Clinical Trials Directory

Trials / Completed

CompletedNCT04423991

Identification of a Responsive Subpopulation to Hydroxychloroquine in COVID-19 Patients Using Machine Learning

Identification of a Responsive Subpopulation to Hydroxychloroquine in COVID-19 Patients Using Machine Learning: the IDENTIFY Trial

Status
Completed
Phase
N/A
Study type
Interventional
Enrollment
290 (actual)
Sponsor
Dascena · Industry
Sex
All
Age
Healthy volunteers
Not accepted

Summary

The purpose of this study was to assess the performance of a machine learning algorithm which identifies patients for whom hydroxychloroquine treatment is associated with predicted survival.

Detailed description

In a multi-center pragmatic clinical trial, COVID-19 positive patients admitted to 6 United States medical centers were enrolled between March 10 and June 4, 2020. A machine learning algorithm was used to determine which patients were suitable for treatment with hydroxychloroquine.

Conditions

Interventions

TypeNameDescription
DEVICECOViageMachine learning intervention

Timeline

Start date
2020-03-10
Primary completion
2020-06-04
Completion
2020-06-04
First posted
2020-06-09
Last updated
2020-06-09

Locations

1 site across 1 country: United States

Source: ClinicalTrials.gov record NCT04423991. Inclusion in this directory is not an endorsement.

Identification of a Responsive Subpopulation to Hydroxychloroquine in COVID-19 Patients Using Machine Learning (NCT04423991) · Clinical Trials Directory