Coronavirus, COVID-19, Mortality
Conditions
Brief 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.
Interventions
DEVICECOViage
Machine learning intervention
Sponsors
Dascena
Study design
Allocation
NON_RANDOMIZED
Intervention model
PARALLEL
Primary purpose
DIAGNOSTIC
Masking
NONE
Eligibility
Sex/Gender
ALL
Healthy volunteers
No
Inclusion criteria
* Patient admitted to covered ward and tested positive for COVID-19 * Patient had COViage applied to electronic health record data within four hours of COVID-19 test
Exclusion criteria
* Patient not admitted to covered ward or tested negative for COVID-19 * Patient had COViage applied to electronic health record data greater than four hours after COVID-19 test
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Mortality outcome | Through study completion, an average of 3 months | Time to in-hospital death |
Countries
United States
Outcome results
None listed