Artificial Intelligence Based Predictive Scoring System to Identify the Risk of Developing Cardiogenic Shock (CS) in Patients Suffering From Acute Coronary Syndrome (ACS)

Background:

Cardiogenic shock is a serious life-threatening condition affecting almost 10% of patients suffering from acute coronary syndrome (ACS). When untreated, it can rapidly progress to collapse of circulation and sudden death. Despite recent improvements in diagnostic and treatment options, mortality remains incredibly high, reaching nearly 50%.

Currently available mechanical circulatory support devices can replace the function of the heart and/or lungs, thereby essentially eliminating the primary cause. However, cardiogenic shock is not only an isolated decrease in cardiac function but a rapidly progressing multiorgan dysfunction accompanied by severe cellular and metabolic abnormalities. The window for successful treatment is relatively narrow, and when missed, even the elimination of the underlying primary cause is not enough to reverse this vicious circle.

The ability to identify high-risk patients prior to the development of shock would allow to take pre-emptive measures, such as the implantation of mechanical circulatory support, and thus prevent the development of shock leading to improved survival.

Rationale: