ECG project UMCU

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.
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PREDICT 2

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.
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LoDoCo2

2016
The aim of the LoDoCo2 (Low Dose Colchicine for secondary prevention of cardiovascular disease) trial was to investigate the effect of low dose colchicine (0,5 mg once daily) on the risk of myocardial infarction (fatal or non-fatal), stroke, or the need for coronary bypass or stent placement. While the precise mechanism through which colchicine mitigates major cardiovascular events remains incompletely understood, it is hypothesized that its anti-inflammatory effects contribute to risk reduction among patients with established atherosclerotic disease. LoDoCo2 stands out in several respects. It represents a large-scale randomized clinical trial conducted entirely by a non-academic network of cardiologists and a consortium of pharmaceutical companies with a focus on drug repurposing. This trial underscores the potential value of older, often cost-effective medications in advancing the development of new innovative drugs. The Research Following a median follow-up period of 3 years, the addition of colchicine to standard treatment resulted in a 30% reduction in risk of myocardial infarction (fatal or non-fatal), stroke, or the need for coronary bypass or stent placement. Patients treated with colchicine exhibited similar side effects compared to those receiving a placebo. Furthermore, no interactions were found with other commonly used drugs such as (potent) statins. In 2021, certain international guidelines had already incorporated colchicine into the secondary prevention of atherosclerotic cardiovascular disease (ASCVD). Subsequently, in 2023, the Food and Drug Administration (FDA) approved Lodoco® (colchicine) for reducing the risk of myocardial infarction (MI), stroke, coronary revascularization, and cardiovascular (CV) death in adult patients with established atherosclerotic disease or multiple risk factors for CV disease. This approval was based on published data regarding the effects of colchicine on cardiovascular events, along with insights from the LoDoCo2 trial. The LoDoCo2 investigators anticipate that colchicine will become the standard treatment for patients with coronary artery disease.
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