DECISION

2020

Digoxin is the oldest, market-authorized drug for heart failure (HF), and very cheap. A large trial with digoxin, the DIG trial, executed in the early nineties revealed a highly significant reduction in HF hospitalizations, but no effect on mortality. A post-hoc analysis of the DIG trial suggests that low serum concentrations of digoxin may not only improve HF hospitalizations but also mortality in chronic HF patients. To validate these findings, a prospective, randomized, placebo-controlled trial is required to redefine the role of digoxin in modern HF treatment.

The Focus
The primary objective of this study is to investigate whether low-level digoxin (targeting serum concentrations of 0.5-0.9 ng/mL), compared to a placebo, reduces (repeated) HF hospitalizations, (repeated) urgent HF hospital visits, and cardiovascular mortality when added to standard guideline-recommended therapies in chronic HF patients with reduced or mid-range ejection fractions (LVEF ≤50%).

The Research

This proposed trial is a national, multicenter, randomized, double-blind, placebo-controlled clinical trial involving 982 chronic HF patients aged ≥18 years, classified as NYHA II to ambulatory IV, LVEF ≤50%, and specific serum NT-proBNP concentrations based on rhythm and recent HF hospitalization status. Patients must also be on guideline-recommended therapies. The study population includes at least one-third with atrial fibrillation (AF) and one-third women to represent the real-life HF population.

Patients were randomized to receive either a low-level digoxin or a placebo in a double-blinded manner. Digoxin Teva will be administered orally, starting at doses of 0.2mg or 0.1mg (based on age, renal function, and concomitant medication). No loading dose is given to the placebo group. After 4 weeks of evaluating medication (digoxin or placebo), concentrations will be measured. Dose adjustments will be made if needed to reach the target serum digoxin concentration range of 0.5-0.9ng/mL.

The outcomes in reducing adverse cardiovascular events in patients with chronic heart failure of low-dose digoxin will be compared to the outcomes of the placebo.

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Funded

Contact person:

Nicoline Smit

Principal investigators

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HEROES

2020
The focus of this project is to develop a novel home-based exergaming system aimed at enhancing resistance to falls among individuals post-stroke. Preventing falls and fall-related injuries, minimizes healthcare utilization and societal costs and supports stroke survivors in maintaining independence in daily life. The Research The HEROES system is designed to target balance perturbations and improve stepping responses. It utilizes action observation and motor imagery techniques to personalize training for individuals with stroke. Stroke survivors will undergo a single training session in a rehabilitation center to practice recovering from real balance perturbations before using HEROES at home. The effectiveness of the HEROES-system will be assessed through a proof-of-principle randomized controlled trial (RCT) involving 60 stroke survivors, evaluating its impact on fall resistance and balance enhancement post-stroke. The approach of involving stroke survivors sets HEROES clearly apart from the currently available home-based exergames, which uses ‘healthy’ people and lack the required personalization of different post-stroke individuals. 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 en funded by the Dutch Heart Foundation, ZonMw and NWO, who collaborate within the Dutch CardioVascular Alliance.
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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: 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). 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 en funded by the Dutch Heart Foundation, ZonMw and NWO, who collaborate within the Dutch CardioVascular Alliance.
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