A Novel Nomogram to Predict Severity of COVID-19
Trial Snapshot
- Phase
- Not Applicable
- Status
- Completed
- Sponsor
- Enrollment
- 1,000
- Locations
- 1
- Primary Endpoint
- the consistency of predicted severe rate and observed severe rate of COVID-19 patients
Study Overview
Brief Summary
Investigators use clinical data from a large sample of COVID-19 disease patients to screen out biomarkers associated with disease severity. Then, a novel nomogram model will be established to predict covid-19 disease severity, which could provide important assistance and supplement for clinical work. In the case of extremely shortage of front-line medical resources, patients with potential severe diseases will be timely treated with the help of the novel nomogram model.
Study Design
- Study Type
- Observational
- Observational Model
- Case Only
- Time Perspective
- Retrospective
Eligibility Criteria
- Ages
- 18 Years to — (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- No
Inclusion Criteria
- •COVID-19 disease patients confirmed by virus nucleic acid RT-PCR and CT
Exclusion Criteria
- •unconfirmed suspected cases
- •Patients during pregnancy and lactation
- •incomplete clinical data
- •investigators considered patients ineligible for the trial
- •Child patients
Outcomes
Primary Outcomes
the consistency of predicted severe rate and observed severe rate of COVID-19 patients
Time Frame: up to 3 months
We aim to use the clinical data of COVID-19 patients to construct a nomogram model to predict the severe rate of each patient, then the the consistency of predicted severe rate and observed severe rate will be evaluated by calibration plot.
Duration of severe illness
Time Frame: up to 3 months
the duration of severe illness of each patient will evaluated
Secondary Outcomes
No secondary outcomes reported
Investigators
Jianguo Sun
Deputy Director,Head of Oncology department, Principal Investigator, Clinical Professor
Xinqiao Hospital of Chongqing