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Not Yet RecruitingNCT05943938

Comparison of Sepsis Prediction Algorithms

Prospective Evaluation of Sepsis Prediction Algorithms in a Multi-Hospital Healthcare System

Status
Not Yet Recruiting
Phase
Study type
Observational
Enrollment
1,200 (estimated)
Sponsor
Emory University · Academic / Other
Sex
All
Age
18 Years
Healthy volunteers
Not accepted

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

Interventions

TypeNameDescription
OTHEREpic Sepsis Model Version - 1The Epic Sepsis Model (ESM) version 1, a proprietary sepsis prediction model.
OTHEREpic Sepsis Model Version - 2The Epic Sepsis Model (ESM) version 2, a proprietary sepsis prediction model.
OTHEREmory Sepsis ModelEmory internal algorithm

Timeline

Start date
2026-06-01
Primary completion
2026-12-01
Completion
2026-12-01
First posted
2023-07-13
Last updated
2026-01-07

Locations

7 sites across 1 country: United States

Source: ClinicalTrials.gov record NCT05943938. Inclusion in this directory is not an endorsement.