Objectives of the course aim to provide a comprehensive understanding of electrocardiography research across various domains, encompassing both basic science and clinical applications.

Topics

• ECG research at Statistics Denmark
• Large and small animal ECG
• Cardiac ion channels
• Phenotypical ECG markers
• ECG in autoimmune and inflammatory diseases
• Processing and analyzing ECG data from ambulance and hospital sources
• Synthetic ECG generation
• Machine learning in ECG research
• Epidemiological ECG research
• Clinical EP studies
• Syncope
• Biventricular pacemaker therapy

Learning objectives

A student who has met the objectives of the course will be able to:

• Understand the legal framework governing ECG research at Statistics Denmark, including specific rules and regulations for accessing, handling, and analyzing data
• Understand and critically evaluate the strengths and limitations of population-based ECG studies
• Understand the structure and format of ECG datasets at Statistics Denmark, including the variables, data types, and metadata associated with each record, to facilitate effective data utilization and interpretation
• Explore collaborative research opportunities and interdisciplinary collaborations fostering partnerships with other research institutions to address complex research questions using ECG data
• Analyze and compare large and small animal models of arrhythmia to elucidate their relevance, advantages, and limitations in translational research for human cardiac electrophysiology
• Explore cardiac ion channels, action potentials, and tissue-level electrophysiology, and apply this knowledge to design and interpret experimental studies
• Identify and characterize phenotypical ECG markers associated with various cardiac conditions, including their sensitivity, specificity, and clinical significance for diagnosis and risk assessment
• Analyze the role of ECG in autoimmune and inflammatory diseases affecting the cardiovascular system, including mechanisms of ECG alterations and their implications for disease monitoring
• Assess the ECG manifestations and drug effects in psychiatric diseases
• Design and implement algorithms for synthetic ECG generation, considering physiological variations and noise characteristics
• Understand machine learning techniques to analyze ECG signals for pattern recognition, risk stratification, and predictive modeling in cardiac arrhythmias and related disorders
• Analyze the mechanisms of action, pharmacokinetics, and clinical efficacy of antiarrhythmic drugs, including their indications, contraindications, and adverse effects, to optimize therapeutic strategies
• Examine the diagnostic utility of ECG in syncope evaluation, including differentiating cardiac and non-cardiac causes
• Evaluate the rationale, patient selection criteria, and clinical outcomes of biventricular pacemaker therapy in bundle branch block, integrating principles of cardiac resynchronization therapy with ECG findings

PROGRAM

Course directors 

Claus Graff, Prof., Aalborg University
Jonas L. Isaksen, PhD, University of Copenhagen
Jørgen Kanters, Assoc. Prof., University of Copenhagen
Christoffer Polcwiartek, MD PhD, Aalborg University

Registration

DCAcademy covers participation fee, catering, accomodation and common transportation from Aalborg airport to the venue and back (if you are traveling by train, please, come to the Aalborg airport train station).
 

Allocation of seats

Please note that you are not guaranteed a seat at the event if you do not meet the target group requirements. Priority is given to early career researchers (PhD-students and Postdocs) employed at Danish research and health-care institutions or in the life science industry. For some events a number of seats may be reserved for international participants employed at research and health-care institutions or in the life science industry. If the event is overbooked, the DCAcademy reserves its right to select participants based on the defined requirements.

No-show fee 

Please note that the DCAcademy will charge a no-show fee of 5000 DKK if you do not show up and have not unregistered prior to start.