SepsisPRISMNCT06238180
Personalised Real-time Interoperable Sepsis Monitoring (PRISM)
An observational study of Sepsis and Abdominal Sepsis, run by Aisthesis Medical P.C. at 1 site in Greece.
Trial summary
The goal of this prospective observational study is to develop and utilize an Artificial Intelligence (AI) model for the prediction of postoperative sepsis in patients undergoing abdominal surgery. The main questions it aims to answer are: 1. Read more about this study
- Who is it for?
- Ages 18 to 120 years
- Conditions the study is for
- Sepsis, Abdominal Sepsis, Infections
- What is being tested?
- PRISM Tool
- Type of treatment
- Medical device
- How many people
- 0 participants
- Where
- 1 siteGreece
- Study dates
- 29 Nov 2023to 30 Jun 2024
- 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 to 120 years
- All sexes
- Adult, Older adult
Study population: The study population for the observational study on sepsis prediction are postoperative abdominal surgery patients >18 years of age, selected from a hospital setting, specifically targeting patients admitted for abdominal surgery. This includes a diverse demographic of adult patients undergoing various types of abdominal surgeries. The selection will focus on ensuring a representative sample of this patient group to accurately assess the efficacy and applicability of the AI-driven sepsis prediction system in a real-world clinical environment.
Who may be able to join
- Patients undergoing elective abdominal surgery.
- Postoperative admission to the surgical ward.
- Age 18 years or older, who are able and willing to participate and have given written consent.
- On admission, the primary investigator assess their risk to deteriorate during the first 72 hours after admission as reasonably high.
Who cannot join
- <18 years of age Known allergy or contraindication to the monitoring devices.
- Pre-existing conditions that could interfere with the study (e.g., chronic sepsis, immunodeficiency disorders).
- Day case surgery.
- Pregnancy.
- Immediate transfer to ICU postoperatively.
- Patient refusal or unable to give written consent.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Prediction of Sepsis in Patients Undergoing Abdominal Surgery: A Prospective, Observational Clinical Study
The goal of this prospective observational study is to develop and utilize an Artificial Intelligence (AI) model for the prediction of postoperative sepsis in patients undergoing abdominal surgery. The main questions it aims to answer are:
- Can a remote AI-driven monitoring system accurately predict sepsis risk in postoperative patients?
- How effectively can this system integrate and analyze multimodal data for early sepsis detection in the surgical ward?
Participants are equipped with non-invasive PPG-based wearable devices to continuously monitor vital signs and collect high-quality clinical data. This data, along with demographic and laboratory information from the Electronic Health Record (EHR) of the hospital, are used for AI model development and validation.
- Being tested
- PRISM Tool
- Keywords
- sepsis, surgical ward, artificial intelligence, decision-support, continuous monitoring, wearable devices
- Medical subject headings
- Sepsis, Intraabdominal Infections, Infections, Clinical Deterioration
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
PRISM ToolDevice
The intervention in this study involves an AI-driven clinical decision-support system, PRISM Tool, designed for the early prediction of sepsis in patients undergoing abdominal surgery. PRISM Tool integrates data from PPG-based wearable wireless devices that monitor vital signs, electronic health records, and laboratory tests. The AI model analyzes this multimodal data to proactively identify signs of sepsis providing an early warning score to clinicians. The distinguishing feature of this intervention is its use of real-time data and advanced AI analytics to enhance early sepsis detection, aiming to improve patient outcomes in postoperative care.
What is being measured
The primary outcome is the main question the study is designed to answer.
Accuracy of AI-Driven Sepsis Prediction in Postoperative Period
This primary outcome measure evaluates the accuracy of an AI-driven monitoring system in predicting postoperative sepsis among patients undergoing abdominal surgery. The measure focuses on the system's ability to correctly identify sepsis, considering sensitivity, specificity, and predictive values.
Measured: The accuracy of sepsis prediction will be assessed from the day of surgery, assessed daily for up to 7 days post-surgery or until hospital discharge.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted2 Feb 2024
- Study start29 Nov 2023 (estimated)
- Primary completion30 Jun 2024 (estimated)
- Study completion30 Jun 2024 (estimated)
Why it stopped: Data collection issues.
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.
- 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
- 0 participants (actual)
Sponsor and investigators
- Lead sponsor
- Aisthesis Medical P.C.
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- Larissa University Hospital, Technical University of Crete
- Responsible party
- Sponsor
- Investigators
- Eleni Arnaoutoglou, MD, PhD, Study chair, Larissa University Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06238180
- Sponsor's protocol ID
- 27681/13-06-23
- Acronym
- PRISM
- Status last verified
- Apr 2026
- First submitted
- 18 Jan 2024
- Last updated
- 9 Apr 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 9 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Prediction of Sepsis in Patients Undergoing Abdominal Surgery: A Prospective, Observational Clinical Study
- ClinicalTrials.gov ID
- NCT06238180
- Acronym / sponsor ID
- PRISM / 27681/13-06-23
- Keywords
- sepsis, surgical ward, artificial intelligence, decision-support, continuous monitoring, wearable devices
- Study type
- Observational
- Recruitment status
- WithdrawnReason stopped: Data collection issues.
- Enrolment
- 0 participants (actual)
- Lead sponsor
- Aisthesis Medical P.C.Industry (pharma, biotech, devices)
- Collaborators
- Larissa University Hospital, Technical University of Crete
- Study start
- 29 Nov 2023 (estimated)
- Primary completion
- 30 Jun 2024 (estimated)
- Study completion
- 30 Jun 2024 (estimated)
- First posted
- 2 Feb 2024 (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.
The goal of this prospective observational study is to develop and utilize an Artificial Intelligence (AI) model for the prediction of postoperative sepsis in patients undergoing abdominal surgery. The main questions it aims to answer are:
- Can a remote AI-driven monitoring system accurately predict sepsis risk in postoperative patients?
- How effectively can this system integrate and analyze multimodal data for early sepsis detection in the surgical ward?
Participants are equipped with non-invasive PPG-based wearable devices to continuously monitor vital signs and collect high-quality clinical data. This data, along with demographic and laboratory information from the Electronic Health Record (EHR) of the hospital, are used for AI model development and validation.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 to 120 years
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- The study population for the observational study on sepsis prediction are postoperative abdominal surgery patients >18 years of age, selected from a hospital setting, specifically targeting patients admitted for abdominal surgery. This includes a diverse demographic of adult patients undergoing various types of abdominal surgeries. The selection will focus on ensuring a representative sample of this patient group to accurately assess the efficacy and applicability of the AI-driven sepsis prediction system in a real-world clinical environment.
Key inclusion criteria (4 listed)
- Patients undergoing elective abdominal surgery.
- Postoperative admission to the surgical ward.
- Age 18 years or older, who are able and willing to participate and have given written consent.
- On admission, the primary investigator assess their risk to deteriorate during the first 72 hours after admission as reasonably high.
Key exclusion criteria (6 listed)
- <18 years of age Known allergy or contraindication to the monitoring devices.
- Pre-existing conditions that could interfere with the study (e.g., chronic sepsis, immunodeficiency disorders).
- Day case surgery.
- Pregnancy.
- Immediate transfer to ICU postoperatively.
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 |
|---|---|---|
| PRISM ToolThe intervention in this study involves an AI-driven clinical decision-support system, PRISM Tool, designed for the early prediction of sepsis in patients undergoing abdominal surgery. PRISM Tool integrates data from PPG-based wearable wireless devices that monitor vital signs, electronic health records, and laboratory tests. The AI model analyzes this multimodal data to proactively identify signs of sepsis providing an early warning score to clinicians. The distinguishing feature of this intervention is its use of real-time data and advanced AI analytics to enhance early sepsis detection, aiming to improve patient outcomes in postoperative care. | Device | – |
Primary outcome
Accuracy of AI-Driven Sepsis Prediction in Postoperative Period
Time frame: The accuracy of sepsis prediction will be assessed from the day of surgery, assessed daily for up to 7 days post-surgery or until hospital discharge.
This primary outcome measure evaluates the accuracy of an AI-driven monitoring system in predicting postoperative sepsis among patients undergoing abdominal surgery. The measure focuses on the system's ability to correctly identify sepsis, considering sensitivity, specificity, and predictive values.
Results and safety
The study was withdrawn before enrolling participants, so there are no results.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 9 Apr 2026.
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.
Eleni Arnaoutoglou, MD, PhD study chair
Larissa University Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Sepsis and Abdominal Sepsis, run by Aisthesis Medical P.C. at 1 site in Greece.
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 4 inclusion and 6 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: withdrawn, as of the sponsor's last update on 9 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Greece. 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 was withdrawn before enrolling participants, so there are no results.
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?
Accuracy of AI-Driven Sepsis Prediction in Postoperative Period (time frame: The accuracy of sepsis prediction will be assessed from the day of surgery, assessed daily for up to 7 days post-surgery or until hospital discharge.). 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 9 Apr 2026.