This study intends to use the relevant case data of COVID-19 in Hubei Province, using big data processing and mining methods to evaluate the effects of clinical indicators, drug use and genes on the clinical prognosis of COVID-19 patients, so as to provide a theoretical basis for the treatment of these diseases and reduce the mortality.
Hubei Province, as the forefront of the fight against epidemic, has the largest number of patients infected with SARS-CoV-2 and the highest quality medical data. However, so far, these data have not been fully analyzed, if these data can not be mined and used, it will be a great loss to the whole human race. By fully mining and analyzing these data, we can sum up a large number of experiences related to COVID-19, summarize various laws of this kind of disease, and provide clinical evidence based on large samples for the research of this disease, eventually contribute China's experience to the global fight against the epidemic. Based on the above background, this study intends to use the relevant case data of COVID-19 in Hubei Province, using big data processing and mining methods to evaluate the effects of clinical indicators, drug use and genes on the clinical prognosis of COVID-19 patients, so as to provide a theoretical basis for the treatment of these diseases and reduce the mortality.
Study Type
OBSERVATIONAL
Enrollment
68,000
No intervention
Tongji Hospital
Wuhan, Hubei, China
All-cause mortality
Numbers and dates of death in each group
Time frame: 2 years
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