A Meta-analysis of Clinical Characteristics and Mortality COVID-19 Pneumonia

Abstract

Objective To investigate the Corona Virus Disease 2019(COVID-19) clinical characteristics and mortality risk by pooling the open published data.Methods Studies relevant to COVID-19 published in Pubmed, China Wanfang database, ChinaXiv and medRxiv were systematic screened by using the text word of “COVID-19”, 2019-nCoV, “SARS-CoV-2”, “NCP”. The mortality and clinical characteristic of the COVID-19 cases such as male/female ratio, mechanical ventilation ratio and top clinical symptom rate of the COVID-19 cases were pooled.ResultsTen clinical studies relevant to COVID-19 were identified by electronic searching the related databases. The combined mortality was 0.03(95%CI: 0.01-0.04) for COVID-19 cases by random effect model. The pooled female ratio of the COVID-19 cases from 10 published data was 0.41(95%CI:0.37-0.46). The pooled invasive and non-invasive ventilation ratio were 0.03(95%CI:0.01-0.05) and 0.06(95%CI:0.02-0.09) respectively for patients with COVID-19 pneumonia. The pooled clinical symptom rate of fever, cough, headache and fatigue were 0.80(95%CI:0.60-1.01), 0.12(95%CI:0.08-0.17), 0.68(95%CI:0.57-0.73) and 0.51(95%CI:0.36-0.67) respectively under random effect model.Conclusion According to the present published data, male was more cline to susceptible to COVID-19 compared to female. The fever, cough and fatigue were the most common symptom of COVID-19 cases. About 10% of patients received invasive or noninvasive mechanical ventilation with the overall crude mortality of 3%.

Multidimensional Representation of COVID-19 Data Using OLAP Information Technology

“…The structure of images metadata collected from open medical sources, websites, and publications is described. A group of authors [10] perform statistical analysis of metadata on clinical descriptions of pneumonia and mortality from COVID-19, and analytical overview of researches on the treatment and prevention of Covid-19 is presented in the paper [11].…”