Unsupervised Machine Learning for Clustering of Septic Patients to Determine Optimal Treatment

PHASE2UnknownINTERVENTIONAL
Enrollment

51,645

Participants

Timeline

Start Date

April 1, 2022

Primary Completion Date

March 31, 2024

Study Completion Date

March 31, 2024

Conditions
SepsisSevere SepsisSeptic Shock
Interventions
DIAGNOSTIC_TEST

Treatment-specific InSight

The InSight algorithm which draws information from a patient's electronic health record (EHR) to predict the onset of severe sepsis, and in this study will be customized to differentiate between clusters of patients who respond similarly to fluids treatment according to the nature of their disease progression.

DIAGNOSTIC_TEST

InSight

The non-customized InSight algorithm which draws information from a patient's electronic health record (EHR) to predict the onset of severe sepsis.

Sponsors

Lead Sponsor

All Listed Sponsors
lead

Dascena

INDUSTRY

NCT03752489 - Unsupervised Machine Learning for Clustering of Septic Patients to Determine Optimal Treatment | Biotech Hunter | Biotech Hunter