A Novel Nomogram to Predict Severity of COVID-19
February 22, 2024 updated by: Jianguo Sun, Xinqiao Hospital of Chongqing
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 Overview
Study Type
Observational
Enrollment (Actual)
1000
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Locations
-
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Chongqing
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Chongqing, Chongqing, China, 400000
- Xinqiao Hospital of Chongqing
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Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
18 years and older (Adult, Older Adult)
Accepts Healthy Volunteers
N/A
Sampling Method
Probability Sample
Study Population
COVID-19 disease patients
Description
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
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
|---|---|
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Observed group
COVID-19 disease patients who were detected by RT-PCR and CT imaging.
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clinical diagnosis
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What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
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.
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up to 3 months
|
|
Duration of severe illness
Time Frame: up to 3 months
|
the duration of severe illness of each patient will evaluated
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up to 3 months
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Sponsor
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Actual)
January 17, 2020
Primary Completion (Actual)
August 30, 2020
Study Completion (Actual)
December 31, 2021
Study Registration Dates
First Submitted
April 21, 2020
First Submitted That Met QC Criteria
April 27, 2020
First Posted (Actual)
April 28, 2020
Study Record Updates
Last Update Posted (Actual)
February 23, 2024
Last Update Submitted That Met QC Criteria
February 22, 2024
Last Verified
February 1, 2024
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- XQonc-016
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.