BACKGROUND:The novel coronavirus disease 2019 (COVID-19) has become a global health emergency. The cumulative number of new confirmed cases and deaths are still increasing out of China. Independent predicted factors associated with fatal outcomes remain uncertain.RESEARCH QUESTION: The goal of the current study was to investigate the potential risk factors associated with fatal outcomes from COVID-19 through a multivariate Cox regression analysis and a nomogram model. STUDY DESIGN AND METHODS:A retrospective cohort of 1,590 hospitalized patients with COVID-19 throughout China was established. The prognostic effects of variables, including clinical features and laboratory findings, were analyzed by using Kaplan-Meier methods and a Cox proportional hazards model. A prognostic nomogram was formulated to predict the survival of patients with COVID-19. RESULTS:In this nationwide cohort, nonsurvivors included a higher incidence of elderly people and subjects with coexisting chronic illness, dyspnea, and laboratory abnormalities on admission compared with survivors. Multivariate Cox regression analysis showed that age $ 75 years (hazard ratio [HR], 7.86; 95% CI, 2. 44-25.35), age between 65 and 74 years (HR, 3.43; 95% CI, 1.24-9.5), coronary heart disease (HR, 4.28; 95% CI, 1.14-16.13), cerebrovascular disease (HR, 3.1; 95% CI, 1.07-8.94), dyspnea (HR, 3.96; 95% CI,, procalcitonin level > 0.5 ng/mL (HR, 8.72; 95% CI,, and aspartate aminotransferase level > 40 U/L (HR, 2.2; 95% CI, 1.1-6.73) were independent risk factors associated with fatal outcome. A nomogram was established based on the results of multivariate analysis. The internal bootstrap resampling approach suggested the nomogram has sufficient discriminatory power with a C-index of 0.91 (95% CI, 0.85-0.97). The calibration plots also showed good consistency between the prediction and the observation. INTERPRETATION:The proposed nomogram accurately predicted clinical outcomes of patients with COVID-19 based on individual characteristics. Earlier identification, more intensive surveillance, and appropriate therapy should be considered in patients at high risk.

Background: Crucial roles of hematologic and immunologic responses in progression of coronavirus disease 2019 (COVID-19) remain largely unclear. Objective: We sought to address the dynamic changes in hematologic and immunologic biomarkers and their associations with severity and outcomes of COVID-19. Methods: A retrospective study including 548 patients with COVID-19 with clarified outcome (discharged or deceased) from a national cohort in China was performed. Cross-sectional and longitudinal variations were compared and the associations with different severity and outcomes were analyzed. Results: On admission, the counts of lymphocytes, T-cell subsets, eosinophils, and platelets decreased markedly, especially in severe/critical and fatal patients. Increased neutrophil count and neutrophils-to-lymphocytes ratio were predominant in severe/critical cases or nonsurvivors. During hospitalization, eosinophils, lymphocytes, and platelets showed an increasing trend in survivors, but maintained lower levels or dropped significantly afterwards in nonsurvivors. Nonsurvivors kept a high level or showed an upward trend for neutrophils, IL-6, procalcitonin, D-dimer, amyloid A protein, and C-reactive protein, which were kept stable or showed a downward trend in survivors. Positive correlation between CD8 1 T-cell and lymphocytes count was found in survivors but not in nonsurvivors. A multivariate Cox regression model suggested that restored levels of lymphocytes, eosinophils, and platelets could serve as predictors for recovery, whereas progressive increases in neutrophils, basophils, and IL-6 were associated with fatal outcome. Conclusions: Hematologic and immunologic impairment showed a significantly different profile between survivors and nonsurvivors in patients with COVID-19 with different severity. The longitudinal variations in these biomarkers could serve to predict recovery or fatal outcome.

Background A novel variant of SARS-CoV-2, the Delta variant of concern (VOC, also known as lineage B.1.617.2), is fast becoming the dominant strain globally. We reported the epidemiological, viral, and clinical characteristics of hospitalized patients infected with the Delta VOC during the local outbreak in Guangzhou, China. Methods We extracted the epidemiological and clinical information pertaining to the 159 cases infected with the Delta VOC across seven transmission generations between May 21 and June 18, 2021. The whole chain of the Delta VOC transmission was described. Kinetics of viral load and clinical characteristics were compared with a cohort of wild-type infection in 2020 admitted to the Guangzhou Eighth People's Hospital. Findings There were four transmission generations within the first ten days. The Delta VOC yielded a significantly shorter incubation period (4.0 vs. 6.0 days), higher viral load (20.6 vs. 34.0, cycle threshold of the ORF1a/b gene), and a longer duration of viral shedding in pharyngeal swab samples (14.0 vs. 8.0 days) compared with the wild-type strain. In cases with critical illness, the proportion of patients over the age of 60 was higher in the Delta VOC group than in the wild-type strain (100.0% vs. 69.2%, p = 0.03). The Delta VOC had a higher risk than wild-type infection in deterioration to critical status (hazards ratio 2.98 [95%CI 1.29-6.86]; p = 0.01). Interpretation Infection with the Delta VOC is characterized by markedly increased transmissibility, viral loads and risk of disease progression compared with the wild-type strain, calling for more intensive prevention and control measures to contain future outbreaks. Funding National Grand Program, National Natural Science Foundation of China, Guangdong Provincial Department of Science and Technology, Guangzhou Laboratory