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BACKGROUND: Despite the growing interest in the impact of the gut microbiome on cancer, the relationship between the lung microbiome and lung cancer has received limited investigation. Additionally, the composition of the oral microbiome was found to differ from that of individuals with lung cancer, indicating that these microorganisms may serve as potential biomarkers for the detection of lung cancer. METHODS: Forty-three Chinese lung cancer patients were enrolled in the current retrospective study and 16 S rRNA sequencing was performed on saliva, cancerous tissue (CT) and paracancerous tissue (PT) samples. RESULTS: Diversity and species richness were significantly different between the oral and lung microbiota. Lung microbiota were largely composed of the phyla Proteobacteria, Firmicutes, Bacteroidetes and Actinobacteria. The relative abundance of Promicromonosporacea and Chloroflexi increased in CT, while Enterococcaceae and Enterococcus were enriched in PT (p<0.05). A cancer-related microbiota model was constructed and produced an area under the curve of 0.74 in the training set, indicating discrimination between subjects with and without cancer. CONCLUSIONS: Characterization of microbiota in saliva, CT and PT from Chinese lung cancer patients revealed little difference between CT and PT, indicating that the tumor and its microenvironment might influence the local microbiome. A model to distinguish between CT and PT was constructed, which has the potential to enhance our comprehension of the involvement of microbiota in the pathogenesis of lung cancer and identify novel therapeutic targets.
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Neoplasias Pulmonares , Microbiota , Humanos , Saliva , Pueblos del Este de Asia , Estudios Retrospectivos , Microbiota/genética , Microambiente TumoralRESUMEN
Introduction: This study aimed to conduct a clinical review and analysis to recommend options for the prevention and treatment of postoperative hemorrhage. Patients and Methods: A total of 138 patients who experienced postoperative hemorrhage after abdominal surgery in the period between January 2015 and December 2020 at the Sir Run Run Shaw Hospital, affiliated to Zhejiang University School of Medicine, participated in this study. They were divided into a group with primary bleeding only and a secondary bleeding group. Univariate and multivariate statistical analyses were performed, followed by plotting of cumulative hazard and survival curves for the two groups. Results: The main factors of interest found to be associated with secondary hemorrhage were duration of the operation, the time of the first bleeding incident, intervention time, performance of combined organ resection, use of surgical intervention, occurrence of abdominal infection, admission to the intensive care unit (ICU), postoperative length of stay, and total hospitalization expenses. Among these, a long operative duration (>5â h) and an extended intervention time (>5â h) were identified as independent predictors of risk of secondary hemorrhage. Conclusions: Secondary hemorrhage after abdominal surgery is mainly associated with subjective human factors, and it is an important cause of poor prognosis and even death. Proper reductions in operation time and implementation of a quick response to bleeding are the key factors in tackling bleeding. Further reduction in the rates of postoperative hemorrhage and mortality will require a concerted effort by surgeons in terms of both intraoperative surgical techniques and postoperative management.
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BACKGROUND: Atrial fibrillation (AF) is a leading cause of morbidity and mortality among elderly patients especially for patients in ICU. Previous studies revealed the impact of red blood cell distribution width (RDW) on predicting onset of AF. However, the prognostic value of RDW in critically ill patients with AF remains largely unknown. Thus, this study aims to explore the potential value on predicting in- and out-of-hospital mortality in critically ill patients with AF. METHODS: Data were extracted from the Medical Information Mart for Intensive Care (MIMIC) III database and 7,867 critically ill patients with AF were enrolled. The association between RDW and inhospital mortality was evaluated using the multiple logistic regression analysis as a design variable. Shortand long-term outcomes were compared between the low RDW and high RDW groups in critically ill patients balanced by the propensity score matching (PSM) algorithm. RESULTS: Analysis of the 7,867 patients revealed a linear relationship between RDW and in-hospital mortality. For critically ill patients with AF, the elevated level of RDW was associated with increased inhospital mortality, with the OR increasing from level 2 (OR: 1.75, 95% CI: 1.25 to 2.44) to level 5 (OR: 3.89, 95% CI: 2.55 to 5.93) with level 1 (RDW ≤13) as the reference group. 3841 enrolled patients with records in the CareVue systems were selected by PSM algorithm. The baseline characters were well balanced in 1,054 pairs of enrolled patients. A significant lower survival rate was observed in the high RDW group (P<0.001). CONCLUSIONS: High levels of RDW are associated with increased in- and out-of-hospital mortality in critically ill patients with AF.