Clinical Research Directory

Personalised Real-time Interoperable Sepsis Monitoring (PRISM)

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.

Characterization of Abdomino-pelvic Lesions by 18Fluorine- Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography

The aim of the study is to identify and characterize lesions in the abdominopelvic region detected by 18fluorine- fluorodeoxyglucose (FDG) positron Emission Tomography combined Computed Tomography (PET/CT) scan, including determining their malignant or benign nature, and to determine the extent of disease to facilitate proper management

OXiris for Abdominal SEptic Shock (OASES Study)

This study innovatively utilizes multi-modal hemodynamic monitoring (Norepinephrine equivalence, NEE+Pulse indicator Continuous Cariac output, PiCCO) to investigate the optimal timing of initiation of oXiris in abdominal infection-associated septic shock patients and to investigate prognosis on sepsis phenotypes undergoing oXiris therapy.