28-day mortality, decrease the inflammatory response and improve some organ functions (all P < 0.05); the application of IVIG in the early stage (admission ≤ 7 days) with a high dose (> 15 g per day) exhibited significant reduction in 60-day mortality in the critical-type patients. CONCLUSION: Early administration of IVIG with high dose improves the prognosis of critical-type patients with COVID-19. This study provides important information on clinical application of IVIG in the treatment of SARS-CoV-2 infection, including patient selection and administration dosage and timing.