AI algorithm can predict long-term patient survival after cardiac surgery, Mayo Clinic study finds

An artificial intelligence algorithm that can identify cardiac dysfunction from a single-lead EKG also can predict long-term survival for patients following cardiac surgery, a new study published Dec. 1 in Mayo Clinical Proceedings found. 

Researchers analyzed reviews of 20,627 patients at Mayo Clinic in Rochester from 1993 to 2019. The patients underwent coronary artery bypass grafting, valve surgery or both, and they had a left ventricular ejection fraction of more than 35 percent. Of the patients, 17,125 had a normal AI EKG screen and 3,502 had an abnormal screen.

Baseline characteristics, as well as in-hospital, 30-day and long-term mortality data, were pulled from the Mayo Clinic cardiac surgery database. Researchers applied the AI algorithm to the most recent EKG the patients had within 30 days before surgery. 

Patients with a normal screen had a survival probability of 86.2 percent while patients with an abnormal screen had a probability of 71.4 percent. The 10-year probability of survival was 68.2 percent and 45.1 percent, respectively, for the two groups.

"The analysis showed that an abnormal AI screen was associated with a 30 percent increase in long-term mortality after valve or coronary bypass surgery," Mohamad Alkhouli, MD, Mayo Clinic cardiologist and the study's senior author said in a press release. "For clinicians, this may aid in risk stratification of patients referred for surgery and facilitate shared decision-making."

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