Patient-Level Model Predicts In-Hospital Cardiac Mortality

The study population, which included 243,440 patients from 655 hospitals, was divided into a 60% sample for model derivation, with the remaining 40% used for model validation.

The researchers found that in-hospital mortality was 4.6%, with independent associations for age, heart rate, systolic blood pressure, presentation after cardiac arrest, cardiogenic shock, and heart failure, presentation with ST-segment elevation myocardial infarction (STEMI), creatinine clearance, and troponin ratio. Upon model validation, the researchers found that it performed well in subgroups based on age, sex, race, transfer status, and presence of diabetes mellitus, renal dysfunction, cardiac arrest, cardiogenic shock, and STEMI. The study was published in the August 9, 2016, issue of the Journal of the American College of Cardiology (JACC).

“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,” concluded lead author Robert McNamara, MD, of Yale, and colleagues. “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.”

MI occurs following an ischemia that causes damage to heart muscle. The most common symptom is chest pain or discomfort, which may travel into the shoulder, arm, back, neck, or jaw. Other symptoms may include shortness of breath, nausea, feeling faint, a cold sweat, or fatigue. Most MIs occur as a result of coronary artery disease (CAD), with risk factors including high blood pressure, smoking, diabetes, lack of exercise, obesity, high blood cholesterol, poor diet, and excessive alcohol intake.

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Yale University School of Medicine
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