Most people in the general population remain healthy throughout life. However, some individuals develop illnesses-often mild-while a smaller proportion experience severe conditions requiring hospitalisation or even admission to an intensive care unit (ICU). Although many patients recover and regain good health, others experience relapses, develop new health problems, or require hospital readmission. In more serious cases, these complications can lead to death. These patterns raise fundamental questions that warrant further research: Why do some otherwise healthy individuals develop critical illnesses while others do not? Why do outcomes differ among patients with similar conditions? And, crucially, can these adverse outcomes be predicted or prevented-and if so, when and how should we intervene?
This project aims to identify factors associated with an increased risk of developing critical illness in the general population and with poorer outcomes among affected individuals, as well as to determine when these risks are greatest. By addressing these questions, it seeks to provide insights into who is most at risk, when risks peak, and how timely interventions might prevent disease progression or adverse outcomes.
Focusing on critical illnesses such as stroke, myocardial infarction, pulmonary embolism, organ failure, severe infection, and ICU admission, the project will leverage the UK Biobank’s comprehensive, longitudinal, multisource health data to conduct advanced epidemiological analyses (e.g., trajectory modelling, time-to-event analyses, and causal machine learning). By mapping health trajectories and identifying high-risk groups, the research will inform strategies for early detection, prevention, and improved long-term recovery after critical illness.