Sudden cardiac death: Lessons from multicenter clinical trials

Abstract

Sudden cardiac death is a major epidemiologic problem that accounts for 300,000 to 400,000 deaths in the United States yearly. Most patients die from a sustained ventricular tachyarrhythmia and nearly all patients have some form of heart disease, usually coronary artery disease. There are many pathophysiologic mechanisms of ventricular fibrillation, including such disparate etiologies as ischemia and long QT syndrome. Appropriate treatment of survivors of cardiac arrest is critical to prevent recurrent episodes. The diverse etiologies preclude a single approach to this problem, and the assessment and treatment of these patients must be done on an individual basis. Importantly, most patients do not survive their first episode of cardiac arrest; therefore, prospective data are needed to identify patients at high risk for sudden cardiac death. The ‘best” approach to identify the patient at high risk for sudden cardiac death, or to treat survivors of cardiac arrest, has not yet been determined. Controlled clinical trials yield important information regarding treatment strategies. Several such trials have been completed or are ongoing in patients who have sustained ventricular tachyarrhythmias or who are considered at high risk for sudden death. The purpose of this symposium was to review information from these trials to determine how they have affected clinical practice or might alter treatment strategies in the future. Senior investigators with substantial experience in randomized clinical trials were asked to provide a manuscript for publication. Dr. Camm presents his heuristic views on clinical trials of arrhythmia management. He reminds us that the data from randomized clinical trials notwithstanding, personal experience and information from nonrandomized trials are also useful in making clinical decisions for patients. He raises issues regarding the scope of any single trial and the appropriateness of the endpoints selected. A detailed discussion of enrollment bias is presented with specific examples from the literature. The interpretation of clinical trials is also reviewed. Dr. Camm discusses important questions concerning extrapolation of data from a