Host susceptibility, long-term conditions and recovery heterogeneity after critical illness: mechanisms underlying divergent long-term trajectories
Supervisors:
Dr David M Griffith, Usher Institute (Centre for Population Health Sciences), University of Edinburgh
Prof Nazir Lone, Usher Institute (School of Population Health Sciences), University of Edinburgh
Prof Kenneth Baillie, Centre for Inflammation Research / Pandemic Science Hub, University of Edinburgh
Summary:
Critically ill patients with apparently similar pre-existing comorbidity burden and acute illness severity frequently experience markedly different long-term outcomes. Some recover rapidly, whereas others develop recurrent hospitalisation, frailty, ICU-acquired weakness, chronic critical illness or accelerated mortality. This project will investigate how underlying biological susceptibility and resilience contribute to these divergent recovery trajectories, using genomics and causal inference to look for modifiable underlying biological mechanisms.
Using linked national healthcare datasets, ICU databases and the GenOMICC study (n=43,739), the project will work with patients, clinicians and researchers to define clinically meaningful recovery trajectories following critical illness. The project will then develop and validate computable routine-data phenotypes capable of identifying these trajectories at population scale, before completing genome-wide analyses to identify mechanistic drivers.
The project will particularly focus on ICU-acquired weakness, healthcare dependency and progression towards adverse multiple long-term condition trajectories following critical illness.
The student will receive interdisciplinary training spanning epidemiology, genomics and data science within an established MLTC research environment.