SepsisNCT05943938
Comparison of Sepsis Prediction Algorithms
An observational study of Sepsis, run by Emory University at 7 sites in United States.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Sepsis
- What is being tested?
- Epic Sepsis Model Version - 1, Epic Sepsis Model Version - 2 and Emory Sepsis Model
- How many people
- 1,200 participants
- Where
- 7 sitesUnited States
- Study dates
- 1 Mar 2027to 1 Sep 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: All adult patients admitted through the ED from the time they arrive at the hospital until discharge, death, or initiation of intravenous antibiotics.
Who may be able to join
- All adult patients admitted through the ED
Who cannot join
- None
Trial locations and contacts
7 sites in 1 country. Contact the study team or a site near you to ask about taking part.
7 sites in 1 country
United States7 sites
Emory Midtown Hospital
Atlanta, Georgia, 30308
Sivasubramanium Bhavani, MD, (404) 501-1000, sivasubramanium.bhavani@emory.edu
Emory Saint Joseph's Hospital
Atlanta, Georgia, 30308
Emory Healthcare System
Atlanta, Georgia, 30322
Emory Hospital
Atlanta, Georgia, 30322
Emory Decatur Hospital
Decatur, Georgia, 30033
Sivasubramanium Bhavani, MD, 404-712-2970, sivasubramanium.bhavani@emory.edu
Emory Johns Creek Hospital
Johns Creek, Georgia, 30097
Emory Hillandale Hospital
Lithonia, Georgia, 30058
Sivasubramanium Bhavani, MD, (404) 501-8000, sivasubramanium.bhavani@emory.edu
About this study
Official title: Prospective Evaluation of Sepsis Prediction Algorithms in a Multi-Hospital Healthcare System
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.
Read the 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
- Being tested
- Epic Sepsis Model Version - 1, Epic Sepsis Model Version - 2, Emory Sepsis Model
- Keywords
- Infection, Emergency Department, Algorithm, Prediction
- Medical subject headings
- Sepsis, Infections, Emergencies
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Epic Sepsis Model Version - 1Other
Also called Proprietary Epic sepsis algorithm -1
The Epic Sepsis Model (ESM) version 1, a proprietary sepsis prediction model.
Epic Sepsis Model Version - 2Other
Also called Proprietary Epic sepsis algorithm -2
The Epic Sepsis Model (ESM) version 2, a proprietary sepsis prediction model.
Emory Sepsis ModelOther
Also called Emory Sepsis Algorithm
Emory internal algorithm
| Study group | Role | What they receive |
|---|---|---|
| ED Patients | All adult patients presenting to Emergency Departments (ED) in the Emory Healthcare system Receives: Other: Epic Sepsis Model Version - 1; Other: Epic Sepsis Model Version - 2; Other: Emory Sepsis Model |
What is being measured
The primary outcome is the main question the study is designed to answer.
Patient hospitalization-level area under curve (AUC) for identification of sepsis,
Definition of Sepsis using the Centers for Disease Control and Prevention (CDC) Adult Sepsis Surveillance.
Measured: Duration of hospital stay (until discharge or death), an expected average of 30 days
Secondary outcomes (7)
Sensitivity, specificity, and Positive and Negative Predictive Value of algorithms
Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).
Measured: Duration of hospital stay (until discharge or death), an expected average of 30 days
Lead time to antibiotic administration
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.
Measured: Duration of hospital stay (until discharge or death), an expected average of 30 days
Percent expected increase in unnecessary antibiotics
Percent of patients who were incorrectly identified as having sepsis (false positives), and received antibiotics.
Measured: Duration of hospital stay (until discharge or death), an expected average of 30 days
Number needed to screen
The number of alerts that would need to be processed to find one true positive sepsis.
Measured: Duration of hospital stay (or death), an expected average of 30 days
Number of Total and false alert burden
The number of Total and false alert burden cumulative across all study patients over the study period
Measured: Duration of hospital stay (until discharge or death), an expected average of 30 days
Time-horizon based AUCs
AUCs will be calculated at 3 pre-specified time horizons.
Measured: 4 hours, 8 hours, and 24 hours
Accuracy and calibration by subgroup
The AUC and calibration curves will be compared by sex and race to ensure predictive accuracy is equal across subgroups.
Measured: Duration of hospital stay (until discharge or death), an expected average of 30 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Jul 2023
- Study start1 Mar 2027 (estimated)
- Primary completion1 Sep 2027 (estimated)
- Study completion1 Sep 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for SepsisStudies of the same condition, open and under way.
- More trials run by Emory UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 1,200 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Emory University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Siva Bhavani, Emory University
- Investigators
- Sivasubramanium Bhavani, MD, Principal investigator, Emory University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05943938
- Sponsor's protocol ID
- STUDY00005958
- Other IDs
- 2024P008316
- Status last verified
- Oct 2026
- First submitted
- 5 Jul 2023
- Last updated
- 26 Oct 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: The investigators will share individual participant data that underlie the results reported in an article, after deidentification (text, tables, figures, and appendices).
Study at a glance
From the registry record, last updated by the sponsor on 26 Oct 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Prospective Evaluation of Sepsis Prediction Algorithms in a Multi-Hospital Healthcare System
- ClinicalTrials.gov ID
- NCT05943938
- Acronym / sponsor ID
- STUDY00005958
- Conditions
- Sepsis
- Keywords
- Infection, Emergency Department, Algorithm, Prediction
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 1,200 participants (estimated)
- Lead sponsor
- Emory UniversityUniversity, hospital or other
- Study start
- 1 Mar 2027 (estimated)
- Primary completion
- 1 Sep 2027 (estimated)
- Study completion
- 1 Sep 2027 (estimated)
- First posted
- 13 Jul 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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 design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| ED Patients | – | Other: Epic Sepsis Model Version - 1, Other: Epic Sepsis Model Version - 2, Other: Emory Sepsis ModelAll adult patients presenting to Emergency Departments (ED) in the Emory Healthcare system |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- All adult patients admitted through the ED from the time they arrive at the hospital until discharge, death, or initiation of intravenous antibiotics.
Key inclusion criteria (1 listed)
- All adult patients admitted through the ED
Key exclusion criteria (1 listed)
- None
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Epic Sepsis Model Version - 1Also: Proprietary Epic sepsis algorithm -1The Epic Sepsis Model (ESM) version 1, a proprietary sepsis prediction model. | Other | ED Patients |
| Epic Sepsis Model Version - 2Also: Proprietary Epic sepsis algorithm -2The Epic Sepsis Model (ESM) version 2, a proprietary sepsis prediction model. | Other | ED Patients |
| Emory Sepsis ModelAlso: Emory Sepsis AlgorithmEmory internal algorithm | Other | ED Patients |
Primary outcome
Patient hospitalization-level area under curve (AUC) for identification of sepsis,
Time frame: 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.
7 secondary outcomes
Sensitivity, specificity, and Positive and Negative Predictive Value of algorithms
Time frame: Duration of hospital stay (until discharge or death), an expected average of 30 days
Lead time to antibiotic administration
Time frame: Duration of hospital stay (until discharge or death), an expected average of 30 days
Percent expected increase in unnecessary antibiotics
Time frame: Duration of hospital stay (until discharge or death), an expected average of 30 days
Number needed to screen
Time frame: Duration of hospital stay (or death), an expected average of 30 days
Number of Total and false alert burden
Time frame: Duration of hospital stay (until discharge or death), an expected average of 30 days
Time-horizon based AUCs
Time frame: 4 hours, 8 hours, and 24 hours
Accuracy and calibration by subgroup
Time frame: Duration of hospital stay (until discharge or death), an expected average of 30 days
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 26 Oct 2026.
- Individual participant dataSharing planned: Yes. The investigators will share individual participant data that underlie the results reported in an article, after deidentification (text, tables, figures, and appendices).
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Sivasubramanium Bhavani, MD principal investigator
Emory University
7 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Sepsis, run by Emory University at 7 sites in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 26 Oct 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 7 sites in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Sivasubramanium Bhavani, MD (404-712-2970, sivasubramanium.bhavani@emory.edu), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Patient hospitalization-level area under curve (AUC) for identification of sepsis, (time frame: Duration of hospital stay (until discharge or death), an expected average of 30 days). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 26 Oct 2026.