Comparison of Sepsis Prediction Algorithms

Not yet recruiting

• Conditions: Sepsis
• Interventions: Other: Epic Sepsis Model Version - 1; Other: Epic Sepsis Model Version - 2; Other: Emory Sepsis Model

• Registration Number: NCT05943938
• Lead Sponsor: Emory University

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).

Study Timeline

• Study First Submitted: 2023-07-05
• Study First Submitted QC: 2023-07-05
• Study First Posted: 2023-07-13
• Status Verified: 2025-02
• Last Update Submitted: 2025-02-14
• Last Update Posted: 2025-02-18
• Study Start: 2025-06
• Primary Completion: 2025-12
• Study Completion: 2025-12

Recruitment & Eligibility

• Status: NOT_YET_RECRUITING
• Sex: All
• Target Recruitment: 1200

Inclusion Criteria

• All adult patients admitted through the ED

Exclusion Criteria

• None

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
ED Patients	Emory Sepsis Model	All adult patients presenting to Emergency Departments (ED) in the Emory Healthcare system
ED Patients	Epic Sepsis Model Version - 2	All adult patients presenting to Emergency Departments (ED) in the Emory Healthcare system
ED Patients	Epic Sepsis Model Version - 1	All adult patients presenting to Emergency Departments (ED) in the Emory Healthcare system

Primary Outcome Measures

Name	Time	Method
Patient hospitalization-level area under curve (AUC) for identification of sepsis,	Duration of hospital stay (until discharge or death), an expected average of 30 days	Definition of Sepsis using the Centers for Disease Control and Prevention (CDC) Adult Sepsis Surveillance.

Secondary Outcome Measures

Name	Time	Method
Sensitivity, specificity, and Positive and Negative Predictive Value of algorithms	Duration of hospital stay (until discharge or death), an expected average of 30 days	Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).
Lead time to antibiotic administration	Duration of hospital stay (until discharge or death), an expected average of 30 days	The time between the initial deployment of the alert in patients confirmed to have sepsis (ture positives) and the physician's ordering of intravenous antibiotic therapy.
Number needed to screen	Duration of hospital stay (or death), an expected average of 30 days	The number of alerts that would need to be processed to find one true positive sepsis.
Percent expected increase in unnecessary antibiotics	Duration of hospital stay (until discharge or death), an expected average of 30 days	Percent of patients who were incorrectly identified as having sepsis (false positives), and received antibiotics.
Number of Total and false alert burden	Duration of hospital stay (until discharge or death), an expected average of 30 days	The number of Total and false alert burden cumulative across all study patients over the study period
Time-horizon based AUCs	4 hours, 8 hours, and 24 hours	AUCs will be calculated at 3 pre-specified time horizons.
Accuracy and calibration by subgroup	Duration of hospital stay (until discharge or death), an expected average of 30 days	The AUC and calibration curves will be compared by sex and race to ensure predictive accuracy is equal across subgroups.

Trial Locations

Locations (7)

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