Two studies advance sudden cardiac arrest prediction

Warning symptoms, recurrent heart events may identify people at risk for this often-deadly event. Two studies from investigators at Cedars-Sinai Health Sciences University move the medical field closer to solving a longstanding challenge: predicting who is at risk for sudden cardiac arrest.

"The majority of people who have a sudden cardiac arrest outside of a hospital will die, so the best protection is being aware of risk," said Kyndaron Reinier, Ph.D., M.P.H., associate director of epidemiology in the Center for Cardiac Arrest Prevention in the Smidt Heart Institute at Cedars-Sinai and an author of both studies.

Sudden cardiac arrest happens when a problem with the heart's electrical system causes the heart to stop beating. It is different from a heart attack, which is caused by a lack of blood flow to the heart. More than 350,000 people experience sudden cardiac arrest outside of a hospital in the U.S. each year, and only about 10% survive.

Experts know that people with low left ventricular ejection fraction, a condition in which the heart's main pumping chamber is weak and pumps less than it should, are at higher risk for sudden cardiac arrest. But this marker has become less effective, and other indicators are needed to identify more people at risk.

"More than two-thirds of people who have cardiac arrest don't have low left ventricular ejection fraction, so using this marker alone misses too many people," Reinier said.

A study published in the journal Circulation: Arrhythmia and Electrophysiology reports that warning symptoms combined with clinical history could predict imminent sudden cardiac arrest. A second study, published in the Journal of the American Heart Association (JAHA), reports that having more than one cardiac event over time could signal rising risk.

Reading warning symptoms

In the Circulation: Arrhythmia and Electrophysiology study, investigators used machine learning to identify combinations of symptoms and medical history that best predicted sudden cardiac arrest in the near future.

The study included people enrolled in two separate, long-standing studies in Oregon and Ventura County, California, established by Sumeet Chugh, M.D., director of the Center for Cardiac Arrest Prevention in the Smidt Heart Institute. The investigators compared 364 people who called 911 while experiencing symptoms such as chest pain and survived sudden cardiac arrest with 313 people who called 911 for similar symptoms but did not experience sudden cardiac arrest.

The analysis found that people with sudden cardiac arrest were more likely to have a combination of shortness of breath and diagnosed coronary artery disease or heart failure than people who did not experience sudden cardiac arrest. Seizure-like symptoms without chest pain or shortness of breath were also more common in people who experienced sudden cardiac arrest.

The investigators also found that chest pain combined with coronary artery disease predicted imminent arrest in women, while chest pain combined with heart failure predicted it in men.

Warning symptoms most often occurred at least 15 minutes before sudden cardiac arrest, a time frame that would make it possible to call 911. In earlier research, the investigators found that 81% of people delayed their 911 call, reducing their chances of successful revival by ambulance paramedics.

These findings could be used to create risk-predicting algorithms for urgent care and emergency medicine providers, the investigators said. "While more research is needed, such risk prediction algorithms have the potential to avoid 911 call delays following warning symptoms of sudden cardiac arrest," said Chugh, vice dean and chief AI health research officer at Cedars-Sinai.

Tracking risk over time

The JAHA study was carried out in the Observational Study of Cardiac Arrest Risk (O.S.C.A.R.) cohort at Cedars-Sinai, established by Chugh, which has tracked the health of approximately 400,000 residents of Los Angeles County since 2017.

Of these, the investigators followed more than 6,700 people hospitalized at Cedars-Sinai for heart failure and more than 2,900 people hospitalized in the health system for acute coronary syndrome, a condition in which an artery blockage reduces blood flow to the heart.

Investigators found that patients in both groups who experienced a recurrent cardiovascular event faced a higher risk of sudden cardiac arrest.

Patients who had a second coronary artery blockage were more than three times as likely to experience sudden cardiac arrest as those without a recurrence. Patients who were hospitalized a second time for heart failure were nearly twice as likely to experience sudden cardiac arrest. Risk climbed with each additional heart failure hospitalization.

The investigators compared the findings with those of participants in the Framingham Heart Study, which enrolled participants about 50 years earlier. The results were similar; however, the heart failure result in that study did not reach statistical significance.

Reinier said that physicians should consider sudden cardiac arrest more likely when a patient is hospitalized for a heart issue a second time.

"This may mean running additional tests," Reinier said. "It may mean educating the patient about what cardiac arrest is and the importance of having a family member who knows to call 911 and start CPR immediately if their loved one collapses."

Moving beyond dead ends

Chugh, senior author of both studies, said the combined findings point toward a more flexible approach to prediction.

"Near-term and long-term predictions are parallel approaches that can help us move past roadblocks we face in preventing death from this lethal heart event," Chugh said.

Additional research, including studies in different populations, is needed to confirm whether the factors the investigators studied could be used in prediction tools, study authors said.

Cedars-Sinai investigators continue to study predictors of sudden cardiac arrest, and their work includes using AI to study patterns in heart tests called electrocardiograms and looking for genetic causes.