Multimorbidity clusters for patients with MI

It is now common to survive over a decade after the diagnosis of myocardial infarction (MI). This has resulted in a growing population with multiple chronic diseases. We used latent class analyses of 693,388 patients with myocardial infarction and up to 7 co-morbidities. We discovered a highly multi-morbid cluster of MI patients with concomitant heart failure, peripheral vascular disease and hypertension. Patients were more often female and less likely to receive guideline-recommended care including aspirin and beta-blockers compared with the low multi-morbidity cluster. The multi-morbidity phenotypes had a significant differential impact on survivorship trajectories over and above the impact of age, sex, individual co-morbidities and treatment, such that highly multi-morbid patients were 2.4 times more likely to die and had a reduced life expectancy by up to 3 years. The findings were published in PLOS Medicine (2018) and the associated press release can be viewed here.

Data phenotyping longitudinal multimorbidity trajectories in cardiovascular disease: a statistical machine learning approach using nationwide electronic healthcare record

This programme of work pools expertise in the analyses of large scale electronic healthcare record (EHR) data, clinical cardiovascular epidemiology and statistical machine learning to investigate the longitudinal multimorbidity trajectories following MI and the develop the required methodologies to underpin this. The work is led by Dr Hall at the University of Leeds, in collaboration with Professor Niels Peek (University of Manchester), Professor Ronan Lyons (University of Swansea), Professor Chris Holmes (University of Oxford) and Professor Chis Gale (University of Leeds). The work is funded through the AI for Science and Government fund via the Alan Turing Institute Health Programme. April 2020 - March 2023. £303,744 (PI: M Hall).

Healthcare utilisation and clinical outcomes among survivors of acute myocardial infarction: a national electronic health records cohort study

This personal fellowship supports Dr Marlous Hall’s research into healthcare utilization and clinical outcomes among survivors of acute myocardial infarction - in particular, the work focusses on the role of concomitant disease and multimorbidity on individual survivorship trajectories. The fellowship is funded through a Sir Henry Wellcome Fellowship awarded by the Wellcome Trust. Sep 2017 - March 2022, £270,336 (PI: M Hall).

VICORI - The Virtual cardio-oncology Research Initiative

This study led by Dr David Adlam, University of Leicester and Dr Michael Peake, Public Health England and is a collaborative initiative with the University of Leeds (Hall: Statistical co-lead & CP Gale: work package lead) and national cancer and cardiovascular audit network in order to link national electronic health records for the high resolution investigation of the interplay between cancer and cardiovascular disease. This programme of work is jointly funded by Cancer Research UK and the British Heart Foundation £1.4 million. 2016-2021.