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

Cardiogenic shock (CS) is a severe complication of acute coronary syndrome (ACS) with mortality approaching 50% despite the use of percutaneous mechanical circulatory support devices (pMCS). Identifying high-risk patients prior to the development of CS could allow pre-emptive use of pMCS possibly preventing CS. For this purpose, we derived and externally validated a machine learning score to predict in-hospital CS in patients with ACS with c-statistics: 0.844 (95% confidence interval, 0.841-0.847). STOPSCHOCK score is available as a web or smartphone application. The aim of this study is to prospectively validate the STOPSHOCK score on a large cohort of ACS patients in a real- world clinical environment.

NCT Number	NCT07090382
Lead Sponsor	Premedix Academy
Conditions	Cardiogenic Shock, Cardiogenic Shock Acute, Cardiogenic Shock Post Myocardial Infarction, Acute Coronary Syndrome (ACS) Undergoing Percutaneous Coronary Intervention (PCI), PCI
Enrollment	1,046 participants
Start Date	2025-06-01
Primary Completion	2025-12-31 (estimated)
Study Completion	2026-04-30 (estimated)
Updated on ClinicalTrials.gov	2025-07-29