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性别、BMI 和空腹高血糖会影响代谢异常患者的单核细胞/高密度脂蛋白比值(MHR)指数。

Gender, BMI and fasting hyperglycaemia influence Monocyte to-HDL ratio (MHR) index in metabolic subjects.

机构信息

Department of Interdisciplinary Medicine, "Aldo Moro" University of Bari, Bari, Italy.

Department of Tissues and Organs Transplantation and Cellular Therapies, "Aldo Moro" University of Bari, Bari, Italy.

出版信息

PLoS One. 2020 Apr 28;15(4):e0231927. doi: 10.1371/journal.pone.0231927. eCollection 2020.

Abstract

Metabolic Syndrome (MS) is characterized by a low-grade inflammatory state causing an alteration of non-invasive indexes derived from blood count, namely monocyte-to-HDL ratio (MHR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR). We analyse a population of 771 subjects (394 controls and 377 MS patients) to evaluate the best predictive index of MS. The diagnosis of MS was made according to the 2006 criteria of the International Diabetes Federation (IDF). We performed ROC curve analyses to evaluate the best predictor index of MS. MHR cut-off value was used to classify the population in two different groups and to create the outcome variable of the Recursive Partitioning and Amalgamation (RECPAM) analysis. This method is a tree-structured approach that defines "risk profiles" for each group of dichotomous variables. We showed that MHR index is significantly linked to body mass index (BMI), waist circumference, creatinine, C-reactive protein (CRP), Erythrocyte Sedimentation Rate (ESR). ROC curve defined an MHR cut-off value of 6.4, which was able to identify two patient groups with significant differences in waist circumference, blood pressure, creatinine, estimated glomerular filtration rate and fasting plasma glucose. RECPAM analysis demonstrated that gender, BMI categorization and hyperglycaemia were the most important risk determinants of increased MHR index that can be considered bona fide a useful and easily obtainable tool to suggest the presence of peculiar metabolic features that predict MS.

摘要

代谢综合征(MS)的特征是低度炎症状态,导致来自血液计数的非侵入性指标发生改变,即单核细胞与高密度脂蛋白的比值(MHR)、中性粒细胞与淋巴细胞的比值(NLR)、血小板与淋巴细胞的比值(PLR)、淋巴细胞与单核细胞的比值(LMR)。我们分析了 771 名受试者(394 名对照和 377 名 MS 患者)的人群,以评估 MS 的最佳预测指标。MS 的诊断根据 2006 年国际糖尿病联合会(IDF)的标准进行。我们进行了 ROC 曲线分析,以评估 MS 的最佳预测指标。MHR 截断值用于将人群分为两组,并创建递归分区和合并(RECPAM)分析的结果变量。这种方法是一种树状结构方法,为每个二项变量组定义“风险特征”。我们表明,MHR 指数与体重指数(BMI)、腰围、肌酐、C 反应蛋白(CRP)、红细胞沉降率(ESR)显著相关。ROC 曲线定义了一个 MHR 截断值为 6.4,它能够识别出两组腰围、血压、肌酐、估算肾小球滤过率和空腹血糖有显著差异的患者。RECPAM 分析表明,性别、BMI 分类和高血糖是增加 MHR 指数的最重要风险决定因素,这可以被认为是一个有用且易于获得的工具,可以提示存在预测 MS 的特殊代谢特征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e3f0/7188261/169851faf841/pone.0231927.g001.jpg

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