Dr Rose Crowley, University of Melbourne, Baker Department of Cardiometabolic Health, VIC.

The Project:

A program of yoga in a randomised control study in people with Atrial Fibrillation.

Synopsis:

The yoga AF study will investigate if a program of regular yoga helps to reduce atrial fibrillation (AF). The study will enrol 244 people with atrial fibrillation who are undergoing a rhythm control management strategy. Participants will be randomised 1: 1 to a 12-month yoga program or standard care.

The primary aims of the study are to assess if a yoga program reduces 1. AF episodes and 2 AF burden. Secondary endpoints include impact on patient reported quality of life, and healthcare utilisation. Possible mechanisms by which yoga may reduce AF will be explored through assessment of cardiopulmonary fitness, autonomic function, blood pressure, weight and cardiac structure and function.

Dr Hari Sritharan, University of Sydney, NSW

The Project:

Clinical translation of machine learning & advanced predictive analytics in cardiovascular disease. 

Synopsis:

Cardiovascular disease (CVD) is a leading cause of mortality and morbidity worldwide, imposing an enormous burden on healthcare systems and public health. Given the significant impact of CVD, there is an urgent need for more accurate risk prediction models to identify high-risk individual, enabling early intervention and tailored preventive strategies. Machine learning (ML), a subset of artificial intelligence, has emerged as a powerful tool in healthcare research, holding the potential to revolutionise CVD risk assessment by harnessing the vast amount of clinical and demographic data available.

The existing risk prediction models for CVD are based on traditional statistical approaches and tend to have limitations in terms of accuracy, especially for individualised predictions. ML algorithms, including deep learning and ensemble methods, offer an opportunity to improve the precision and personalisation of CVD risk assessment. My project delves into the development, application and clinical translation of ML-based risk prediction algorithms and advanced predictive analytics to enhance the management of five critical cardiovascular conditions: ST-elevation myocardial infarction (STEMI), severe aortic stenosis (AS), severe tricuspid regurgitation, atrial fibrillation (AF), and COVID-19-associated cardiovascular outcomes.

The aim is to leverage the power of artificial intelligence and predictive modelling to optimise patient care and improve clinical decision-making in the complex landscape of cardiovascular medicine.

Dr Stephanie Rowe, cardiologist at the Baker Heart and Diabetes Institute, VIC.

The Project:

Cardiac remodelling and exercise capacity: Clinical and genetic predictors of low exercise capacity and atrial fibrillation.

Synopsis:

The interaction between physical activity, our genome and cardiac structure is complex. Emerging evidence suggests functional capacity and cardiac size play a critical role in the development of heart failure and atrial fibrillation – both key causes of illness and health expenditure. Extremes of activity, from a sedentary lifestyle to endurance athletes, can impact heart structure and function and risk of arrhythmias. The sedentary end of the spectrum is associated with smaller stiffer hearts, poor exercise capacity and cardiovascular risk factors including type 2 diabetes and obesity. Through in-depth assessment of clinical, imaging and genetic factors that influence low exercise capacity and atrial fibrillation, this research project aims to identify novel and simple ways to detect people in this high risk population. Using the largest and most comprehensive cohort of cardiac, exercise and genetic metrics world-wide, we will also develop an understanding of the interaction between physical activity, cardiac structure and genetics by assessing how a person’s genetic signature impacts the heart’s ability to remodel in response to exercise.

Our aim is to identify and better understand clinical and genetic predictors of low exercise capacity and atrial fibrillation. Our hypothesis is that small cardiac size can be used to identify people with poor exercise capacity due to reduced cardiac reserve and that polygenic risk scores can predict those who are genetically primed to have low exercise capacity and atrial fibrillation.

Aim 1: Determine clinical and imaging markers which predict poor exercise capacity and atrial fibrillation.

Aim 2: Identify genetic traits associated with small hearts, poor exercise capacity and cardiac atrophy.

Aim 3: Assess the relationship between genes, physical activity, and heart structure and how they impact one another.

This project will generate highly clinically relevant knowledge with clear benefits to Australian clinical practice. Current health interventions are directed at those diagnosed with disease, but there is a crucial window of opportunity in preventing disease. By identifying markers predictive of exercise capacity, we will be able to identify individuals at greatest risk of heart failure and arrhythmias – both key causes of illness and health expenditure. By evaluating the relationship between our genome and exercise capacity we will identify to what extent the sedentary population may be genetically primed to be non-responders to exercise. The use of a cheap genetic test to anticipate response to therapy would be a considerable advance in individualized care. This research will lead to improvement in individualized risk assessments and early interventions to reduce population cardiac morbidity and mortality.

Dr Shaun Evans, Royal Adelaide Hospital, SA

The Project:

PREDICTive value of aggressive risk factor modification on the occurrence of major cardiovascular events in patients with embolic STROKE: PREDICT-STROKE

Synopsis:

PREDICT-STROKE is a randomised, multicentre trial to evaluate the potential benefits of aggressive risk factor modification versus standard of care to prevent major adverse cardiovascular events in patients with an embolic stroke or transient ischaemic attack.

Stroke is a major contributor to cardiovascular morbidity and mortality, resulting in lost quality of life, economic productivity, and health expense. Approximately one third of all strokes are attributable to atrial fibrillation, and a further third are cryptogenic (without known cause). Most cryptogenic strokes are subclassified as embolic stroke of undetermined source (ESUS). Approximately 3/10 patients with ESUS will be diagnosed with AF with prolonged monitoring.

Atrial cardiomyopathy is a relatively novel concept which encompasses pathological changes in the left atrium leading to the development of AF, or atrial thrombus and cardioembolism (potentially in the absence of AF). Multiple known factors influence atrial cardiomyopathy, and these include hypertension, obesity, diabetes, sleep apnoea and systemic inflammation.

We aim to test the hypothesis that aggressive management of these factors in a patient- specific fashion will prevent recurrent clinical and radiological embolic stroke.

The primary aim of the study is to investigate for patients with embolic stroke or transient ischaemic attack, whether the risk of major adverse cardiovascular events (including recurrent embolic stroke) can be modified by aggressive risk factor prevention.

For the diagnosis of atrial cardiomyopathy, invasive electroanatomical atrial mapping is known to demonstrate electrical atrial scar and regions of low voltage – the characteristic electrical changes of atrial cardiomyopathy. We aim to show that a multielectrode vest used to perform electrocardiographic imaging (ECGi) will correlate with invasive electroanatomical atrial mapping, predicting its extent and assist in stratifying risk of future atrial fibrillation.

We hypothesise that aggressive risk factor modification will reverse atrial cardiomyopathy, and that serial ECGi mapping will be able to demonstrate concordant longitudinal changes.

Systemic inflammation is closely related to the risk of developing AF, as shown by its relationship to multiple biomarkers of inflammation. We aim to investigate the relationship between these biomarkers and the extent of atrial cardiomyopathy as diagnosed by ECGi.

The primary potential benefit of this study is the identification of directed therapy for secondary prevention of embolic stroke of undetermined source. More generally, we expect a reduction in cardiovascular disease, which will provide individual patient benefit. With risk factor modification, we anticipate a group-level effect in weight reduction, blood pressure management and lifestyle improvement, which each have public health benefits for reduced incidence of atherosclerotic cardiovascular disease and improved mental health.

A clinically significant reduction in the primary endpoint of the study would translate to reduced hospitalisations, preserved quality of life, preserved cognitive function, freedom from physical disability and overall reduced healthcare expenditure.

Rebecca Raeside, PhD Candidate, Research Officer at the University of Sydney

The Project:

Health4Me Randomised Controlled Trial (RCT): primary prevention of cardiovascular disease among young people.

Synopsis:

The current picture of young peoples’ health in Australia is alarming with escalating health risks such as poor diet, physical inactivity, increased screen time and poor mental health becoming widely prevalent. These health risks can lead to chronic health problems such as heart disease in adulthood. Australia’s 3.3 million teenagers have little support to manage these health risks and accessible, engaging programs that support a healthy lifestyle are urgently needed. My innovative Health4Me program will strive to solve this problem. We know that text message healthy lifestyle programs in adults have improved health outcomes and resulted in positive behaviour change. Over the next 3 years, I will lead a research project that will develop and test an engaging healthy lifestyle program for teenagers using text messages, a method through which they communicate every day. I will work with teenagers to co-create the Health4Me program using an established process. I will test how effective Health4Me is in a randomised clinical trial (330 teenagers) and evaluate if the program improves physical and mental health outcomes, whether it is acceptable and engaging and if the program can be embedded into the Australian healthcare system. If it helps, it can be scaled up to deliver to teenagers throughout Australia to improve health outcomes.

Dr Thomas Meredith, Victor Chang Cardiac Research Institute, UNSW

The Project:

Improving therapeutic decision making in aortic valve stenosis.

Synopsis:

Aortic stenosis is the most common heart valve disease. It is characterised by a complex interplay between the aortic valve and the heart muscle (ventricular) function, making diagnosis and treatment timing challenging. Although replacement of the aortic valve has improved the prognosis of this condition, the current recommendations for the timing of replacement are associated with a highly advanced disease state and oftentimes sub-clinical heart muscle dysfunction, which is not only likely irreversible, but also portends a worse prognosis. It is possible that there may be a significant advantage to aortic valve intervention prior to the end-stage disease state which currently forms the basis for guideline recommendations. In the proposed doctoral research, we aim to better predict the response to therapy in aortic stenosis and identify factors associated with a favourable response to aortic valve intervention, such that we can help individualise treatment for patients and improve survival.