This algorithm can predict survival IA long term patient after cardiac surgery

This algorithm can predict survival IA long term patient after cardiac surgery

According to new research from Mayo Clinic, a new artificial intelligence (AI) algorithm that identifies cardiac dysfunction from a single-lead EKG it can also predict the long-term survival of the patient after cardiac surgery.

The retrospective study included reviews of 20,627 patients at the Mayo Clinic in Rochester from 1993 to 2019. The patients underwent coronary artery bypass graft, valve surgery, or both, and had a left ventricular ejection fraction of greater 35%.


Of these patients, 17,125 had a normal EKG screen AI and 3,502 had an abnormal screen. Patients with an abnormal screen tended to be older with more comorbidities.

ECG algorithms applied to the most recent

The algorithm was applied to the most recent ECG that patients had within 30 days of surgery. Baseline characteristics, as well as in-hospital, 30-day, and long-term mortality data were extracted from the Mayo Clinic cardiac surgery database.

The probability of survival at five years was 86.2% for patients with a normal screen versus 71.4% for those with an abnormal screen. The probability of survival at 10 years was 68.2% and 45.1% respectively for the two groups.

The analysis showed that an abnormal detection IA was associated with a 30% increase in long-term mortality after coronary bypass or valve. For doctors, This can help in the risk stratification of patients referred for surgery and facilitate shared decision making.