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Clinical Trials/NCT04390516
NCT04390516CompletedNot Applicable

Prediction Of Respiratory Decompensation In Covid-19 Patients Using Machine Learning: The READY Trial

Dascena2 sites in 1 country197 target enrollmentStarted: March 24, 2020Last updated:
Conditions

Trial Snapshot

Phase
Not Applicable
Status
Completed
Sponsor
Enrollment
197
Locations
2
Primary Endpoint
Mechanically ventilated patient outcome

Study Overview

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.

Study Design

Study Type
Interventional
Allocation
Na
Intervention Model
Single Group
Primary Purpose
Diagnostic
Masking
None

Eligibility Criteria

Ages
18 Years to — (Adult, Older Adult)
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

Outcomes

Primary Outcomes

Mechanically ventilated patient outcome

Time Frame: Through study completion, an average of 2 months

Ventilated or not ventilated within 24 hours

Secondary Outcomes

  • Mortality or mechanically ventilated patient outcome(Through study completion, an average of 2 months)

Investigators

Sponsor
Dascena
Sponsor Class
Industry
Responsible Party
Sponsor

Study Sites (2)

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