Association between the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and mortality in patients with metabolic dysfunction-associated steatotic liver disease (MASLD): data from the NHANES III (1988-1994).

IF 4.1 2区 医学 Q2 NUTRITION & DIETETICS
Ying Zhang, Peng-Yu Luo, Yu-Na Tang, Jing Wang, Shuai Gao, Yu-Chen Fan, Kai Wang
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引用次数: 0

Abstract

Background: The prognostic value of the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) in patients with metabolic dysfunction-associated steatotic liver disease (MASLD) remains unclear. This study aimed to evaluate the associations between the NHHR and all-cause and cause-specific mortality in patients with MASLD.

Methods: Data for this study were obtained from the National Health and Nutrition Examination Survey (NHANES III and the National Death Index (NDI). The NHHR was calculated according to the formula. The results of mortality associated with the NDI were recorded as of December 31, 2019. We used a multivariate Cox proportional hazard model and restricted cubic spline (RCS) regression to assess the associations between the NHHR and all-cause and cause-specific mortality. In addition, subgroup analyses were performed to explore the relationships between the NHHR and all-cause and cause-specific mortality.

Results: This study included 3155 patients with a definite diagnosis of MASLD. A total of 1,381 (43.8%) patients with MASLD died, and 1,774 (56.2%) survived. Multivariate Cox proportional hazards model analysis showed that NHHR was not significantly associated with all-cause mortality in MASLD patients. The RCS curve showed a significant nonlinear trend between the NHHR and all-cause mortality in patients with MASLD. Subgroup analysis revealed that the NHHR was better suited to predict cardiovascular mortality in patients without advanced fibrosis.

Conclusions: Our study revealed the clinical value of the NHHR in the prediction of mortality in the MASLD population. The NHHR can be used as a biomarker for follow-up in people without advanced fibrosis.

非高密度脂蛋白胆固醇与高密度脂蛋白胆固醇比值(NHHR)与代谢功能障碍相关脂肪变性肝病(MASLD)患者死亡率之间的关系:来自NHANES III(1988-1994)的数据
背景:非高密度脂蛋白胆固醇与高密度脂蛋白胆固醇比值(NHHR)在代谢功能障碍相关脂肪变性肝病(MASLD)患者中的预后价值尚不清楚。本研究旨在评估NHHR与MASLD患者全因死亡率和病因特异性死亡率之间的关系。方法:本研究的数据来自国家健康与营养调查(NHANES III)和国家死亡指数(NDI)。根据公式计算NHHR。截至2019年12月31日,记录了与NDI相关的死亡率结果。我们使用多变量Cox比例风险模型和限制性三次样条(RCS)回归来评估NHHR与全因死亡率和病因特异性死亡率之间的关系。此外,还进行了亚组分析,以探讨NHHR与全因死亡率和病因特异性死亡率之间的关系。结果:本研究纳入3155例明确诊断为MASLD的患者。共有1381例(43.8%)MASLD患者死亡,1774例(56.2%)存活。多因素Cox比例风险模型分析显示,NHHR与MASLD患者的全因死亡率无显著相关。RCS曲线显示MASLD患者NHHR与全因死亡率之间存在显著的非线性趋势。亚组分析显示,NHHR更适合于预测无晚期纤维化患者的心血管死亡率。结论:我们的研究揭示了NHHR在预测MASLD人群死亡率方面的临床价值。NHHR可作为无晚期纤维化患者随访的生物标志物。
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来源期刊
Nutrition & Metabolism
Nutrition & Metabolism 医学-营养学
CiteScore
8.40
自引率
0.00%
发文量
78
审稿时长
4-8 weeks
期刊介绍: Nutrition & Metabolism publishes studies with a clear focus on nutrition and metabolism with applications ranging from nutrition needs, exercise physiology, clinical and population studies, as well as the underlying mechanisms in these aspects. The areas of interest for Nutrition & Metabolism encompass studies in molecular nutrition in the context of obesity, diabetes, lipedemias, metabolic syndrome and exercise physiology. Manuscripts related to molecular, cellular and human metabolism, nutrient sensing and nutrient–gene interactions are also in interest, as are submissions that have employed new and innovative strategies like metabolomics/lipidomics or other omic-based biomarkers to predict nutritional status and metabolic diseases. Key areas we wish to encourage submissions from include: -how diet and specific nutrients interact with genes, proteins or metabolites to influence metabolic phenotypes and disease outcomes; -the role of epigenetic factors and the microbiome in the pathogenesis of metabolic diseases and their influence on metabolic responses to diet and food components; -how diet and other environmental factors affect epigenetics and microbiota; the extent to which genetic and nongenetic factors modify personal metabolic responses to diet and food compositions and the mechanisms involved; -how specific biologic networks and nutrient sensing mechanisms attribute to metabolic variability.
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