Objective. To investigate the value of coagulation indicators D‐dimer (DD), prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT), and fibrinogen (Fg) in predicting the severity and prognosis of COVID‐19. Methods. A total of 115 patients with confirmed COVID‐19, who were admitted to Tianyou Hospital of Wuhan University of Science and Technology between January 18, 2020, and March 5, 2020, were included. The dynamic changes of DD, PT, APTT, and Fg were tested, and the correlation with CT imaging, clinical classifications, and prognosis was studied. Results. Coagulation disorder occurred at the early stage of COVID‐19 infection, with 50 (43.5%) patients having DD increased and 74 (64.3%) patients having Fg increased. The levels of DD and Fg were correlated with clinical classification. Among 23 patients who deceased, 18 had DD increased at the first lab test, 22 had DD increased at the second and third lab tests, and 18 had prolonged PT at the third test. The results from ROC analyses for mortality risk showed that the AUCs of DD were 0.742, 0.818, and 0.851 in three times of test, respectively; PT was 0.643, 0.824, and 0.937. In addition, with the progression of the disease, the change of CT imaging was closely related to the increase of the DD value (P < 0.01). Conclusions. Coagulation dysfunction is more likely to occur in severe and critically ill patients. DD and PT could be used as the significant indicators in predicting the mortality of COVID‐19.

A lot of previous studies have recently reported that the gut microbiota influences the development of colorectal cancer (CRC) in Western countries, but the role of the gut microbiota in Chinese population must be investigated fully. The goal of this study was to determine the role of the gut microbiome in the initiation and development of CRC. We collected fecal samples of 206 Chinese individuals: 59 with polyp (group P), 54 with adenoma (group A), 51 with colorectal cancer (group CC), and 42 healthy controls (group HC).16S ribosomal RNA (rRNA) was used to compare the microbiota community structures among healthy controls, patients with polyp, and those with adenoma or colorectal cancer. Our study proved that intestinal flora, as a specific indicator, showed significant differences in its diversity and composition. Sobs, Chao, and Ace indexes of group CC were significantly lower than those of the healthy control group (CC group: Sobs, Chao, and Ace indexes were 217.3 ± 69, 4265.1 ± 80.7, and 268.6 ± 78.1, respectively; HC group: Sobs, Chao, and Ace indexes were 228.8 ± 44.4, 272.9 ± 58.6, and 271.9 ± 57.2, respectively). When compared with the healthy individuals, the species richness and diversity of intestinal flora in patients with colorectal cancer were significantly reduced: PCA and PCoA both revealed that a significant separation in bacterial community composition between the CC group and HC group (with PCA using the first two principal component scores of PC1 14.73% and PC2 10.34% of the explained variance, respectively; PCoA : PC1 = 14%, PC2 = 9%, PC3 = 6%). Wilcox tests was used to analyze differences between the two groups, it reveals that Firmicutes (P=0.000356), Fusobacteria (P=0.000001), Proteobacteria (P=0.000796), Spirochaetes (P=0.013421), Synergistetes (P=0.005642) were phyla with significantly different distributions between cases and controls. The proportion of microorganism composition is varying at different stages of colon cancer development: Bacteroidetes (52.14%) and Firmicutes (35.88%) were enriched in the healthy individuals; on the phylum level, the abundance of Bacteroidetes (52.14%-53.92%-52.46%-47.06%) and Firmicutes (35.88%-29.73%-24.27%-25.36%) is decreasing with the development of health-polyp-adenomas-CRC, and the abundance of Proteobacteria (9.33%-12.31%-16.51%-22.37%) is increasing. PCA and PCOA analysis showed there was no significant (P < 0.05) difference in species similarity between precancerous and carcinogenic states. However, the composition of the microflora in patients with precancerous lesions (including patients with adenoma and polyp) was proved to have no significant disparity (P < 0.05). Our study provides insights into new angles to dig out potential biomarkers in diagnosis and treatment of colorectal cancer and to provide scientific advice for a healthy lifestyle for the sake of gut microbiota.

To explore the value, and influencing factors, of D-dimer on the prognosis of patients with COVID-19. A total of 1,114 patients with confirmed COVID-19 who were admitted to three designated COVID-19 hospitals in Wuhan, China from January 18, 2020, to March 24, 2020, were included in this study. We examined the relationship between peripheral blood levels of D-dimer, and clinical classification and prognosis, as well as its related influencing factors. D-dimer levels were found to be related to the clinical classification and the prognosis of clinical outcome. D-dimer levels were more likely to be abnormal in severely and critically ill patients compared with mild and ordinary cases, while D-dimer levels of patients who had died were significantly higher than those of surviving patients according to the results of the first and last lab tests. The results from ROC analyses for mortality risk showed that the AUCs of D-dimer were 0.909, YI was 0.765 at the last lab test, and a D-dimer value of 2.025 mg/L was regarded to be the optimal probability cutoff for a prognosis of death. In addition, we found that patients with advanced age, male gender, dyspnea symptoms, and some underlying diseases have a higher D-dimer value (p < 0.05). In short, D-dimer is related to the clinical classification and can be used to evaluate the prognosis of COVID-19 patients. The D-dimer value of 2.025 mg/L was the optimal probability cutoff for judging an outcome of death. Advanced age, male gender, dyspnea symptoms, and some underlying diseases are influencing factors for D-dimer levels, which impacts the prognosis of patients.

Background: The temporal relationship between SARS-CoV-2 and antibody production and clinical progression remained obscure. The aim of this study was to describe the viral kinetics of symptomatic patients with SARS-CoV-2 infection and identify factors that might contribute to prolonged viral shedding. Methods: Symptomatic COVID-19 patients were enrolled in two hospitals in Wuhan, China, from whom the respiratory samples were collected and measured for viral loads consecutively by reverse transcriptase quantitative PCR (RT-qPCR) assay. The viral shedding pattern was delineated in relate to the epidemiologic and clinical information. Results: Totally 2726 respiratory samples collected from 703 patients were quantified. The SARS-CoV-2 viral loads were at the highest level during the initial stage after symptom onset, which subsequently declined with time. The median time to SARS-CoV-2 negativity of nasopharyngeal test was 28 days, significantly longer in patients with older age (> 60 years old), female gender and those having longer interval from symptom onset to hospital admission (> 10 days). The multivariate Cox regression model revealed significant effect from older age (HR 0.73, 95% CI 0.55–0.96), female gender (HR 0.72, 95% CI 0.55–0.96) and longer interval from symptom onset to admission (HR 0.44, 95% CI 0.33–0.59) on longer time to SARS-CoV-2 negativity. The IgM antibody titer was significantly higher in the low viral loads group at 41–60 days after symptom onset. At the population level, the average viral loads were higher in early than in late outbreak periods. Conclusions: The prolonged viral shedding of SARS-CoV-2 was observed in COVID-19 patients, particularly in older, female and those with longer interval from symptom onset to admission.