Inspecting the association between metabolic obese phenotypes and heart failure subtypes risk

研究代谢性肥胖表型与心力衰竭亚型风险之间的关联

阅读:1

Abstract

AIM: Obesity and metabolic unhealth don't always co-exist. The relation between phenotypes derived from metabolic obese status and heart failure (HF) subtypes categorized by left ventricular ejection fraction (LVEF) is unclear. We aimed to investigate the association between metabolic obese phenotypes and future HF subtypes risk. OBJECTIVES: A total of 9791 participants from the ARIC study were classified into phenotypes based on obese and metabolic status: metabolically healthy non-obesity (MHNO), metabolically healthy obesity (MHO), metabolically unhealthy non-obesity (MUNO) and metabolically unhealthy obesity (MUO). METHODS: Cox regression models were applied to explore the relationship between metabolic obese phenotypes and risk of HF with preserved ejection fraction (HFpEF, LVEF ≥ 50 %) and HF with reduced or mid-range ejection fraction (HFrEF/HFmrEF, LVEF < 50 %) in total population and subgroups. Associations between phenotypes transition over time and HF subtypes risk were further analyzed. RESULTS: Compared with MHNO participants, HFpEF risk was increased in MHO (hazard ratio and 95 % confidence interval, 1.77 [1.39-2.26]), MUNO (1.59 [1.27-1.99]) and MUO (2.77 [2.25-3.40]), while HFrEF/HFmrEF risk were higher in MUNO (1.61 [1.27-2.04]) and MUO (2.19 [1.74-2.75]) participants. Subgroup analyses revealed that the associations between metabolic obese phenotypes and HF subtypes risk were more predominant in participants < 55 years old and female. Persistent MHO, MUNO or MUO were associated with increased HFpEF risk and almost any transition to MUO resulted in increased risk of all HF subtypes. CONCLUSIONS: MUNO and MUO were associated with all HF subtypes risk, while MHO was only associated with future HFpEF rather than HFrEF/HFmrEF.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。