谷歌浏览器插件
订阅小程序
在清言上使用

控制糖尿病心血管风险的行动(ACCORD)试验中的血脂变异性和微血管并发症风险:一项事后分析

Journal of Diabetes(2022)

引用 0|浏览4
暂无评分
摘要
Abstract Background Greater lipid variability may cause adverse health events among diabetic patients. We aimed to examine the effect of lipid variability on the risk of diabetic microvascular outcomes among type 2 diabetes mellitus patients. Methods We assessed the association between visit‐to‐visit variability (measured by variability independent of mean) in high‐density lipoprotein (HDL) cholesterol, low‐density lipoprotein‐cholesterol (LDL), triglyceride, and remnant cholesterol (RC) measurements among participants involved in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study and the risk of incident microvascular outcomes, including nephropathy, neuropathy, and retinopathy. Cox proportional hazards models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs), adjusted for potential confounders. Results There were 2400, 2470, and 2468 cases of nephropathy, neuropathy, and retinopathy during a follow‐up period of 22 600, 21 542, and 26 701 person‐years, respectively. Higher levels of HDL, triglyceride, and RC variability were associated with an increased risk of incident nephropathy and neuropathy. Compared with the lowest quartile, the fully adjusted HRs (95% CI) for the highest quartile of HDL, triglyceride, and RC variability for nephropathy risk were 1.57 (1.22, 2.01), 1.50 (1.18, 1.92), and 1.40 (1.09, 1.80), respectively; and for neuropathy, the corresponding risks were 1.36 (1.05, 1.75), 1.47 (1.14, 1.91), and 1.35 (1.04, 1.74), respectively. Null association was observed between LDL variability and all microvascular complications. Additionally, all associations of variability in the other lipids with retinopathy risk were null. Conclusion Among individuals with type 2 diabetes mellitus, HDL, triglyceride, and RC variability were associated with increased risks of nephropathy and neuropathy but not retinopathy. Trial registration: ClinicalTrials.gov., no. NCT00000620.
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