Project description
Multistate modeling to predict risk markers for AF
Atrial fibrillation (AF) is a severe medical condition often associated with increased mortality risk. The most common available diagnostical tool is Electrocardiogram (ECG). Numerous P wave indices (PWI) are associated with increased risk for adverse cardiovascular outcomes and mortality. The non-invasive signal-averaged electrocardiogram (SAECG) is more reliable for the detection of P wave prolongation as a risk marker for AF. However, available data analysing this issue are limited. The EU-funded SAECG project will perform P wave SAECGs in Framingham Heart Study (Boston, US) and LIFE Health Care Study (Leipzig, Germany) to investigate their role in AF incidence. The project will use multistate modeling phenomapping of AF to predict the corresponding lifetime risk.
Objective
Atrial fibrillation (AF) may be categorized as an epidemic disease associated with an increased risk for heart failure, thromboembolism, dementia and mortality. The underlying mechanisms behind AF describe multiple pathological states leading to various remodeling processes. One of the easiest available diagnostical tools is an electrocardiogram (ECG). Numerous P wave indices have been identified, demonstrating associations with increased risk for adverse cardiovascular outcomes and mortality. Prolonged signal-averaged P wave duration (SAPWD) measured from the non-invasive signal averaged electrocardiogram (SAECG) using a vector composite of filtered orthogonal leads accurately measures cardiac activation times. In comparison with analysis of a standard 12-lead ECG, the SAECG is superior in detection of P wave prolongation as a risk marker for AF. However, there are only limited data analyzing this issue.
Current project is aimed to perform P wave SAECGs in Framingham Heart Study (Boston, US) and LIFE Health Care Study (Leipzig, Germany) and to investigate their role in AF incidence. Furthermore, estimation of corresponding lifetime risk will be performed using multistate modeling phenomapping of AF, e.g. classification of AF patients based on a broad range of data (clinical, laboratory, ECG, echocardiography, biomarkers) predicting adverse clinical outcomes.
The current project represents an innovative and authentic multidisciplinary research in AF and includes different future perspectives. It paves the way for fruitful international cooperation with Framingham cohort - the one the most renowned epidemiological studies, intensive exchange of experience and researcher mobility as well as academical and practical implementation of cardiovascular epidemiology and prevention at European institution.
Fields of science
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Programme(s)
Funding Scheme
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinator
04109 Leipzig
Germany