Clinical and Radiomic Model of COVID-19

NCT04337502 | Completed

• 1 other identifier: UM_2020_GY_COVID-19
• Study Type: observational
• Target: 300
• Locations: 1 country
• Sites: 1

Brief Summary

To develop and validate a machine-learning model based on clinical, laboratory, and radiological characteristics alone or combination of COVID-19 patients to facilitate risk Assessment before and after symptoms and triage (home, hospitalization inward or ICU).

Conditions

Coronavirus; Machine Learning

Outcome Measures

Primary Outcomes (1)

• Predictive performance

  AUC, accuracy, sensitivity, and specificity

  Janunary 1, 2020, to February 13, 2020

Study Arms (2)

severe group

The severe group was designated when the patients had one of the following criteria during hospitalization issued by the Chinese National Health Committee (Version 3-5). 1) Respiratory distress with respiratory frequency ≥ 30/min; 2) Pulse Oximeter Oxygen Saturation ≤ 93% at rest; 3) Oxygenation index (artery partial pressure of oxygen/inspired oxygen fraction, PaO2/FiO2) ≤ 300 mmHg; 4) One of the conditions as following: a) respiratory failure occurs and requires mechanical ventilation; b) Shock occurs; c) ICU admission is required for combined organ failure.

Diagnostic Test: Machine learning model

non-severe group

The non-severe group was designated when the patients did not occur in the mentioned severe criteria until discharged from the hospital.

Diagnostic Test: Machine learning model

Interventions

Machine learning model DIAGNOSTIC_TEST

Machine learning, such as logistic regression, random forest, and deep learning

non-severe group; severe group

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

COVID-19 patients

You may qualify if:

• confirmed COVID-19 patients by high-throughput sequencing or real-time reverse-transcriptase polymerase-chain-reaction (RT-PCR) assay for nasal and pharyngeal swab specimens.

You may not qualify if:

• patients with severe illness when admitted;
• time interval \> 2 days between the admission and examinations;
• absent data or delayed results

Sponsors & Collaborators

• Maastricht University: lead
• Wuhan Central Hospital: collaborator

Study Sites (1)

The central hospital of Wuhan

Wuhan, Hubei, China

Location

MeSH Terms

Conditions

Coronavirus Infections

Condition Hierarchy (Ancestors)

Coronaviridae Infections; Nidovirales Infections; RNA Virus Infections; Virus Diseases; Infections

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: April 6, 2020
• First Posted: April 7, 2020
• Study Start: December 23, 2019
• Primary Completion: January 20, 2020
• Study Completion: March 3, 2020
• Last Updated: April 7, 2020

Record last verified: 2020-03

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)