Respiratory Decompensation and Model for the Triage of COVID-19 Patients

Purpose

The purpose of this study is to prospectively evaluate a machine learning algorithm for the prediction of outcomes in COVID-19 patients.

Conditions

  • COVID-19
  • Coronavirus
  • Mortality
  • Mechanical Ventilation

Eligibility

Eligible Ages
Over 18 Years
Eligible Sex
All
Accepts Healthy Volunteers
No

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

Phase
N/A
Study Type
Interventional
Allocation
N/A
Intervention Model
Single Group Assignment
Primary Purpose
Diagnostic
Masking
None (Open Label)

Arm Groups

ArmDescriptionAssigned Intervention
Other
COViage 		Machine learning intervention
  • Device: COViage
    The COViage machine learning algorithm is designed to predict mechanical ventilation and mortality within 24 hours after hospital admission.

Recruiting Locations

More Details

NCT ID
NCT04390516
Status
Completed
Sponsor
Dascena

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.