Personalised Real-time Interoperable Sepsis Monitoring (PRISM)

Aisthesis Medical P.C.55 enrolled

Overview

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. Can a remote AI-driven monitoring system accurately predict sepsis risk in postoperative patients? 2. 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 Type

OBSERVATIONAL

Enrollment

Conditions

Sepsis Abdominal Sepsis Infections Clinical Deterioration Hemodynamic Instability

Interventions

The intervention in this study involves an AI-driven clinical decision-support system, VIOSync Sepsis Prediction Index (SPI), designed for the early prediction of sepsis in patients undergoing abdominal surgery. VIOSync 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, the SPI, 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.

Eligibility

Sex: ALLMin age: 18 YearsMax age: 120 Years

Medical Language ↔ Plain English

Inclusion Criteria: * 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. Exclusion Criteria: * \<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.

Outcomes

Primary Outcomes

Accuracy of AI-Driven Sepsis Prediction in Postoperative Period

This primary outcome measure evaluates the accuracy of the AI-driven monitoring system, VIOSync SPI, 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.

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.