NCT04358510

Brief Summary

The objective of this study is to develop and evaluate an algorithm which accurately predicts mortality in COVID-19, pneumonia and mechanically ventilated ICU patients.

Trial Health

87
On Track

Trial Health Score

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

Enrollment
114

participants targeted

Target at P50-P75 for all trials

Timeline
Completed

Started Apr 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

April 1, 2020

Completed
16 days until next milestone

Primary Completion

Last participant's last visit for primary outcome

April 17, 2020

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

April 17, 2020

Completed
3 days until next milestone

First Submitted

Initial submission to the registry

April 20, 2020

Completed
4 days until next milestone

First Posted

Study publicly available on registry

April 24, 2020

Completed
Last Updated

April 24, 2020

Status Verified

April 1, 2020

Enrollment Period

16 days

First QC Date

April 20, 2020

Last Update Submit

April 21, 2020

Conditions

COVID-19PneumoniaMechanical Ventilation

Keywords

machine learningCOVID-19mortalitypredictionpneumoniamechanical ventilation

Outcome Measures

Primary Outcomes (3)

  • Mortality outcome in COVID-19 ICU patients

    Deceased or not deceased

    Through study completion, an average of 2 months

  • Mortality outcome in mechanically ventilated ICU patients

    Deceased or not deceased

    Through study completion, an average of 2 months

  • Mortality outcome in pneumonia ICU patients

    Deceased or not deceased

    Through study completion, an average of 2 months

Study Arms (1)

COViage

Machine learning intervention

Device: COViage

Interventions

COViageDEVICE

The COViage machine learning algorithm is designed to predict mortality in COVID-19, pneumonia and mechanically ventilated ICU patients.

COViage

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

Retrospective study of 53,001 total ICU patients, including 9,166 patients with pneumonia and 25,895 mechanically ventilated patients, performed on the MIMIC dataset. The community hospital patient dataset included 114 patients positive for SARS-COV-2 by PCR test.

You may qualify if:

  • Patients aged 18 years or older
  • Record of ICU stay

You may not qualify if:

  • Patients aged less than 18 years
  • Patients for which there were no records of raw data or no discharge or death dates.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Dascena

Oakland, California, 94612-2603, United States

Location

MeSH Terms

Conditions

COVID-19Pneumonia

Condition Hierarchy (Ancestors)

Pneumonia, ViralRespiratory Tract InfectionsInfectionsVirus DiseasesCoronavirus InfectionsCoronaviridae InfectionsNidovirales InfectionsRNA Virus InfectionsLung DiseasesRespiratory Tract Diseases

Study Design

Study Type
observational
Observational Model
COHORT
Time Perspective
RETROSPECTIVE
Sponsor Type
INDUSTRY
Responsible Party
SPONSOR

Study Record Dates

First Submitted

April 20, 2020

First Posted

April 24, 2020

Study Start

April 1, 2020

Primary Completion

April 17, 2020

Study Completion

April 17, 2020

Last Updated

April 24, 2020

Record last verified: 2020-04

Locations

US(1)