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Purpose

The objective of this study is to develop and evaluate an algorithm which accurately predicts mortality in COVID-19, pneumonia and mechanically ventilated ICU patients.

Conditions

Eligibility

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

Inclusion Criteria

  • Patients aged 18 years or older - Record of ICU stay

Exclusion Criteria

  • Patients aged less than 18 years - Patients for which there were no records of raw data or no discharge or death dates.

Study Design

Phase
Study Type
Observational
Observational Model
Cohort
Time Perspective
Retrospective

Arm Groups

ArmDescriptionAssigned Intervention
COViage Machine learning intervention
  • Device: COViage
    The COViage machine learning algorithm is designed to predict mortality in COVID-19, pneumonia and mechanically ventilated ICU patients.

Recruiting Locations

More Details

NCT ID
NCT04358510
Status
Completed
Sponsor
Dascena

Detailed Description

Retrospective study of 53,001 total ICU patients, including 9,166 patients with pneumonia and 25,895 mechanically ventilated patients, performed on the MIMIC dataset. The NPH patient dataset includes 114 patients positive for SARS-COV-2 by PCR test.

Notice

Study information shown on this site is derived from ClinicalTrials.gov (a public registry operated by the National Institutes of Health). The listing of studies provided is not certain to be all studies for which you might be eligible. Furthermore, study eligibility requirements can be difficult to understand and may change over time, so it is wise to speak with your medical care provider and individual research study teams when making decisions related to participation.