Association Between BMI and Cardiovascular Benefits After More Intensive LDL-C Lowering Strategy: A Systematic Review and Meta-Analysis

Social Science Research Network(2021)

引用 0|浏览0
暂无评分
摘要
Objective: To assess the influencing factors, especially BMI level contributing to the cardiovascular benefits of more intensive LDL-C lowering strategy. Methods: We systematically searched MEDLINE, Cochrane Central Register of Controlled Trials, Web of Science, ClinicalTrials and Embase for randomized controlled trials of statins, ezetimibe, proprotein convertase subtilisin-kexin type 9 inhibitors, ATP Citrate Lyase inhibitors published before April, 2021. Results: A total of 263787 participants from 33 trials were included. BMI level, baseline LDL-C level and type of lipid-lowering agents are the main factors affecting the cardiovascular benefits from more intensive LDL-C lowering strategies. Among them, the influence of BMI is more prominent. Each 1kg/m2 increase in BMI level reduced the benefit of cardiovascular mortality by 8% (RR 1.08, 95% CI 1.03-1.13), and this effect still exists when only statins are used as the LDL-C lowering strategy. The same trend was also found in myocardial infarction (RR 1.06, 95% CI 1.01-1.11) and revascularization events (RR 1.06, 95% CI 1.02-1.10) by 6%, respectively. Compared to 44% reduction of cardiovascular mortality when the BMI level was less than 25kg/m2 (RR 0.56, 95%CI 0.36-0.86), the reduction gradually vanished as the BMI increased, no benefit of cardiovascular mortality was found when the BMI was higher than 28kg/m2, this cut point is 29kg/m2 in myocardial infarction and 30kg/m2 in revascularization events. Conclusions: With the increase of BMI level, some cardiovascular benefits of intensive LDL-C lowering strategy gradually vanished. Funding Information: This work was partially supported by the National Natural Science Foundation of China (No. 81570732, Shaohua Wang and No. 81870568, Shaohua Wang). Declaration of Interests: The authors declare that they have no competing interests.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要