Risk Factors Associated with Statin-Associated Muscle Symptoms in Patients Attending a Specialized Regional Lipid Clinic. (19th March 2021)

• Record Type: Journal Article
• Authors: Saeed, M. K.; Shah, J.; Damani, R.; Rahman, F.; Patel, P.; Gupta, P.
• Other Names: Jauhiainen Matti Academic Editor.
• Is Part Of: Journal of lipids. Volume 2021(2021)
• Publication Date: 2021-03-19
• Subjects: Lipids -- Periodicals; Lipids; Lipids; Electronic journals; Periodicals; Periodicals; 572.57
• DOI: 10.1155/2021/8882706
• Languages: English
• ISSNs: 2090-3030

Abstract

Abstract : Background . Statin-associated muscle symptoms (SAMS) are the major side effects reported for statins. Data from previous studies suggest that 7–29% of patients on statin had associated muscle symptoms. In the UK, there is a lack of corresponding data on SAMS and factors associated with the development of SAMS. Objective . This analysis is aimed at establishing the prevalence of SAMS and identifying major contributory risk factors in patients attending a lipid clinic. Methods . Clinical records of 535 consecutive patients, who visited the lipid clinic in the University Hospitals of Leicester, were studied retrospectively between 2009 and 2012. SAMS were defined by the presence of muscle symptoms with two or more different statins. Patients who reported muscle symptoms to statin with one or no rechallenge were excluded. The association of SAMS with clinical characteristics such as age and BMI, sex, smoking, excess alcohol, comorbidities, and medications was tested for statistical significance. A binomial logistic regression model was applied to adjust for risk factors significantly associated with SAMS. Results . The prevalence of SAMS was found to be 11%. On unadjusted analysis, the mean age of patients who had SAMS was significantly higher than those without SAMS (59.4 ± 10.5 years vs. 50.3 ± 13.4 years, respectively, P < 0.001 ). Nonsmokers were more likely to develop SAMS in comparison to active smokers (P = 0.037 ). Patients taking antihypertensive medications were more likely to develop SAMS (P = 0.010 ). In binomial logistic regression analysis, only age was positively and significantly associated with SAMS after adjusting for other risk factors (β = 0.054, P = 0.001 ). Conclusion . To the best of our knowledge, this study is the largest cohort of patients with SAMS in the United Kingdom. Our data suggest that the prevalence of SAMS is 11% and increased age is a risk factor associated with the development of SAMS in our cohort of patients.