We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

HospiMedica

Download Mobile App
Recent News AI Critical Care Surgical Techniques Patient Care Health IT Point of Care Business Focus

Patient-Level Model Predicts In-Hospital Cardiac Mortality

By HospiMedica International staff writers
Posted on 18 Aug 2016
Researchers at Yale University School of Medicine (Yale; New Haven, CT, USA), Duke University (Durham, NC, USA), and other institutions reviewed patient admittance characteristics in the Acute Coronary Treatment and Intervention Outcomes Network (ACTION) registry database from January 2012 through December 2013, in order to develop a multivariate hierarchical logistic regression model to predict in-hospital 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.

Related Links:
Yale University School of Medicine
Duke University

Gold Member
Real-Time Diagnostics Onscreen Viewer
GEMweb Live
Gold Member
STI Test
Vivalytic Sexually Transmitted Infection (STI) Array
Silver Member
Compact 14-Day Uninterrupted Holter ECG
NR-314P
New
Soft-Tissues Biopsy Needle
MR-CLEAR

Latest Critical Care News

Stretchable Microneedles to Help In Accurate Tracking of Abnormalities and Identifying Rapid Treatment

Machine Learning Tool Identifies Rare, Undiagnosed Immune Disorders from Patient EHRs

On-Skin Wearable Bioelectronic Device Paves Way for Intelligent Implants