What is the clinical evidence from this study?

Study design: Observational. Population: acute myocardial infarction (n=243440). Intervention: Clinical risk model. Primary outcome: In-hospital mortality (C statistic 0.88).

What question did this study set out to answer?

To develop and validate a clinical risk model predicting in-hospital mortality for acute myocardial infarction patients.

June 5, 2026

Predicting In-Hospital Mortality in Patients With Acute Myocardial Infarction

Key Result

A clinical risk model accurately predicted in-hospital mortality (overall rate 4.6%) in patients with acute myocardial infarction, demonstrating good calibration and a C statistic of 0.88.

Key Points

To develop and validate a clinical risk model predicting in-hospital mortality for acute myocardial infarction patients.
Utilized patient data from the ACTION Registry-GWTG (2012-2013) involving 243,440 patients across 655 hospitals.
Developed a multivariate hierarchical logistic regression model to predict mortality.
Created a simplified risk score for prospective risk stratification.
In-hospital mortality rate was 4.6%.
Multiple factors including age and heart rate were significantly associated with mortality.
The model demonstrated a C statistic of 0.88, indicating good predictive accuracy.

Study Design

Type

Observational (n=243,440)

Multicenter

Yes

Structured PICO

Does a parsimonious clinical risk model accurately predict in-hospital mortality in contemporary patients with acute myocardial infarction?

Population

243,440 patients with acute myocardial infarction from 655 hospitals, used to develop and validate a risk model for in-hospital mortality.

Exposure

Development and validation of a parsimonious patient-level clinical risk model

Outcome

In-hospital mortalityhard clinical

A parsimonious risk model using presentation characteristics accurately predicts in-hospital mortality in contemporary AMI patients, enabling risk adjustment and stratification.

Main Result

Effect estimate: C statistic 0.88

Abstract

BACKGROUND: As a foundation for quality improvement, assessing clinical outcomes across hospitals requires appropriate risk adjustment to account for differences in patient case mix, including presentation after cardiac arrest. OBJECTIVES: The aim of this study was to develop and validate a parsimonious patient-level clinical risk model of in-hospital mortality for contemporary patients with acute myocardial infarction. METHODS: Patient characteristics at the time of presentation in the ACTION (Acute Coronary Treatment and Intervention Outcomes Network) Registry-GWTG (Get With the Guidelines) database from January 2012 through December 2013 were used to develop a multivariate hierarchical logistic regression model predicting in-hospital mortality. The population (243,440 patients from 655 hospitals) was divided into a 60% sample for model derivation, with the remaining 40% used for model validation. A simplified risk score was created to enable prospective risk stratification in clinical care. RESULTS: The in-hospital mortality rate was 4.6%. Age, heart rate, systolic blood pressure, presentation after cardiac arrest, presentation in cardiogenic shock, presentation in heart failure, presentation with ST-segment elevation myocardial infarction, creatinine clearance, and troponin ratio were all independently associated with in-hospital mortality. The C statistic was 0.88, with good calibration. The model performed well in subgroups based on age; sex; race; transfer status; and the presence of diabetes mellitus, renal dysfunction, cardiac arrest, cardiogenic shock, and ST-segment elevation myocardial infarction. Observed mortality rates varied substantially across risk groups, ranging from 0.4% in the lowest risk group (score 59). CONCLUSIONS: This parsimonious risk model for in-hospital mortality is a valid instrument for risk adjustment and risk stratification in contemporary patients with acute myocardial infarction.

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