New AI can distinguish treatable, untreatable heart attacks 

Researchers at Smidt Heart Institute at Los Angeles-based Cedars-Sinai have developed an algorithm that, for the first time, distinguishes between treatable and untreatable forms of sudden cardiac arrest, the medical center said March 30. 

The findings were published March 30 in Journal of the American College of Cardiology: Clinical Electrophysiology. The risk assessment algorithm "consists of 13 clinical, electrocardiogram, and echocardiographic variables that could put a patient at higher risk of treatable sudden cardiac arrest," according to the journal.

"All sudden cardiac arrest is not the same," stated Sumeet Chugh, MD, director of the institute's Center for Cardiac Arrest Prevention and lead author of the study. "Until now, no prior research has distinguished between potentially treatable sudden cardiac arrest versus untreatable forms that cause death in almost all instances."

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