Predictive algoRithm for EValuation and Intervention in SEpsis (PREVISE)

September 17, 2021 updated by: Dascena

Prediction of Severe Sepsis Using a Machine Learning Algorithm

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).

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Study Type

Interventional

Enrollment (Actual)

2296

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • United States
    • West Virginia
      • Huntington, West Virginia, United States, 25701
        • Cabell Huntington Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Description

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 Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: Non-Randomized
  • Interventional Model: Factorial Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: With InSight
Healthcare provider receives an alert from InSight for patients trending towards severe sepsis. Healthcare provider also receives information from the severe sepsis detector in the CHH electronic health record.
Other: Severe Sepsis Prediction
Upon receiving an InSight alert, healthcare provider follows standard practices in assessing possible (severe) sepsis and intervening accordingly.
Other: Severe Sepsis Detection
Upon receiving information from the severe sepsis detector in the CHH electronic health record, healthcare provider follows standard practices in assessing possible (severe) sepsis and intervening accordingly.
Active Comparator: Without Insight
Healthcare provider does not receive any alerts from InSight. Healthcare provider receives information from the severe sepsis detector in the CHH electronic health record.
Other: Severe Sepsis Detection
Upon receiving information from the severe sepsis detector in the CHH electronic health record, healthcare provider follows standard practices in assessing possible (severe) sepsis and intervening accordingly.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Time Frame
In-hospital mortality
Time Frame: Through study completion, an average of 30 days
Through study completion, an average of 30 days

Secondary Outcome Measures

Outcome Measure
Time Frame
Hospital length of stay
Time Frame: Through study completion, an average of 30 days
Through study completion, an average of 30 days

Other Outcome Measures

Outcome Measure
Time Frame
Hospital readmission
Time Frame: Through study completion, an average of 30 days
Through study completion, an average of 30 days
ICU length of stay
Time Frame: Through study completion, an average of 30 days
Through study completion, an average of 30 days

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Dascena

Collaborators

Cabell Huntington Hospital

Investigators

  • Principal Investigator: Hoyt Burdick, Cabell Huntington Hospital

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

July 1, 2017

Primary Completion (Actual)

August 30, 2017

Study Completion (Actual)

August 30, 2017

Study Registration Dates

First Submitted

July 27, 2017

First Submitted That Met QC Criteria

July 27, 2017

First Posted (Actual)

August 1, 2017

Study Record Updates

Last Update Posted (Actual)

September 21, 2021

Last Update Submitted That Met QC Criteria

September 17, 2021

Last Verified

September 1, 2021

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 1097090-1

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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