ECG project UMCU

2020

The correct interpretation of electrocardiograms (ECGs) is crucial for accurately diagnosing cardiac abnormalities. Current methods, both manual by physicians and computerized, have not achieved the level of accuracy comparable to cardiologists in detecting acute cardiac issues. Leveraging advancements in artificial intelligence and big data, particularly deep neural networks, offers promising avenues to improve ECG interpretation where traditional methods have fallen short. The ECG-Project develops deep learning algorithms to automate ECG interpretation, particularly focusing on areas where current methods are inadequate.

Through this research, we aim to revolutionize ECG interpretation, improving diagnostic accuracy, reducing healthcare resource utilization, and ultimately enhancing patient outcomes.

The Research
The project objectives are:

  1. WP1: Creating an algorithm capable of accurately and swiftly triaging ECGs through transfer learning, uncovering features in diseases with unknown ECG characteristics (such as primary arrhythmia syndromes and genetic disorders).
  2. WP2: design a portable multi-lead ecg-device, suitable for use by patients at home and healthcare professionals. This device will enable high-quality ECG acquisitions for rapid diagnosis.

Origin
This project is funded within the Innovative Medical Devices Initiative (IMDI) program 'Heart for Sustainable Care'. The focus of this program is the development of medical technology for the earlier detection, monitoring, and better treatment of cardiovascular diseases to ensure accessible healthcare and sufficient staffing. The program has been developed and funded by the Dutch Heart Foundation, ZonMw and NWO, who collaborate within the Dutch CardioVascular Alliance.

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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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CUSTOM-AF

2020
Individuals with atrial fibrillation are at increased risk of an ischemic stroke. Active detection of atrial fibrillation (AF) and optimal referral and treatment of patients could prevent an estimated 1500 ischemic strokes annually. Effective collaboration between primary and secondary care professionals is essential for achieving this goal of stroke prevention attributed to AF. This is the primary objective of the implementation consortium known as CUSTOM-AF. The origin  The CUSTOM-AF was founded in June 2020 and restarted in 2022. CUSTOM-AF implementation consortium aims to share successful practice examples with regional networks and develop guidelines for organizing active detection and integrated care within a network. Additionally, consortium partners seek innovative methods for general practitioners to detect and manage AF without necessitating hospital referrals. With this consortium, the Dutch Heart Foundation, NVVC Connect, Harteraad, and the Dutch CardioVascular Alliance, all work together towards optimal care for patients with AF. The Dutch College of General Practitioners (NHG) serves as a key advisor to the consortium. Earlier detection and better treatment of atrial fibrillation, the most common cardiac arrhythmia in adults, is an important part of the cardiovascular disease research agenda that the Dutch Heart Foundatoin set in 2014, which funds the CUSTOM-AF consortium. The Research The scope of the consortium has been expanded to include two disorders: heart failure and AF. The consortium has undertaken significant initiatives over the past two years (2020-2022) to advance its objectives: Guideline Development: The consortium developed the "Screening and Treatment Optimization for AF" guideline, designed to facilitate early detection of AF within regional healthcare systems. Cost-Effectiveness Analysis: A comprehensive analysis conducted to assess various screening scenarios for AF, evaluating the economic feasibility of different approaches. Thematic Collaboration: In early 2022, a thematic collaboration titled "Juiste Hartzorg op de Juiste Plek" was established in partnership with the Heart Foundation and ZonMw. This collaboration secured funding for 22 regions to support transmural collaboration on AF and HF, with a focus on early detection and treatment optimization. Moving forward from September 2022, NVVC Connect will intensify support for the regions by emphasizing continuous improvement through the PDCA cycle, facilitating knowledge sharing, and implementing innovative approaches. These efforts are aimed at strengthening collaboration and improving outcomes in AF and HF care across the participating regions.
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