Dr. Mary Mooney

Summary

This innovative study aims to identify the unmet needs of women in menopause and their health research priorities, and potential solutions to optimise menopausal health. The transformative element is focused on co-creating with women and healthcare professionals, a blueprint for personalised health and management of menopausal symptoms. This blueprint will inform national and international policy for directing future menopausal services and research priorities.

Funding Agency

Trinity College Dublin

Programme

Dean's Research Initiative Fund

Project Type

Mixed methods

Person Months

36

Summary

In 2017 the primary care reimbursement service of Ireland approved the use of LCZ696 (which later became known as Entresto) to be used following strict guidelines for use in selected patients with HFrEF. For patients with HFrEF who do not meet the criteria for use of Entresto and who have a systolic BP>100mmHg and no history of angioedema a ACE inhibitor is recommended or ARB if intolerant to ACE inhibitor (Grade 1A recommendation see reference more details). This was following PARADIGM-HF trial (McMurray et all, 2014). The study found LCZ696 was superior to enalapril in reducing the risk of death and of hospitalisation for heart failure. The study found that by reducing the inhibition of both the angiotensin II inhibitor receptor and neprilysin with Entresto, it therefore reduced the risk of death from cardiovascular causes or hospitalisation for heart failure the ACE inhibitor. The LCZ696 was also superior to enalapril in reducing symptoms and physical limitations of heart failure. These robust findings provided strong evidence that combined inhibition of the angiotensin receptor and nepilysin is superior to inhibition of the renin-angiotensin system alone inpatient with chronic heart failure. This study will quantify the effects of Entresto in HF patients using secondary data analysis.

Funding Agency

unfunded

Programme

Cardiology

Project Type

Clinical audit and research

Person Months

18

Summary

The predominance of prior research has focused on the causes of delay. However, the question about the reasons patients may seek treatment early has not been addressed. We believe this is important to consider, with the goal of identifying what might support patients with decision-making in seeking early treatment, in the future. Over the past decade there has been a paucity of qualitative research undertaken in the early post-MI phase, either during or following hospitalisation, with many studies focusing on the negative aspects of pre-hospital delay. We propose to depart from these negative perspectives by illuminating and exploring those positive actions taken by patients in seeking help, which is something that is rarely highlighted. Therefore, the aim of this study is to explore, within four weeks of the event, patients" perceptions of the contributors to their treatment-seeking interval, among those who sought treatment early, when experiencing a myocardial infarction. To elucidate patients' perceptions of the contributors to prompt treatment-seeking behaviours and responses to symptoms during acute myocardial infarction. Aim: To elucidate patients' perceptions of the contributors to prompt treatment-seeking behaviours and responses to symptoms during acute myocardial infarction. Objectives " To describe patients" perceptions of those factors that contributed to prompt treatment-seeking behaviour during their myocardial infarction. " To elucidate the basic social processes that may help to explain prompt help-seeking behaviour in the presence of myocardial infarction.

Funding Agency

University of British Columbia

Project Type

Research

Person Months

12

Summary

Heart Failure (HF) is a life-threatening condition affecting the ability of the heart to maintain an adequate blood flow, due to changes in structure or function, and typically has a poor prognosis. HF is often a consequence of other diseases resulting in cardiac dysfunction. Typical symptoms are shortness of breath, leg swelling and excessive tiredness which tend to worsen, leading to reduced quality of life, increased dependency and frequent hospitalizations. RAFAEL aims to develop an AI model for risk assessment and the prediction of decompensations in telemonitored HF patients, avoiding exacerbations and preventing hospitalizations. The model will target scalable and optimal management of a large population of patients, integrating data capture technology (apps, wearables) and prediction models into a novel decision support system (DSS) for HF management, to improve health outcomes, reduce healthcare costs, increase health literacy and self-management of patients. For model development and validation, RAFAEL will deploy the monitoring solution at different validation sites (five in Europe and one in Colombia) for optimal model development and validation, comparing its integration into different settings, organizations and countries, also including aspects of social innovation. It will also establish methodologies for the validation of similar models, including aspects such as the AI model lifecycle and a regulatory pathway for this kind of development, as well as clinical guidelines and protocols for the smooth integration of the prediction and prevention models within different clinical settings. The RAFAEL project proposes an innovative AI model to predict and prevent the risk of HF decompensation that brings together the expertise of a number of European entities specialized in Big Data and AI, eHealth, data capture and processing, sensors and wearables, wearable manufacturing, HF research, clinical trials, stakeholder involvement and patients' engagement.

Funding Agency

Horizon Action Health - European Commission

Programme

Horizon Europe Framework Programme (HORIZON)

Project Type

Clinical trial using AI

Summary

Cardiovascular diseases (CVD) account for 37% of all deaths in the EU, with a total of over 1.8 million deaths annually. CVD cost the EU 210 billion € per year, due to direct healthcare costs, productivity loss, and informal care by caregivers. Although heart disease is the leading cause of death in women, CVD is not adequately researched in women, more so in the 40-60 age group, even though evidence confirms that menopause render women more susceptible to CVD after menopause. As a result, CVD are under-diagnosed and under-treated in women in the 40-60 age group. General models for CVD risk scoring are applied, evidencing a lack of specific and tailored risk models, gender, or sex-specific risk factors, throughout their life cycle. In this context, there is an opportunity to design and refine national CVD plans and stratify the risk of CVD, following a population-based approach, between women from early stages for a personalised prevention and care, considering Big Data and AI capabilities applied to heterogenous data sources, including clinical, lifestyle, image and -omics. The objective of CARAMEL is to develop and validate a novel stratified approach for personalized CVD Risk Assessment and intervention model, enabled by a variety of data sources. CARAMEL, will deliver: i) Validated AI and statistical CVD-Risk Assessment models for women aged 40-60 years allowing to carry stratification strategies for the predictions of developing CVD in women aged 40-60years, tested in 6 international clinical sites; ii) A personalised CVD prevention model including a Clinical Decisions Support System and self-management ecosystem (app, personal coach and wearables for monitoring) empowering women and helping healthcare professionals in the management of CVD; iii) Clinical pathways and guidelines for EU CVD Prevention and Screening programmes integrating personalised prevention and management strategies; iv) Regulatory Roadmap for certification of the CVD RA models.

Funding Agency

HORIZON-HLTH-2024-STAYHLTH-01-two-stage

Programme

HORIZON-HLTH-2024-STAYHLTH-01-05-two-stage

Project Type

HORIZON-RIA (HORIZON Research and Innovation Actions

Person Months

48