Cardiovascular (CV) disease is a leading cause of death worldwide, accounting for approximately 31.4% of deaths globally in 2012. It is estimated that, from 1980 to 2000, reduction in total cholesterol accounted for a 33% decrease in coronary heart disease (CHD) deaths in the United States. In other developed countries, similar decreases in CHD deaths (ranging from 19%-46%) have been attributed to reduction in total cholesterol. Low-density lipoprotein cholesterol (LDL-C) has now largely replaced total cholesterol as a risk marker and the primary treatment target for hyperlipidemia. Reduction in LDL-C levels by statin-based therapies has been demonstrated to result in a reduction in the risk of nonfatal CV events and mortality in a continuous and graded manner over a wide range of baseline risk and LDL-C levels. This article provides a review of (1) the relationship between LDL-C and CV risk from a biologic, epidemiologic, and genetic standpoint; (2) evidence-based strategies for LDL-C lowering; (3) lipid-management guidelines; (4) new strategies to further reduce CV risk through LDL-C lowering; and (5) population-level and health-system initiatives aimed at identifying, treating, and lowering lifetime LDL-C exposure.
Large gaps exist between recommendations and current practice regarding LLT in the population with ASCVD. In our model that assumes no LLT intolerance and full adherence, intensification of oral LLT could achieve an LDL-C level of less than 70 mg/dL in most patients, with only a modest percentage requiring a PCSK9 inhibitor.
PurposeThe Statin-Associated Muscle Symptom Clinical Index (SAMS-CI) is a method for assessing the likelihood that a patient’s muscle symptoms (e.g., myalgia or myopathy) were caused or worsened by statin use. The objectives of this study were to prepare the SAMS-CI for clinical use, estimate its inter-rater reliability, and collect feedback from physicians on its practical application.MethodsFor content validity, we conducted structured in-depth interviews with its original authors as well as with a panel of independent physicians. Estimation of inter-rater reliability involved an analysis of 30 written clinical cases which were scored by a sample of physicians. A separate group of physicians provided feedback on the clinical use of the SAMS-CI and its potential utility in practice.ResultsQualitative interviews with providers supported the content validity of the SAMS-CI. Feedback on the clinical use of the SAMS-CI included several perceived benefits (such as brevity, clear wording, and simple scoring process) and some possible concerns (workflow issues and applicability in primary care). The inter-rater reliability of the SAMS-CI was estimated to be 0.77 (confidence interval 0.66–0.85), indicating high concordance between raters. With additional provider feedback, a revised SAMS-CI instrument was created suitable for further testing, both in the clinical setting and in prospective validation studies.ConclusionsWith standardized questions, vetted language, easily interpreted scores, and demonstrated reliability, the SAMS aims to estimate the likelihood that a patient’s muscle symptoms were attributable to statins. The SAMS-CI may support better detection of statin-associated muscle symptoms in clinical practice, optimize treatment for patients experiencing muscle symptoms, and provide a useful tool for further clinical research.Electronic supplementary materialThe online version of this article (doi:10.1007/s10557-017-6723-4) contains supplementary material, which is available to authorized users.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.