Clinical trials

Heart Failure (HF) is a global condition affecting at least 26 million people worldwide. Despite advances in treatment, HF patients continue to experience poor health outcomes. This study aims to improve understanding of the role of blood vessels in people with heart failure. The study will assess how arterial stiffness (how stiff blood vessels are) and endothelial function (how well the lining of blood vessels functions) change over time and respond to treatments received as part of routine clinical care. Blood vessel function and heart performance will be assessed at three time points: * At baseline (when Patients are first diagnosed with heart failure). * After completing 4 ± 2 weeks of heart-failure medicines prescribed to patients as part of their routine clinical care. * After completion of cardiac rehabilitation program as a part of their routine clinical care. All assessments are non-invasive.

Heart failure (HF) is a complex clinical syndrome associated with impaired heart function, poor quality of life for patients and high healthcare costs. Accurate risk stratification and early diagnosis in HF are challenging as signs and symptoms are non-specific. Here the investigators propose to address this global challenge by developing novel analytic methods for HF (STRATIFYHF). A prospective clinical study will collect patient-specific data related to medical history, a physical examination for signs and symptoms, blood tests including natriuretic peptides, an electrocardiogram (ECG), an echocardiogram (ultrasound of the heart), cardiovascular magnetic resonance imaging (MRI), demographic, socio-economic and lifestyle data along with novel technologies (cardiac output response to stress (CORS) test and voice recognition biomarkers) from individuals at-risk of developing HF and those with a confirmed diagnosis of HF. STRATIFYHF will use these data to develop, validate and implement the first artificial intelligence (AI)-based, Decision Support System (DSS) for assessing and predicting the risk of HF development, its early diagnosis and progression. STRATIFYHF will integrate 1) patient-specific data i.e. demographic, clinical, genetic, lifestyle and socio-economic, 2) an AI-based digital patient library and AI-driven algorithms for risk stratification, early diagnosis, and disease progression in HF, and 3) a highly innovative multifunctional AI-based DSS and mobile application for informing a patient-centred, personalised, prevention and treatment strategies for HF.

The purpose of this study is to investigate and compare the effects of Christian and Islamic heart-centred spiritual meditation to mindfulness meditation and waitlist control conditions, respectively, in healthy adults. The potential effects will be studied at multiple levels, with a focus on psychophysiology, cognition, mental health, and social functioning.

The study aims to implement a 12-week home-based exercise programme utilising an online intervention delivery platform. The focus will be on increasing exercise behaviour within the participant's home setting using aerobic, resistance and flexibility exercises as well as behaviour change techniques. Following the programme, semi-structured interviews will be conducted, to explore participant experiences. It is hypothesised that the exercise programme will be feasible, accessible and acceptable.