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Prediction of Patient Deterioration Using Machine Learning
Prediction of Patient Deterioration Using Machine Learning

NCT05045742

CompletedN/A

Sponsor: Brigham and Women's Hospital

Conditions: Infection, Heart Failure, Chronic Obstructive Pulmonary Disease, Asthma, Gout Flare

Interventions: Traditional vital sign alarms versus the BioVitals Index vs the National Early Warning Score 2

Countries: United States

This is a retrospective observational study drawing on data from the Brigham and Women's Home Hospital database. Sociodemographic and clinic data from a training cohort were used to train a machine learning algorithm to predict patient deterioration throughout a patient's admission. This algorithm was then validated in a validation cohort.

Eligibility overview

Sex: ALL

Age: 18 Years to —

Healthy volunteers: No

Study type: OBSERVATIONAL

Eligibility criteria
Inclusion Criteria:

Cared for in the Brigham and Women's Home Hospital study

Exclusion Criteria:

Incomplete continuous monitoring data
Locations (2)
  • Boston, Massachusetts, United States
  • Boston, Massachusetts, United States