Sepsis Clinical Decision Support [CDS] Master Enrollment Study Protocol

Severe Sepsis Clinical Trial

Official title:

Sepsis Onset Warning System [SOWS] Master Enrollment Study Protocol

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05304728
• Other study ID #: 2.7.2-1
• Status: Recruiting
• Start date: February 15, 2021
• Est. completion date: December 31, 2024

Study information

• Verified date: January 2023
• Source: Beckman Coulter, Inc.
• Contact: Rebecca Henshaw
• Phone: 760-419-0809
• Email: rhenshaw[@]beckman.com
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

This protocol will collect real-world data retrospectively from the electronic health record (EHR) as data obtained from the delivery of routine medical care to develop a machine learning (ML)-based Clinical Decision Support (CDS) system for severe sepsis prediction and detection.

Description:

The purpose of this study is to gather data for the clinical development of the Sepsis Onset Warning System (SOWS) Software as Medical Device (SaMD) product to support a De Novo FDA submission and commercialization in the United States. Product development of SOWS is funded in part with federal funds from the Department of Health and Human Services; Office of the Assistant Secretary for Preparedness and Response; Biomedical Advanced Research and Development Authority. Data will be obtained from passive prospective collection of patient encounter data throughout the duration of the planned study to support the product development life cycle activities associated with developing the Sepsis Onset Warning System (SOWS) for severe sepsis risk detection. Inputs from patient health records in combination with proprietary hematology parameters developed by Beckman Coulter, such as Monocyte Distribution Width (MDW), will be used. The SOWS tool will look to use clinical measurements which are commonly and reliably available in the EHR as structured data elements, such as heart rate, temperature, blood pressure, and laboratory results and account for changes in these values over time.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 40000
• Est. completion date: December 31, 2024
• Est. primary completion date: March 30, 2024
• Gender: All
• Age group: 18 Years to 89 Years

Eligibility

Inclusion Criteria:

• All races, ages and ethnicities
• All patients admitted to the hospital or presenting to the Emergency Department

Exclusion Criteria:

• Patients not presenting to a hospital setting (e.g. urgent care, outpatient clinic excluded).

Related Conditions & MeSH terms

• Sepsis
• Severe Sepsis
• Severe Sepsis Without Septic Shock
• Toxemia

Locations

Country	Name	City	State
United States	Augusta University Medical School	Augusta	Georgia
United States	MetroHealth Systems	Cleveland	Ohio
United States	The Ohio State University	Columbus	Ohio
United States	Hackensack University Medical Center	Hackensack	New Jersey
United States	Indiana University Health	Indianapolis	Indiana

Sponsors (2)

Lead Sponsor	Collaborator
Beckman Coulter, Inc.	Biomedical Advanced Research and Development Authority

Country where clinical trial is conducted

United States, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Severe Sepsis	Identify patients having Severe Sepsis with the use of electronic health data	Within 6 hours from presentation to the emergency department
Secondary	Mortality	Hospital mortality at hospital for Severe Sepsis patients identified by algorithm using electronic health data as potential benefits for increased early detection of risk of severe sepsis	Within 6hours from presentation to the emergency department
Secondary	Length of Stay	Determine length of stay at hospital for Severe Sepsis patients identified by algorithm using electronic health data as potential benefits for increased early detection of risk of severe sepsis	Within 6hours from presentation to the emergency department
Secondary	Re-admission Rates	Determine potential reduction of hospital readmission rates for Severe Sepsis patients identified by algorithm using electronic health data as potential benefits for increased early detection of risk of severe sepsis	Within 6hours from presentation to the emergency department