Yi-xiang Peng

TL;DR: During the first 2 months of the current outbreak, Covid-19 spread rapidly throughout China and caused varying degrees of illness, and patients often presented without fever, and many did not have abnormal radiologic findings.

TL;DR: The 2019-nCoV epidemic spreads rapidly by human-to-human transmission and the disease severity (including oxygen saturation, respiratory rate, blood leukocyte/lymphocyte count and chest X-ray/CT manifestations) predict poor clinical outcomes.

TL;DR: Comorbidities are present in around one fourth of patients with COVID-19 in China, and predispose to poorer clinical outcomes, and have significantly escalated risks of reaching to the composite endpoint compared with those who had a single comorbidity.

TL;DR: The proposed nomogram accurately predict clinical outcomes of patients with COVID-19 based on individual characteristics and has sufficient discriminatory power with the C-index of 0.91.

TL;DR: Hematologic and immunologic impairment showed a significantly different profile between survivors and non-survivors in COVID-19 patients with different severity, and a multivariate Cox regression model suggested that restored levels of lymphocytes, eosinophils and platelets could serve as the predictors for the recovery, while progressive increases in neutrophils, basophil and IL-6 were associated with fatal outcome.