Improving the Prediction of and Response to Sudden Cardiac Arrest

The co-founder and co-director of the Stanford Arrhythmia Center, cardiologist Sanjiv M. Narayan, MD, PhD, and his team strive to develop new treatments for heart rhythm disorders such as atrial fibrillation. Formerly a professor at the University of California, San Diego, Dr. Sanjiv Narayan studies topics that involve a number of cardiovascular conditions, including sudden cardiac arrest (SCA).

SCA is a leading worldwide killer. People who experience SCA out of a hospital setting survive less than 10 percent of the time. To improve that statistic, certain challenges must be overcome in prediction and response pathways.

A study conducted by Dr. Narayan and other investigators found that prediction could benefit greatly by streamlining the classification of SCA by personalized risk factors such as genetic expression variants, their functional changes, structural factors in the heart and other disease conditions, using machine learning to integrate multidisciplinary discovery.

Response systems can be addressed by outfitting community response stakeholders (first responders, hospitals, schools, etc.) with external defibrillators and other technology to facilitate resuscitation when an SCA event occurs.

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