Overview of guidelines for the management of dyslipidemia: EU perspectives

Abstract

Modern medicine is characterized by a continuous genesis of evidence making it very difficult to translate the latest findings into a better clinical practice. Clinical practice guidelines (CPG) emerge to provide clinicians evidence-based recommendations for their daily clinical practice. However, the high number of existing CPG as well as the usual differences in the given recommendations usually increases the clinician’s confusion and doubts. It has apparently been the case for the 2013 American College of Cardiology/American Heart Association (ACC/AHA) Guideline on the Treatment of Blood Cholesterol. These CPG proposed new and controversial concepts that have usually been considered an antagonist shift respective to European CPG. The most controversial published proposals are: 1) to consider evidence just from randomized clinical trials, 2) creation of a new cardiovascular (CV) risk calculator, 3) to consider reducing CV risk instead of reducing low-density lipoprotein cholesterol (LDLc) as the target of the treatment, and 4) consideration of statins as the only drugs for treatment. A deep analysis of the 2013 American College of Cardiology/American Heart Association CPG and comparison with the European ones show that from a practical and clinical point of view, there are more similarities than differences. To further help clinicians in their daily work, in the present globalized world, it is time to discuss and adopt a mutually agreed upon document created by both sides of the Atlantic. Probably it is not a short-term solution. Meanwhile, taking advantage of the similarities, the recommended practical attitude for the daily clinical practice should be based on 1) early detection of people with increased CV risk promoting the use of validated local scales, 2) reinforce the mainstream importance of nonpharmacological treatment, and 3) need for periodically monitoring response with analytical parameters (LDL or non-highdensity lipoprotein cholesterol) and global CV risk estimation. Technological solutions such as the big data technology could help to obtain high-quality evidence in an intermediate term.