Sudden Cardiac Death (SCD) accounts for approximately 5,000 deaths yearly in Norway. High-risk individuals when identified can be offered life-saving therapy. Selection of patients for this therapy and prediction of SCD is one of the greatest challenges in current cardiology. Use of patient-specific genetic data combined with clinical data is instrumental in risk stratification for SCD.
Hypertrophic cardiomyopathy (HCM) is the
most common genetic heart disease, with disease-associated mutations found in
0.2-0.5% of European populations. HCM patients have an elevated risk of SCD,
with several factors known to modulate individual risk.
The overall objective of the workpackage is
to structure patients’ course through the chain of health care providers and
support decision making for patients at risk of sudden cardiac death and of
adverse outcome e.g. heart failure.
- NLP projects:
- Identification of patients at risk for SCD from electronic medical journal, identification of “syncope” to populate risk calculator.
- Interpretation of CT descriptions
- Pedigree tool: Extraction from free text - family relations relevant for medical condition
- SCD Risk Calculator implemented in DIPS Arena
- Automatic echo measurements for input to calculator (machine learning)
- Pipeline for text extraction from electronic medical journal