Heart4Data

2022

Registry-based research enables faster and cheaper clinical research by using real world data. This is particularly important in patient populations where research is otherwise difficult to conduct, such as heart failure patients with comorbidities. The main aim of the Heart4data consortium is therefore to develop a sustainable infrastructure for cardiovascular registry-based research in the Netherlands. This includes governance and Information Technology (IT) infrastructure, research methods, FAIR (findable, accessible, interoperable and reusable) data creation and data linkage with relevant databases. 
 
About Heart4Data 
The Heart4Data consortium is building on the core qualities and experience of DCVA partners. Heart4Data will create a DCVA Health Data Hub that will be part of the DCVA pillar Data Infrastructure to combine all expertises across the different DCVA partners as part of the sustainability program. 
 
In addition, Heart4Data will contribute to improvement of valorisation and implementation through accelerating the generation of results and facilitate DCVA consortia by providing a platform for research at lower operational costs compared to more traditional research methods. 
 
The Research 
1. To create a national and sustainable FAIR data-based infrastructure for cardiovascular registry-based research. 
The infrastructure includes a framework/structure for the governance, and the ethical, legal, financial, technological and methodological factors. There will be a special focus on heart failure in this project by creating a sustainable heart failure (and atrial fibrillation (AF)) registry in the Netherlands Heart Registration (NHR) and links with other relevant national and regional registries and data sources. 
 
2. To use and prove value of the infrastructure by conducting two projects: 
- Observational, longitudinal research on the entire spectrum of patients with heart failure (including patients with HFpEF) in the Netherlands (project A) with focus on guideline recommended diagnostic trajectories and treatment. 
- Prospective randomized clinical research on pharmaco-therapeutic treatment in patients with chronic heart failure (project B: SELEQT-HF).

The origin

One of the five top priorities named on the cardiovascular disease research agenda that the Dutch Heart Foundation set in 2014 was finding better treatment for heart failure and arrhythmias. Back in 2014, when the research agenda was drawn up, it became clear that registry-based research is essential for this. The Dutch Heart Foundation therefore funded this study as part of the collaboration with the ZonMw GGG program on Good Use of Medicines (Goed Gebruik Geneesmiddelen).

For a complex project such as this, collaboration within the entire cardiovascular field is an important starting point. The consortium is a collaboration between several DCVA partners; the Dutch Heart Foundation, ZonMw, NHR, WCN, Harteraad, NLHI, NVHVV, NVT, NVVC, VIG and Health-RI.

 

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PREDICT 2

2019
Sudden cardiac arrest (SCA) remains a significant public health challenge, accounting for nearly 20% of all deaths in developed nations and approximately half of all heart disease-related fatalities. A notable subset of SCA cases occurs in individuals without prior heart disease diagnosis, resulting in profound psychosocial impacts on affected families and society. Ventricular fibrillation (VF) is the primary arrhythmia leading to SCA, often occurring outside healthcare settings with survival rates ranging from 5% to 20%. Prevention is crucial, yet gaps in our understanding of SCA causes and mechanisms hinder effective prevention efforts. Various genetic and non-genetic factors, such as gender, age, comorbidities, and lifestyle, likely influence SCA risk, but their specific contributions remain unclear. The Focus The PREDICT2 initiative brings together leading Principal Investigators with expertise in epidemiology, clinical studies, genetics, and functional research to elucidate factors contributing to SCA, uncover underlying mechanisms, and develop strategies for prevention and treatment. The Research Building on foundational work from PREDICT1, which involved extensive patient characterization and preclinical model development, PREDICT2 focuses on inherited arrhythmia syndromes as models to understand the arrhythmogenic substrate in more common cardiac syndromes associated with SCA. Specifically, PREDICT2 aims to: Identify genetic and non-genetic factors that contribute to SCA risk and develop personalized risk prediction algorithms for individual patient assessment. Conduct functional studies to elucidate the mechanisms underlying SCA, enabling the development of novel risk stratification and therapeutic approaches. Implement clinical studies to evaluate risk prediction algorithms and therapeutic interventions, aiming to enhance the treatment and prevention of SCA. Origin This consortium was funded through the Impulse Grant program by the Dutch Heart Foundation.
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MyDigiTwin

2020
Cardiovascular disease (CVD) is the leading global cause of mortality and morbidity, with ischemic heart disease (IHD) representing approximately half of all CVD-related deaths. Precise, personalized risk assessment and treatment recommendations are crucial for addressing the diverse population at risk of CVD. Current standard approaches rely on algorithms that incorporate a limited set of traditional risk factors to estimate CVD and IHD risk. However, significant cardiovascular events often occur in individuals categorized as low risk, underscoring the need for ongoing research to enhance preventive strategies. The Focus The MyDigiTwin initiative aims to provide individuals with personalized insights into their cardiac health, enabling proactive monitoring and management of cardiovascular conditions. This integrated digital health platform empowers individuals to take control of their cardiac health by offering accessible, data-driven insights and tools. The Research MyDigiTwin is a pioneering research initiative focused on revolutionizing cardiac health management by integrating advanced AI technologies with extensive patient data. The development of MyDigiTwin involves harnessing large-scale longitudinal datasets from over 500,000 patients, combined with sophisticated AI algorithms. This approach enables the platform to analyze diverse health parameters and generate tailored recommendations for users based on their unique health profiles. By leveraging AI and comprehensive patient data, MyDigiTwin represents an innovative approach to preventive and personalized healthcare, facilitating early detection and intervention for cardiovascular conditions. Origin This project was funded within the Big Data & Health Program. The focus of this public-private research program is the use of big data for the early detection and prevention of cardiovascular diseases. The program has been developed by NWO, ZonMw, the Dutch Heart Foundation, the Top Sectors Life Sciences & Health (LSH), ICT and Creative Industry, the Ministry of Health, Welfare and Sport, and the Netherlands eScience Center. Within this research program, the ambitions of the Dutch Heart Foundation, the Ministry of Health, Welfare and Sport, and the Netherlands eScience Center were aligned with the ambitions of Commit2Data for the Top Sectors ICT, LSH, and Creative Industry, as described in the 2018-2019 Kennis- en Innovatiecontracts between NWO and the Top Sectors.
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