Predictors of ventricular fibrillation or cardiac arrest in patients hospitalized for acute myocardial infarction

Abstract

A community-wide study of patients hospitalized with acute myocardial infarction in metropolitan Baltimore was conducted to examine socio-demographic and clinical characteristics in association with ventricular fibrillation and cardiac arrest (VF/CA). Multivariate analyses revealed that variables significantly associated with occurrence of VF/CA included older age (60 years or older), male sex, and a history of cigarette smoking. These factors allow the identification of subgroups of patients hospitalized with acute myocardial infarction at high risk for the subsequent development of VF/CA, in whom prophylactic therapy and close surveillance are especially recommended

Association of Impaired Thrombolysis In Myocardial Infarction Myocardial Perfusion Grade With Ventricular Tachycardia and Ventricular Fibrillation Following Fibrinolytic Therapy for ST-Segment Elevation Myocardial Infarction

“…Identification of simply assessed clinical variables associated with subsequent ventricular tachycardia (VT) and ventricular fibrillation (VF) could prove useful in the triage of patients to more aggressive pharmacologic-or device-based therapies. Previous observational studies have demonstrated that traditional cardiac risk factors, such as age, hypertension, and tobacco use, are associated with an increased risk of VT/VF after MI (3)(4)(5).…”

“…A number of epidemiologic risk factors associated with ventricular arrhythmia have been observed (3)(4)(5). Risk factor assessment is ever-changing as modern pharmacologic therapy for coronary artery disease and heart failure change (25).…”

The length of hospitalization after acute myocardial infarction determined by risk calculation.

“…A recent multivariate study identified age, sex, and smoking as the most important variables for late cardiac arrest. 39 Because the important prognostic variables are identical to clinically important variables, the time of discharge could be determined by the presence or absence of these variables alone. However, our proposed model can quantitate the risk for an individual patient based on a combination of important variables for three end points.…”