SepsisNCT05826223
Novel Sepsis Sub-phenotypes Based on Trajectories of Vital Signs
An observational study of Sepsis, run by Emory University at 4 sites in United States.
Trial summary
Sepsis is a dysregulated host response to infection resulting in organ dysfunction. Over the past three decades, more than 30 pharmacological therapies have been tested in >100 clinical trials and have failed to show consistent benefit in the overall population of patients with sepsis. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Sepsis
- What is being tested?
- Implementation and evaluation of a sepsis sub-phenotyping algorithm
- How many people
- 1,916 participants
- Where
- 4 sitesUnited States
- Study dates
- 18 Sep 2025to 14 Jan 2026
- Phase
- Observational
- Are there results?
- None posted in the registry
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 who present to the emergency department at the participating facilities will automatically be enrolled in the study until the enrollment target for the study is met. All patients will be classified into subphenotypes using the algorithm, but the subgroup that will be analyzed will be patients with suspected infection.
Who may be able to join
- All adults who present to the emergency department
Who cannot join
- None
Trial locations and contacts
4 sites in 1 country.
United States4 sites
Emory Hospital Midtown
Atlanta, Georgia, 30308
Emory Saint Joseph's Hospital
Atlanta, Georgia, 30308
Emory University Hospital
Atlanta, Georgia, 30322
Emory Johns Creek Hospital
Johns Creek, Georgia, 30097
About this study
Official title: Implementation and Prospective Validation of a Sepsis Sub-phenotyping Algorithm Based on Vital Sign Trajectories
Sepsis is a dysregulated host response to infection resulting in organ dysfunction. Over the past three decades, more than 30 pharmacological therapies have been tested in >100 clinical trials and have failed to show consistent benefit in the overall population of patients with sepsis. The one-size-fits-all approach has not worked. This has resulted in a shift in research towards identifying sepsis subphenotypes through unsupervised learning. The ultimate objective is to identify sepsis subphenotypes with different responses to therapies, which could provide a path towards the precision medicine approach to sepsis.
The investigators have previously discovered sepsis subphenotypes in retrospective data using trajectories of vital signs in the first 8 hours of hospitalization. The team aims to prospectively classify adult hospitalized patients into these subphenotypes in a prospective, observational study. This will be done through the implementation of an electronic health record integrated application that will use vital signs from hospitalized patients to classify the patients into one of four subphenotypes. This study will continue until 1,200 patients with infection are classified into the sepsis subphenotypes. The classification of the patients is only performed to validate the association of the subphenotypes with clinical outcomes as was shown in retrospective studies. Physicians and providers treating the patients will not see the classification, and the algorithm classifying the patients will in no way affect the care of the patients. Further, all the data needed for the algorithm (vital signs from the first 8 hours) are standard of care, and enrollment in the prospective study does not require any additional data.
Read the detailed description
The primary goal of this study is to investigate the feasibility of implementing a prospective sepsis subphenotyping tool in the electronic health record and evaluating the characteristics and outcomes of the sepsis subphenotypes. During this study, clinicians will not see the results of the algorithm or have access to its predictions. Instead, the algorithm will run silently in the background and continuously compute the subphenotypes of patients who are presenting to the emergency department (ED). For each patient, the probability of subphenotype membership over the first 8 hours of presentation to the ED will be calculated using an algorithm previously validated on retrospective data. Differences in clinical characteristics and outcomes between the subphenotypes will be compared. Investigators will seek to classify 1,200 patients with suspected infections. Since it will not be apparent on ED presentation who has suspected infection, all patients will be classified into subphenotypes using the algorithm, but the primary subgroup who will be analyzed will be patients with suspected infection.
- Conditions
- Sepsis
- Being tested
- Implementation and evaluation of a sepsis sub-phenotyping algorithm
- Keywords
- phenotypes, sub-phenotypes, infection, vital signs, subphenotypes
- Medical subject headings
- Sepsis, Infections
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Implementation and evaluation of a sepsis sub-phenotyping algorithmOther
The algorithm will run silently in the background and continuously compute the subphenotypes of patients who are presenting to the emergency department (ED) with suspected infection.
What is being measured
The primary outcome is the main question the study is designed to answer.
In-hospital mortality
Comparison of 30 day in-hospital mortality rate between the 4 subphenotypes.
Measured: Up to 30 days
Secondary outcomes (7)
Renal replacement therapy (RRT)
Proportion of patients requiring (RRT) during hospital admission.
Measured: Through study completion, on average 30 days
Mechanical ventilation
Proportion of patients requiring mechanical ventilation during hospital admission.
Measured: Through study completion, on average 30 days
Vasopressor use
Proportion of patients requiring vasopressor use during hospital admission.
Measured: Through study completion, on average 30 days
Inotrope use
Proportion of patients requiring inotrope use during hospital admission.
Measured: Through study completion, on average 30 days
Admission to the intensive care unit (ICU)
Proportion of patients requiring admission to ICU during hospital admission.
Measured: Through study completion, on average 30 days
Hospital Length of stay
Duration of hospital length (from arrival to ED until hospital discharge) of stay in days.
Measured: Through study completion, on average 30 days
Response to Balanced Crystalloids vs Normal Saline
Within each subphenotype, the mortality rate will be compared between patients who received at least 2 liters in 24 hours of balanced crystalloids and patients who received normal saline. This is to evaluate the replicability of the finding of a significant mortality benefit from balanced crystalloids in Group D.
Measured: 24 hours
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Apr 2023
- Study start18 Sep 2025
- Primary completion14 Jan 2026
- Study completion14 Jan 2026
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- 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
- 1,916 participants (actual)
Sponsor and investigators
- Lead sponsor
- Emory University
- Sponsor type
- University, hospital or other
- Collaborators
- National Institute of General Medical Sciences (NIGMS)
- Responsible party
- Principal investigator, Siva Bhavani, Emory University
- Investigators
- Sivasubramanium Bhavani, MD, Principal investigator, Emory University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05826223
- Sponsor's protocol ID
- STUDY00004970
- Other IDs
- 5K23GM144867-02, 2022P004808
- Status last verified
- Feb 2026
- First submitted
- 12 Apr 2023
- Last updated
- 23 Feb 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Bhavani SV, Semler M, Qian ET, Verhoef PA, Robichaux C, Churpek MM, Coopersmith CM. Development and validation of novel sepsis subphenotypes using trajectories of vital signs. Intensive Care Med. 2022 Nov;48(11):1582-1592. doi: 10.1007/s00134-022-06890-z. Epub 2022 Sep 24.
PubMed 36152041
Study at a glance
From the registry record, last updated by the sponsor on 23 Feb 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Implementation and Prospective Validation of a Sepsis Sub-phenotyping Algorithm Based on Vital Sign Trajectories
- ClinicalTrials.gov ID
- NCT05826223
- Acronym / sponsor ID
- STUDY00004970
- Conditions
- Sepsis
- Keywords
- phenotypes, sub-phenotypes, infection, vital signs, subphenotypes
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 1,916 participants (actual)
- Lead sponsor
- Emory UniversityUniversity, hospital or other
- Collaborators
- National Institute of General Medical Sciences (NIGMS)
- Study start
- 18 Sep 2025 (actual)
- Primary completion
- 14 Jan 2026 (actual)
- Study completion
- 14 Jan 2026 (actual)
- First posted
- 24 Apr 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 dysregulated host response to infection resulting in organ dysfunction. Over the past three decades, more than 30 pharmacological therapies have been tested in >100 clinical trials and have failed to show consistent benefit in the overall population of patients with sepsis. The one-size-fits-all approach has not worked. This has resulted in a shift in research towards identifying sepsis subphenotypes through unsupervised learning. The ultimate objective is to identify sepsis subphenotypes with different responses to therapies, which could provide a path towards the precision medicine approach to sepsis.
The investigators have previously discovered sepsis subphenotypes in retrospective data using trajectories of vital signs in the first 8 hours of hospitalization. The team aims to prospectively classify adult hospitalized patients into these subphenotypes in a prospective, observational study. This will be done through the implementation of an electronic health record integrated application that will use vital signs from hospitalized patients to classify the patients into one of four subphenotypes. This study will continue until 1,200 patients with infection are classified into the sepsis subphenotypes. The classification of the patients is only performed to validate the association of the subphenotypes with clinical outcomes as was shown in retrospective studies. Physicians and providers treating the patients will not see the classification, and the algorithm classifying the patients will in no way affect the care of the patients. Further, all the data needed for the algorithm (vital signs from the first 8 hours) are standard of care, and enrollment in the prospective study does not require any additional data.
Detailed description
The primary goal of this study is to investigate the feasibility of implementing a prospective sepsis subphenotyping tool in the electronic health record and evaluating the characteristics and outcomes of the sepsis subphenotypes. During this study, clinicians will not see the results of the algorithm or have access to its predictions. Instead, the algorithm will run silently in the background and continuously compute the subphenotypes of patients who are presenting to the emergency department (ED). For each patient, the probability of subphenotype membership over the first 8 hours of presentation to the ED will be calculated using an algorithm previously validated on retrospective data. Differences in clinical characteristics and outcomes between the subphenotypes will be compared. Investigators will seek to classify 1,200 patients with suspected infections. Since it will not be apparent on ED presentation who has suspected infection, all patients will be classified into subphenotypes using the algorithm, but the primary subgroup who will be analyzed will be patients with suspected infection.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- All adult patients who present to the emergency department at the participating facilities will automatically be enrolled in the study until the enrollment target for the study is met. All patients will be classified into subphenotypes using the algorithm, but the subgroup that will be analyzed will be patients with suspected infection.
Key inclusion criteria (1 listed)
- All adults who present to the emergency department
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 |
|---|---|---|
| Implementation and evaluation of a sepsis sub-phenotyping algorithmThe algorithm will run silently in the background and continuously compute the subphenotypes of patients who are presenting to the emergency department (ED) with suspected infection. | Other | – |
Primary outcome
In-hospital mortality
Time frame: Up to 30 days
Comparison of 30 day in-hospital mortality rate between the 4 subphenotypes.
7 secondary outcomes
Renal replacement therapy (RRT)
Time frame: Through study completion, on average 30 days
Mechanical ventilation
Time frame: Through study completion, on average 30 days
Vasopressor use
Time frame: Through study completion, on average 30 days
Inotrope use
Time frame: Through study completion, on average 30 days
Admission to the intensive care unit (ICU)
Time frame: Through study completion, on average 30 days
Hospital Length of stay
Time frame: Through study completion, on average 30 days
Response to Balanced Crystalloids vs Normal Saline
Time frame: 24 hours
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 23 Feb 2026.
- Results publication: PubMed 36152041Bhavani SV, Semler M, Qian ET, Verhoef PA, Robichaux C, Churpek MM, Coopersmith CM. Development and validation of novel sepsis subphenotypes using trajectories of vital signs. Intensive Care Med. 2022 Nov;48(11):1582-1592. doi: 10.1007/s00134-022-06890-z. Epub 2022 Sep 24.
- Individual participant dataSharing planned: No
Related trials for Sepsis
Not yet recruitingPhase 2/3
A Pivotal Safety and Immunogenicity GBS-NN/NN2 Vaccine Maternal Immunisation Trial
Streptococcus Agalactiae Infection, Neonatal Sepsis
Active, not recruiting
CT for Personalized Mechanical Ventilation
Ventilator-Induced Lung Injury, Sepsis Syndrome
RecruitingPhase 4
A Study to Compare the Efficacy and Safety of Extended and Intermittent Infusion of Beta-lactams in Critically Ill Paediatric Patients
Infection, Sepsis
Not yet recruiting
Double Plasma Separation and Adsorption in Acute-on-Chronic Liver Failure (DPMAS-ACLF Trial)
Acute-on-Chronic Liver Failure (ACLF)
Active, not recruitingPhase 4
Thymosin Alpha 1 and IgM Levels in Sepsis
Sepsis, Septic Shock
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. This study is not recruiting at the moment.
Sivasubramanium Bhavani, MD principal investigator
Emory University
4 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 4 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: finished, as of the sponsor's last update on 23 Feb 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 4 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
In-hospital mortality (time frame: Up to 30 days). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05826223, which also lists 1 linked publication.
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 23 Feb 2026.