Effect of a Sepsis Prediction Algorithm on Clinical Outcomes

Dascena

Status: Completed

Conditions: Severe Sepsis

Treatments: Diagnostic Test: InSight

Study type: Interventional

Funder types: Industry

Identifiers

NCT03960203

05172019

Details and patient eligibility

About

In this clinical outcomes analysis, the effect of a machine learning algorithm for severe sepsis prediction on in-hospital mortality, hospital length of stay, and 30-day readmission was evaluated.

Full description

Materials and Methods: Clinical outcomes evaluation performed on a multiyear, multicenter clinical data set of real-world data containing 75,147 patient encounters from nine hospitals. Mortality, hospital length of stay, and 30-day readmission analysis performed for 17,758 adult patients who met two or more Systemic Inflammatory Response Syndrome (SIRS) criteria at any point during their stay.

Enrollment: 75,147 patients

Sex: All

Ages: 18+ years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• All patients over the age of 18 presenting to the emergency department or admitted to an inpatient unit at the participating facilities were automatically included for clinical outcomes analysis

Exclusion criteria

• Patients under the age of 18

Trial design

75,147 participants in 1 patient group

Comparator

Experimental group

Description:

The comparator arm will involve patients monitored by InSight.

Treatment:

Diagnostic Test: InSight