25 Aug Model Developed For Prediction of Sudden Cardiac Death
MedicalResearch.com Interview with:
Alvaro Alonso, MD, PhD
Department of Epidemiology
Rollins School of Public Health
MedicalResearch.com: What is the background for this study? What are the main findings?
Response: Sudden cardiac death (SCD) is a major public health problem. Each year, 300,000-400,000 Americans experience SCD and, in more than half of these cases, sudden cardiac death is the first manifestation of heart disease. To date, however, we lack effective strategies to identify those at higher risk of developing sudden cardiac death so targeted preventive strategies can be applied.
In this study, we develop and validate the first model for the prediction of SCD in ~18,000 adults without a prior history of cardiovascular disease. We show that information on demographic variables (age, sex, race), some traditional cardiovascular risk factors (smoking, elevated blood pressure, diabetes, HDL cholesterol) as well as some factors more specifically related to SCD causes (electrocardiogram QT interval) and novel biomarkers (albumin, potassium in blood, kidney function) can be leveraged to predict risk of SCD and identify individuals more likely to suffer this event.
MedicalResearch.com: What should readers take away from your report?
Response: Clinicians can consider using our proposed risk score, in combination to other validated scores for prediction of cardiovascular disease in general, to inform their patients about their future risk of sudden cardiac death. This information can facilitate conversations about preventive strategies to reduce future risk of cardiovascular disease. The general public could also use the information from the predictive model to discuss with their healthcare providers the best approaches to prevent SCD and other cardiovascular diseases.
MedicalResearch.com: What recommendations do you have for future research as a result of this study?
Response: This is a first step towards stratifying risk of sudden cardiac death across the general population. Future work should aim to refine our predictive model adding information on other biomarkers, genomics data, etc. Also, it will be important to determine whether information on SCD risk is useful and leads to better outcomes in clinical practice.
MedicalResearch.com: Is there anything else you would like to add?
Response: This work is the result of an exciting collaboration between investigators across many different institutions and a testament to the value of population-based cohort studies to answer important questions about prevention of cardiovascular diseases. Support from the National Institutes of Health and the American Heart Association has been invaluable to make it happen.
MedicalResearch.com: Thank you for your contribution to the MedicalResearch.com community.
Rajat Deo, Faye L. Norby, Ronit Katz, Nona Sotoodehnia, Selcuk Adabag, Christopher R. deFilippi, Bryan Kestenbaum, Lin Y. Chen, Susan R. Heckbert, Aaron R. Folsom, Richard A. Kronmal, Suma Konety, Kristen K. Patton, David Siscovick, Michael G. Shlipak, Alvaro Alonso. Development and Validation of a Sudden Cardiac Death Prediction Model for the General Population. Circulation, 2016; CIRCULATIONAHA.116.023042
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