We are evaluating and refining the VExUS score as a bedside tool for quantifying venous congestion in critically ill patients. Our work focuses on its physiological underpinnings, its reliability across different haemodynamic states, and its potential to guide fluid management and decongestive therapy in shock, right heart failure, and during mechanical circulatory support.

We are evaluating the use of percutaneous microaxial left ventricular assist devices and how they effect ventricular interdependence during mechanical circulatory support. By selectively unloading the left ventricle, these devices alter septal position, right ventricular geometry, and biventricular filling, uniquely impacting how the two ventricles interact. Our work investigates how these interactions shape right ventricular performance, with the goal of better predicting and managing right heart failure during left-sided support.

In cardiogenic shock and cardiac arrest, VA-ECMO can be life-saving but introduces complex loading conditions on the heart and lungs. We investigate left ventricular unloading, right ventricular–pulmonary vascular coupling, and harlequin/north-south physiology, and we develop monitoring strategies and computational models to support decisions on initiation, titration, and weaning.

For patients with severe respiratory failure, we study how VV-ECMO interacts with native lung function, ventilation strategy, and right ventricular performance. Our research targets optimised gas exchange management, lung-protective ventilation during support, and monitoring tools that help clinicians titrate flows, sweep gas, and weaning more rationally.

Mechanical ventilation supports not only the lungs, but also venous return, right ventricular afterload, and cardiac output. We investigate heart-lung interactions during controlled and assisted ventilation, with the aim of developing integrated cardiopulmonary strategies that protect both organs simultaneously, particularly in patients requiring circulatory support.

This project will develop a computational model of the heart that realistically captures the haemodynamic effects of cardiac assist devices used in clinical practice (e.g. microaxial pumps, VA-ECMO). The student will work at the interface of cardiovascular physiology and computational modelling, building and validating a simulation platform that can be used to explore device-heart interactions, test new monitoring strategies, and predict patient responses before clinical implementation. 

This project investigates how pulmonary infection develops and how it shapes clinical outcomes and treatment decisions. The work focuses on the development of a computational model that links infection risk, host response, and treatment effects.