Respiratory Decompensation and Model for the Triage of COVID-19 Patients
Not Applicable
Completed
- Conditions
- COVID-19CoronavirusMechanical VentilationMortality
- Interventions
- Device: COViage
- Registration Number
- NCT04390516
- Lead Sponsor
- Dascena
- Brief Summary
The purpose of this study is to prospectively evaluate a machine learning algorithm for the prediction of outcomes in COVID-19 patients.
- Detailed Description
In a multi-center prospective clinical trial, a machine learning algorithm was deployed at five partner hospitals to analyze live patient data, including blood pressure and Creatinine levels, to determine the algorithm's ability to predict COVID-19 patient prognosis. The primary endpoint was mechanical ventilation of study subjects within 24 hours after hospital admission separate from a decompensation alert related to oxygen levels.
Recruitment & Eligibility
- Status
- COMPLETED
- Sex
- All
- Target Recruitment
- 197
Inclusion Criteria
- Patients aged 18 years or older
- Confirmed COVID-19 infection through RT-PCR test
Exclusion Criteria
- Patients aged less than 18 years
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- SINGLE_GROUP
- Arm && Interventions
Group Intervention Description COViage COViage Machine learning intervention
- Primary Outcome Measures
Name Time Method Mechanically ventilated patient outcome Through study completion, an average of 2 months Ventilated or not ventilated within 24 hours
- Secondary Outcome Measures
Name Time Method Mortality or mechanically ventilated patient outcome Through study completion, an average of 2 months Death or ventilated, or no death or not ventilated within 24 hours
Trial Locations
- Locations (1)
Dascena
🇺🇸Oakland, California, United States