Predictive algoRithm for EValuation and Intervention in SEpsis

Not Applicable

Completed

• Conditions: Severe Sepsis; Septic Shock; Sepsis

• Registration Number: NCT03235193
• Lead Sponsor: Dascena

Brief Summary

In this prospective study, the ability of a machine learning algorithm to predict sepsis and influence clinical outcomes, will be investigated at Cabell Huntington Hospital (CHH).

Detailed Description

Not available

Study Timeline

• Study Start: 2017-07-01
• Study First Submitted: 2017-07-27
• Study First Submitted QC: 2017-07-27
• Study First Posted: 2017-08-01
• Primary Completion: 2017-08-30
• Study Completion: 2017-08-30
• Status Verified: 2021-09
• Last Update Submitted: 2021-09-17
• Last Update Posted: 2021-09-21

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 2296

Inclusion Criteria

• All adult patients visiting the emergency department, or admitted to the participating intensive care unit (ICU) wards of Cabell Huntington Hospital will be eligible.

Exclusion Criteria

• All patients younger than 18 years of age will be excluded.

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: FACTORIAL

Primary Outcome Measures

Name	Time	Method
In-hospital mortality	Through study completion, an average of 30 days

Secondary Outcome Measures

Name	Time	Method
Hospital length of stay	Through study completion, an average of 30 days

Trial Locations

Locations (1)

Cabell Huntington Hospital; 🇺🇸 Huntington, West Virginia, United States