Association between atorvastatin and sarcopenia: a study based on NHANES and FAERS databases

作者
Hao Zhang,Ping Zhang,Xi Luo,Li Zhao,Hua Huang,Qi Ou
出处
期刊:Naunyn-schmiedebergs Archives of Pharmacology [Springer Science+Business Media]
标识
DOI:10.1007/s00210-025-04559-0
摘要

Post-marketing surveillance data suggest a potential link between atorvastatin use and sarcopenia. However, further large-scale observational studies are needed to confirm this preliminary finding. This study aims to comprehensively investigate the relationship between atorvastatin exposure and sarcopenia, with the goal of providing more accurate safety and efficacy profiles to guide its clinical use. We utilized two primary datasets: the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2018 and the Food and Drug Administration Adverse Event Reporting System (FAERS) from 2004 to 2018. Using a multi-step analytical approach that included descriptive statistical analysis, multivariable logistic regression, and receiver operating characteristic (ROC) curve analysis, we systematically assessed the relationship between atorvastatin exposure and the incidence of sarcopenia. In the NHANES cohort analysis, after adjusting for demographic variables, lifestyle factors, and other confounders in the multivariable logistic regression model, atorvastatin use was associated with an increased risk of sarcopenia (OR = 2.21; 95% CI: 1.07-4.55; p = 0.032). An analysis of the FAERS database identified 13,625 adverse event reports related to atorvastatin, of which 5370 specifically documented myasthenia-related events. Independent analyses from both population-based epidemiological surveys and pharmacovigilance systems consistently indicate that atorvastatin use may increase the risk of sarcopenia. Based on these findings, we recommend that healthcare providers implement comprehensive risk communication strategies before prescribing atorvastatin, with particular emphasis on the need for regular musculoskeletal assessments in patients undergoing long-term statin therapy.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
科研通AI6.2应助yixi采纳,获得10
刚刚
清脆冬日完成签到 ,获得积分10
刚刚
xing_xing给孙明丽的求助进行了留言
1秒前
Akim应助快乐的千兰采纳,获得10
1秒前
tiptip应助NN采纳,获得30
1秒前
1秒前
1秒前
YWK完成签到,获得积分10
1秒前
雪霁完成签到,获得积分10
1秒前
2秒前
科研通AI6.2应助jacob采纳,获得10
2秒前
66666完成签到,获得积分10
3秒前
3秒前
wqy完成签到 ,获得积分10
3秒前
3秒前
令狐雪莲发布了新的文献求助20
4秒前
老曹完成签到,获得积分10
4秒前
如意半凡完成签到,获得积分10
4秒前
隐形的绣连完成签到,获得积分10
5秒前
明月发布了新的文献求助10
5秒前
儒雅的如松完成签到 ,获得积分10
5秒前
6秒前
luckypig完成签到,获得积分20
6秒前
hkh发布了新的文献求助10
6秒前
tiptip应助NN采纳,获得30
6秒前
仧目一叶完成签到 ,获得积分10
6秒前
谦让的慕凝完成签到 ,获得积分10
7秒前
雨竹完成签到 ,获得积分10
7秒前
长脚蟹完成签到,获得积分10
8秒前
yangts2021发布了新的文献求助10
8秒前
8秒前
小蘑菇应助明亮向日葵采纳,获得30
9秒前
kiwi完成签到,获得积分10
9秒前
9秒前
优美的胡萝卜完成签到,获得积分10
9秒前
今后应助林森采纳,获得10
9秒前
卡佳完成签到,获得积分10
11秒前
tiptip应助NN采纳,获得30
12秒前
丁丁当当发布了新的文献求助10
12秒前
高分求助中
Markov Chain Monte Carlo 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
政治传播过程中的外交与说服——以中苏友好协会为例的历史考察 566
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7579814
求助须知:如何正确求助?哪些是违规求助? 9159288
关于积分的说明 19594255
捐赠科研通 7162441
什么是DOI,文献DOI怎么找? 3265750
关于科研通互助平台的介绍 2430774
邀请新用户注册赠送积分活动 2256569