The investigators retrospectively analyze the clinical characteristics of severe COVID-19 in our hospital, and then establish a prediction model for long-term complications in patients with severe COVID-19, and strengthen follow-up to improve the prognosis of patients.
At present, there is a lack of prediction models for the long-term complications of severe COVID-19. Therefore, the investigators used the hospital big data platform to retrospectively analyze the clinical characteristics of severe COVID-19 in our hospital, and conducted cohort follow-up of the changes in lung function including FEV1, FVC，FEV1% and DLCO, etc and and high-resolution CT of patients after discharge. COX model and other statistical methods were used to establish a prediction model for long-term complications of severe COVID-19, and early identification and intervention, strengthen follow-up, and improve the prognosis of patients.
Study Type
OBSERVATIONAL
Enrollment
500
According to the pulmonary rehabilitation guidelines, patients with severe COVID-19 were given regular rehabilitation treatment, including breathing exercises and physical rehabilitation exercises.
Follow-up of patients with severe COVID-19
Wuhan, China
Lung function
Pulmonary function indicators improved gradually
Time frame: 1 year
Imaging of the lung
The residual lesions in the lung were gradually absorbed
Time frame: 1 year
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