Score TO Predict SHOCK - STOP SHOCK

Study Overview
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Brief Summary
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The goal of this international multicenter study is to develop a scoring system to identify the risk of developing cardiogenic shock (CS) in patients suffering from acute coronary syndrome (ACS) utilising artificial intelligence. Study hypothesis: A complex machine learning (ML) model utilising standard patient's admission data predicts the development of cardiogenic shock in patients suffering from acute myocardial infarction better than standard prediction models. Study objectives: The primary objective of this study is to further improve predictive parameters of #STOPSHOCK model for prediction of development of cardiogenic shock in patients suffering from acute myocardial infarction. The secondary objective of this study is to develop a new predictive model for the development of cardiogenic shock in patients suffering from acute myocardial infarction based on larger combined cohort of patients utilising advanced ML algorithms, continuous model performance monitoring and continual learning.

Detailed Description
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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: The AI-based scoring system could aid in identifying high-risk patients prior to the development of cardiogenic shock. This would allow taking pre-emptive measures, implanting mechanical circulatory support, and thus prevent the development of shock, leading to improved survival. For this purpose, a predictive scoring system STOP SHOCK (Score TO Predict SHOCK) was developed. This scoring system showed better prediction compared to standard models. STOP SHOCK was validated on an external cohort of patients with area under the curve (AUC) of 0.844 surpassing other externally validated cardiogenic shock (CS) models (e.g. ORBI score). Furthermore, this model is based on variables that are readily available at the first contact with patients and thus STOPSHOCK can be utilized in emergency room (ER) or ambulance even before catheterization.

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

Conditions
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Cardiogenic Shock, Acute Coronary Syndrome, Acute Myocardial Infarction

Participation Criteria
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Eligibility Criteria
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Inclusion criteria for study population: Patients with at least one ICD9 diagnosis code: 41000 - 41092: various versions of Acute myocardial infarction 41189: Other acute and subacute forms of ischemic heart disease, other 4139: Other and unspecified angina pectoris Patients with at least one ICD9 diagnosis code: 78551: Cardiogenic shock 78550: Shock, unspecified Patients with at least one ICD9 procedures codes: 0066: Percutaneous transluminal coronary angioplasty [PTCA] 3604: Intracoronary artery thrombolytic infusion 3606: Insertion of non-drug-eluting coronary artery stent(s) 3607: Insertion of drug-eluting coronary artery stent(s) 3609: Other removal of coronary artery obstruction 8855: Coronary arteriography using a single catheter 8856: Coronary arteriography using two catheters 8857: Other and unspecified coronary arteriography 3722: Left heart cardiac catheterization 3723: Combined right and left heart cardiac catheterization Inclusion criteria for control group: Patients with at least one ICD9 diagnosis code: 41000 - 41092: various versions of Acute myocardial infarction 41189: Other acute and subacute forms of ischemic heart disease, other 4139: Other and unspecified angina pectoris Patients with at least one of the ICD9 procedures codes: 0066: Percutaneous transluminal coronary angioplasty [PTCA] 3604: Intracoronary artery thrombolytic infusion 3606: Insertion of non-drug-eluting coronary artery stent(s) 3607: Insertion of drug-eluting coronary artery stent(s) 3609: Other removal of coronary artery obstruction 8855: Coronary arteriography using a single catheter 8856: Coronary arteriography using two catheters 8857: Other and unspecified coronary arteriography 3722: Left heart cardiac catheterization 3723: Combined right and left heart cardiac catheterization Exclusion criteria for control group: 1. Patients without ICD9 diagnosis codes: 78551: Cardiogenic shock 78550: Shock, unspecified

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Study group (with CS)<br>A population of patients acquired from multiple national registries aged > 18 years, admitted for ACS without CS and proceeding to coronary angiography who developed cardiogenic shock (CS). | |
| Control group (without CS)<br>A population of patients acquired from multiple national registries aged > 18 years, admitted for ACS without CS and proceeding to coronary angiography who did not develop cardiogenic shock (CS). | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Development of cardiogenic shock | Development of cardiogenic shock (CS) in patients suffering from acute coronary syndrome (ACS) | Up to 72 hours | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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cardiogenic shock, acute coronary syndrome, artificial intelligence, scoring system, machine learning, acute myocardial infarction