Prediction Models for Diagnosis and Prognosis of Severe COVID-19
Trial Snapshot
- Phase
- Not Applicable
- Status
- Completed
- Sponsor
- Enrollment
- 617
- Locations
- 6
- Primary Endpoint
- Chest CT and clinical features
Study Overview
Brief Summary
Clinical observation has found that COVID-19 patients often present inconsistency of clinical features, nucleic acid of the SARS-CoV-2 and imaging findings, which brings challenges to the management of patients.The quantitative assessment of patients' pulmonary lesions of chest CT, combined with the basic information, epidemiological history, clinical symptoms, basic diseases and other information of patients, will quickly establish a reliable prediction model for the severe COVID-19. This model will greatly contribute to the effective diagnosis and treatment of COVID-19.
Detailed Description
- Research purpose
The research team collected the clinical and chest CT of 1,000 COVID-19 patients from multiple hospitals. We plan to use these data to explore the imaging features of the COVID-19 and develop a convenient, easy-to-use, highly reliable imaging AI model for detecting and predicting the severe COVID-19. The model is used for imaging evaluation of COVID-19 patients, in order to achieve the purpose of early diagnosis, reasonable management of patients and prediction of severe COVID-19. 2. Research design and methods:
This research is a retrospective study. The project research period have 6 months. Start time: the date of ethics approval.
End time: August 20, 2020.
2.1 Establish an AI model for the detection of COVID-19 chest CT lesions Based on existing models and data, rapid detection of lesions on the chest high-resolution CT (HRCT) images of COVID-19, identification of the character of the lesions including the volume of the lesions.
Study Design
- Study Type
- Observational
- Observational Model
- Case Control
- Time Perspective
- Retrospective
Eligibility Criteria
- Sex
- All
- Accepts Healthy Volunteers
- No
Inclusion Criteria
- •The patient was tested positive for nucleic acid of the SARS-CoV-2
Exclusion Criteria
- Not provided
Outcomes
Primary Outcomes
Chest CT and clinical features
Time Frame: 2020-1-1 to 2020-6-1
chest CT imaging data of the patient, basic patient information, epidemiological history, clinical symptoms, and underlying diseases
Secondary Outcomes
No secondary outcomes reported