Comparison of Sepsis Prediction Algorithms

NCT ID: NCT05943938

Last Updated: 2026-01-07

Basic Information

• Recruitment Status: NOT_YET_RECRUITING
• Total Enrollment: 1200 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2026-06-30
• Study Completion Date: 2026-12-31

Brief Summary

Sepsis is a severe response to infection resulting in organ dysfunction and often leading to death. More than 1.5 million people get sepsis every year in the U.S., and 270,000 Americans die from sepsis annually. Delays in the diagnosis of sepsis lead to increased mortality. Several clinical decision support algorithms exist for the early identification of sepsis. The research team will compare the performance of three sepsis prediction algorithms to identify the algorithm that is most accurate and clinically actionable. The algorithms will run in the background of the electronic health record (EHR) and the predictions will not be revealed to patients or clinical staff. In this current evaluation study, the algorithms will not affect any part of a patient's care. The algorithms will be deployed across the Emory healthcare system on data from all patients presenting to the emergency department.

Detailed Description

The primary goal of this study is to prospectively evaluate three sepsis prediction algorithms that are embedded in the EHR. The models will be deployed in a "shadow" mode, and the results will not be displayed to the treatment team during this study. Two of the algorithms are proprietary algorithms of the EHR provider (Epic). The third algorithm is an internally developed, open-source algorithm.

The algorithms will compute the probability of sepsis at periodic intervals and will continue to run on a patient's data until the patient's discharge, death, or upon initiation of intravenous antibiotics (at which point there is an indirect record of clinical suspicion of an infection).

Conditions

Sepsis

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Study Groups

ED Patients

All adult patients presenting to Emergency Departments (ED) in the Emory Healthcare system

Epic Sepsis Model Version - 1

Intervention Type: OTHER

The Epic Sepsis Model (ESM) version 1, a proprietary sepsis prediction model.

Epic Sepsis Model Version - 2

Intervention Type: OTHER

The Epic Sepsis Model (ESM) version 2, a proprietary sepsis prediction model.

Emory Sepsis Model

Intervention Type: OTHER

Emory internal algorithm

Interventions

Epic Sepsis Model Version - 1

The Epic Sepsis Model (ESM) version 1, a proprietary sepsis prediction model.

Intervention Type: OTHER

Epic Sepsis Model Version - 2

The Epic Sepsis Model (ESM) version 2, a proprietary sepsis prediction model.

Intervention Type: OTHER

Emory Sepsis Model

Emory internal algorithm

Intervention Type: OTHER

Other Intervention Names

Proprietary Epic sepsis algorithm -1; Proprietary Epic sepsis algorithm -2; Emory Sepsis Algorithm

Eligibility Criteria

Inclusion Criteria

• All adult patients admitted through the ED

Exclusion Criteria

• None

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Emory University

OTHER

Sponsor Role: lead

Responsible Party

Siva Bhavani

Assistant Professor

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Sivasubramanium Bhavani, MD

Role: PRINCIPAL_INVESTIGATOR

Emory University

Locations

Emory Midtown Hospital

Atlanta, Georgia, United States

Emory Saint Joseph's Hospital

Atlanta, Georgia, United States

Emory Healthcare System

Atlanta, Georgia, United States

Emory Hospital

Atlanta, Georgia, United States

Emory Decatur Hospital

Decatur, Georgia, United States

Emory Johns Creek Hospital

Johns Creek, Georgia, United States

Emory Hillandale Hospital

Lithonia, Georgia, United States

Countries

United States

Central Contacts

Sivasubramanium Bhavani, MD

Role: CONTACT

sivasubramanium.bhavani@emory.edu

404-712-2970

Facility Contacts

Sivasubramanium Bhavani, MD

Role: primary

sivasubramanium.bhavani@emory.edu

(404) 501-1000

Sivasubramanium Bhavani, MD

Role: primary

sivasubramanium.bhavani@emory.edu

404-712-2970

Sivasubramanium Bhavani, MD

Role: primary

sivasubramanium.bhavani@emory.edu

(404) 501-8000

Other Identifiers

2024P008316

Identifier Type: OTHER

Identifier Source: secondary_id

STUDY00005958

Identifier Type: -

Identifier Source: org_study_id