Prehospital Prediction of Cardiogenic Shock Among Patients With ST‐Segment–Elevation Myocardial Infarction: The EARLY SHOCK Score

Cardiogenic shock (CS) develops in up to 10% of patients with ST-segment-elevation myocardial infarction and is associated with high mortality and morbidity rates. The objective of the current study was to generate a clinical scoring system that can be easily applied in the prehospital setting to pr...

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Published in:	Journal of the American Heart Association Vol. 14; no. 19; p. e040681
Main Authors:	Yang, Cathevine, Lee, Terry, Kochan, Andrew, Barker, Madeleine, Roston, Thomas M., Cairns, John A., Singer, Joel, Grunau, Brian, Helmer, Jennie, Berg, David D., Wong, Graham C., Fordyce, Christopher B.
Format:	Journal Article
Language:	English
Published:	England Wiley 07.10.2025
Subjects:	Aged cardiogenic shock Emergency Medical Services - methods Female Humans Male Middle Aged Percutaneous Coronary Intervention - adverse effects Predictive Value of Tests prehospital Retrospective Studies Risk Assessment - methods Risk Factors shock team Shock, Cardiogenic - diagnosis Shock, Cardiogenic - epidemiology Shock, Cardiogenic - etiology ST Elevation Myocardial Infarction - complications ST Elevation Myocardial Infarction - diagnosis ST Elevation Myocardial Infarction - surgery STEMI Time Factors STEMI cardiogenic shock prehospital shock team
ISSN:	2047-9980, 2047-9980
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Abstract	Cardiogenic shock (CS) develops in up to 10% of patients with ST-segment-elevation myocardial infarction and is associated with high mortality and morbidity rates. The objective of the current study was to generate a clinical scoring system that can be easily applied in the prehospital setting to predict the development of in-hospital CS among patients undergoing primary percutaneous coronary intervention for ST-segment-elevation myocardial infarction. The authors conducted a retrospective cohort study using prospective data from a dual hub-and-spoke health system. Logistic regression was used to assess the relationship between prespecified clinical predictors and the occurrence of in-hospital CS. Internal validation was conducted to assess the C statistic and calibration curve of the prediction model. The prediction model was converted to a risk score by scaling of the regression coefficients. From April 1, 2012, to December 31, 2020, there were 2736 consecutive patients with ST-segment-elevation myocardial infarction undergoing primary percutaneous coronary intervention. Of these, 415 (15.2%) developed CS. Eight strong predictors were independently associated with CS by multivariable analysis and used to develop a prediction model. The model achieved a C statistic of 0.87. The EARLY SHOCK risk scoring algorithm incorporates Emergency Medical Services Heart Rate and Systolic Blood Pressure, Age, Renal Replacement, Location of Infarction, Sugar (diabetes), Heart Failure, and Cardiac Arrest. The authors identified 8 clinical variables that strongly predict CS among patients with ST-segment-elevation myocardial infarction undergoing primary percutaneous coronary intervention. This has been developed into the EARLY SHOCK score, which can be easily applied in the prehospital setting to rapidly identify CS and enable shock team activation. External validation for the scoring system is pending for broader application.
AbstractList	Cardiogenic shock (CS) develops in up to 10% of patients with ST-segment-elevation myocardial infarction and is associated with high mortality and morbidity rates. The objective of the current study was to generate a clinical scoring system that can be easily applied in the prehospital setting to predict the development of in-hospital CS among patients undergoing primary percutaneous coronary intervention for ST-segment-elevation myocardial infarction. The authors conducted a retrospective cohort study using prospective data from a dual hub-and-spoke health system. Logistic regression was used to assess the relationship between prespecified clinical predictors and the occurrence of in-hospital CS. Internal validation was conducted to assess the C statistic and calibration curve of the prediction model. The prediction model was converted to a risk score by scaling of the regression coefficients. From April 1, 2012, to December 31, 2020, there were 2736 consecutive patients with ST-segment-elevation myocardial infarction undergoing primary percutaneous coronary intervention. Of these, 415 (15.2%) developed CS. Eight strong predictors were independently associated with CS by multivariable analysis and used to develop a prediction model. The model achieved a C statistic of 0.87. The EARLY SHOCK risk scoring algorithm incorporates Emergency Medical Services Heart Rate and Systolic Blood Pressure, Age, Renal Replacement, Location of Infarction, Sugar (diabetes), Heart Failure, and Cardiac Arrest. The authors identified 8 clinical variables that strongly predict CS among patients with ST-segment-elevation myocardial infarction undergoing primary percutaneous coronary intervention. This has been developed into the EARLY SHOCK score, which can be easily applied in the prehospital setting to rapidly identify CS and enable shock team activation. External validation for the scoring system is pending for broader application. Cardiogenic shock (CS) develops in up to 10% of patients with ST-segment-elevation myocardial infarction and is associated with high mortality and morbidity rates. The objective of the current study was to generate a clinical scoring system that can be easily applied in the prehospital setting to predict the development of in-hospital CS among patients undergoing primary percutaneous coronary intervention for ST-segment-elevation myocardial infarction.BACKGROUNDCardiogenic shock (CS) develops in up to 10% of patients with ST-segment-elevation myocardial infarction and is associated with high mortality and morbidity rates. The objective of the current study was to generate a clinical scoring system that can be easily applied in the prehospital setting to predict the development of in-hospital CS among patients undergoing primary percutaneous coronary intervention for ST-segment-elevation myocardial infarction.The authors conducted a retrospective cohort study using prospective data from a dual hub-and-spoke health system. Logistic regression was used to assess the relationship between prespecified clinical predictors and the occurrence of in-hospital CS. Internal validation was conducted to assess the C statistic and calibration curve of the prediction model. The prediction model was converted to a risk score by scaling of the regression coefficients.METHODSThe authors conducted a retrospective cohort study using prospective data from a dual hub-and-spoke health system. Logistic regression was used to assess the relationship between prespecified clinical predictors and the occurrence of in-hospital CS. Internal validation was conducted to assess the C statistic and calibration curve of the prediction model. The prediction model was converted to a risk score by scaling of the regression coefficients.From April 1, 2012, to December 31, 2020, there were 2736 consecutive patients with ST-segment-elevation myocardial infarction undergoing primary percutaneous coronary intervention. Of these, 415 (15.2%) developed CS. Eight strong predictors were independently associated with CS by multivariable analysis and used to develop a prediction model. The model achieved a C statistic of 0.87. The EARLY SHOCK risk scoring algorithm incorporates Emergency Medical Services Heart Rate and Systolic Blood Pressure, Age, Renal Replacement, Location of Infarction, Sugar (diabetes), Heart Failure, and Cardiac Arrest.RESULTSFrom April 1, 2012, to December 31, 2020, there were 2736 consecutive patients with ST-segment-elevation myocardial infarction undergoing primary percutaneous coronary intervention. Of these, 415 (15.2%) developed CS. Eight strong predictors were independently associated with CS by multivariable analysis and used to develop a prediction model. The model achieved a C statistic of 0.87. The EARLY SHOCK risk scoring algorithm incorporates Emergency Medical Services Heart Rate and Systolic Blood Pressure, Age, Renal Replacement, Location of Infarction, Sugar (diabetes), Heart Failure, and Cardiac Arrest.The authors identified 8 clinical variables that strongly predict CS among patients with ST-segment-elevation myocardial infarction undergoing primary percutaneous coronary intervention. This has been developed into the EARLY SHOCK score, which can be easily applied in the prehospital setting to rapidly identify CS and enable shock team activation. External validation for the scoring system is pending for broader application.CONCLUSIONSThe authors identified 8 clinical variables that strongly predict CS among patients with ST-segment-elevation myocardial infarction undergoing primary percutaneous coronary intervention. This has been developed into the EARLY SHOCK score, which can be easily applied in the prehospital setting to rapidly identify CS and enable shock team activation. External validation for the scoring system is pending for broader application. Background Cardiogenic shock (CS) develops in up to 10% of patients with ST‐segment–elevation myocardial infarction and is associated with high mortality and morbidity rates. The objective of the current study was to generate a clinical scoring system that can be easily applied in the prehospital setting to predict the development of in‐hospital CS among patients undergoing primary percutaneous coronary intervention for ST‐segment–elevation myocardial infarction. Methods The authors conducted a retrospective cohort study using prospective data from a dual hub‐and‐spoke health system. Logistic regression was used to assess the relationship between prespecified clinical predictors and the occurrence of in‐hospital CS. Internal validation was conducted to assess the C statistic and calibration curve of the prediction model. The prediction model was converted to a risk score by scaling of the regression coefficients. Results From April 1, 2012, to December 31, 2020, there were 2736 consecutive patients with ST‐segment–elevation myocardial infarction undergoing primary percutaneous coronary intervention. Of these, 415 (15.2%) developed CS. Eight strong predictors were independently associated with CS by multivariable analysis and used to develop a prediction model. The model achieved a C statistic of 0.87. The EARLY SHOCK risk scoring algorithm incorporates Emergency Medical Services Heart Rate and Systolic Blood Pressure, Age, Renal Replacement, Location of Infarction, Sugar (diabetes), Heart Failure, and Cardiac Arrest. Conclusions The authors identified 8 clinical variables that strongly predict CS among patients with ST‐segment–elevation myocardial infarction undergoing primary percutaneous coronary intervention. This has been developed into the EARLY SHOCK score, which can be easily applied in the prehospital setting to rapidly identify CS and enable shock team activation. External validation for the scoring system is pending for broader application.
Author	Kochan, Andrew Roston, Thomas M. Wong, Graham C. Fordyce, Christopher B. Yang, Cathevine Lee, Terry Berg, David D. Singer, Joel Grunau, Brian Barker, Madeleine Helmer, Jennie Cairns, John A.
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Snippet	Cardiogenic shock (CS) develops in up to 10% of patients with ST-segment-elevation myocardial infarction and is associated with high mortality and morbidity... Background Cardiogenic shock (CS) develops in up to 10% of patients with ST‐segment–elevation myocardial infarction and is associated with high mortality and...
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SubjectTerms	Aged cardiogenic shock Emergency Medical Services - methods Female Humans Male Middle Aged Percutaneous Coronary Intervention - adverse effects Predictive Value of Tests prehospital Retrospective Studies Risk Assessment - methods Risk Factors shock team Shock, Cardiogenic - diagnosis Shock, Cardiogenic - epidemiology Shock, Cardiogenic - etiology ST Elevation Myocardial Infarction - complications ST Elevation Myocardial Infarction - diagnosis ST Elevation Myocardial Infarction - surgery STEMI Time Factors
Title	Prehospital Prediction of Cardiogenic Shock Among Patients With ST‐Segment–Elevation Myocardial Infarction: The EARLY SHOCK Score
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