NCT06235866

Risk Identification of Long-term Complications

Risk Identification of Long-term Complications in the Recover Patients With Severe COVID-19

• Status: Enrolling By Invitation
• Phase: —
• Study type: Observational
• Enrollment: 500 (estimated)
• Sponsor: Wuhan Central Hospital · Academic / Other
• Sex: All
• Age: 18 Years – 80 Years
• Healthy volunteers: Accepted

Summary

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.

Detailed description

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.

Conditions

• Severe COVID-19

Interventions

Type	Name	Description
OTHER	Pulmonary rehabilitation	According to the pulmonary rehabilitation guidelines, patients with severe COVID-19 were given regular rehabilitation treatment, including breathing exercises and physical rehabilitation exercises.

Timeline

• Start date: 2023-02-01
• Primary completion: 2024-09-30
• Completion: 2025-11-01
• First posted: 2024-02-01
• Last updated: 2024-05-08

Locations

1 site across 1 country: China