NCT04347369

Brief Summary

The research aim to collect large samples of COVID-19 disease patients with clinical symptoms, laboratory and imaging examination data. Screening the biological indicators which are related to the occurrence of severe diseases. Then, investigators using artificial intelligence (AI) technology deep learning method to find a prediction model that can dynamically quantify COVID-19 disease severity.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
1,000

participants targeted

Target at P75+ for all trials

Timeline
Completed

Started Jan 2020

Shorter than P25 for all trials

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

January 17, 2020

Completed
2 months until next milestone

First Submitted

Initial submission to the registry

March 18, 2020

Completed
28 days until next milestone

First Posted

Study publicly available on registry

April 15, 2020

Completed
5 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

August 30, 2020

Completed
4 months until next milestone

Study Completion

Last participant's last visit for all outcomes

December 31, 2020

Completed
Last Updated

February 23, 2024

Status Verified

February 1, 2024

Enrollment Period

8 months

First QC Date

March 18, 2020

Last Update Submit

February 22, 2024

Conditions

COVID-19 Disease

Outcome Measures

Primary Outcomes (3)

  • discrimination

    The performance of our prediction model is evaluated with the receiver operating characteristic (ROC) curves, areas under the curves (AUCs) and concordance index (c-index).

    up to 3 months

  • Calibration

    The calibration curves analysis is used to show error between the predicted clinical phenotype with prediction model and actual clinical phenotype.

    up to 3 months

  • Net benefit

    Decision curve analysis was used to determine whether the models could be considered useful tools for clinical decisionmaking by comparing the net benefits at any threshold.

    up to 3 months

Study Arms (1)

Observed group

The patients who were detected COVID-19 disease by RT-PCR and CT imaging.

Other: other

Interventions

otherOTHER

clinical diagnosis

Observed group

Eligibility Criteria

Age18 Years - 80 Years
Sexall
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodProbability Sample
Study Population

Patients of COVID-19 disease

You may qualify if:

  • Patients of COVID-19 disease confirmed by virus nucleic acid RT-PCR and CT

You may not qualify if:

  • unconfirmed suspected cases
  • Patients during pregnancy and lactation
  • incomplete clinical data
  • inestigators considered patients ineligible for the trial

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Xinqiao Hospital of Chongqing

Chongqing, 400000, China

Location

Study Design

Study Type
observational
Observational Model
CASE ONLY
Time Perspective
RETROSPECTIVE
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Deputy Director,Head of Oncology department, Principal Investigator, Clinical Professor

Study Record Dates

First Submitted

March 18, 2020

First Posted

April 15, 2020

Study Start

January 17, 2020

Primary Completion

August 30, 2020

Study Completion

December 31, 2020

Last Updated

February 23, 2024

Record last verified: 2024-02

Locations

CN(1)