University of Edinburgh

Edinburgh Clinical Academic Track

DL_2023_059

Patient groups in intensive care units (ICUs) exhibit considerable diversity in terms of their health conditions and demographic profiles. This variance has been inadequately addressed, leading to a notable disparity in applying scientific findings to practical care. Elements contributing to critical illness include pre-disposing factors, such as multimorbidity, polypharmacy, and frailty, and precipitating factors such as diagnosis and illness severity. The complex interplay of these factors in determining patient trajectories and outcomes is poorly understood. The first aim of the project will be to bring together healthcare datasets to understand the scale of the multimorbidity burden in the critical care population, alongside other pre-disposing and precipitating factors. I will aim to derive distinct patient clusters and explore the relationships between these clusters and patterns of multiple organ dysfunction and outcomes including early and late mortality, care-transitions and hospital readmission. This will help elucidate mechanistic pathways and identify targets for tailored interventions. The second aim will be to use prediction modelling and causal inference techniques, such as target trial emulation, to identify and explore customised treatments within the different patient clusters identified that can lead to improved outcomes.

Patients developing critical illness have a complex interplay of pre-disposing factors, such as multimorbidity, polypharmacy and frailty, and precipitating factors such as diagnosis and illness severity. The interplay of these factors in determining response to treatments and outcomes is poorly understood. Multimorbidity is poorly characterised in ICU, and estimates range from 13-54%. By bringing together healthcare datasets, we will understand the scale of the multimorbidity burden in the critical care population, and the challenges it poses to the healthcare system. In parallel, patients in ICU rarely experience single organ dysfunction, and predisposing and precipitating risk factors in the patient’s journey result in multi-organ dysfunction. Pre-existing organ dysfunction is a risk factor for deterioration in acute/critical illness. Ongoing time-varying factors, such as organ support and treatment, challenge analytical techniques or have lacked high-quality longitudinal data, and have historically not been included in analyses. If we move from a construct of syndromes towards discriminating discrete disease states at presentation and exploring subsequent patterns of biomarkers and physiological derangement reflecting end-organ dysfunction then we will discover more about underlying mechanisms, providing opportunities for early targeted interventions.

Public Health Research

07/05/2024

De-Personalised

TRE