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Towards the insulin resistance and obesity diagnosis: A dimensional analysis approach

机译:朝向胰岛素抵抗和肥胖诊断:尺寸分析方法

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Diabetes mellitus and cardiovascular diseases are ailments related to insulin resistance (IR) and obesity. The existing methods for IR and obesity diagnosis are the HOMA-IR and body mass index (BMI), respectively. Those methods have limitations in the diagnosis. The aim of this research is to propose dimensionless indexes that can diagnose subjects with IR and obesity using anthropometrics and biochemical variables (waist circumference, height, weight, systolic blood pressure, diastolic blood pressure and triglycerides). Three dimensionless indexes, designed from the π Vaschy-Buckingham theorem, were assessed using receiver operating characteristic (ROC) curves and a database of 829 subjects. The index π1, constructed with the variables: waist circumference, triglycerides height and weight; obtained a better performance as classifier of IR and obesity, presenting an area under the ROC curve of 0.78, sensitivity of 0.82 and specificity of 0.68 for IR diagnosis, and an area under the ROC curve of 0.68, sensitivity of 0.66 and specificity of 0.65 for obesity diagnosis. The π1 dimensionless index designed in this study is a simple method that allows diagnosing two pathologies from variables that can be collected in a routine medical examination.
机译:糖尿病和心血管疾病是与胰岛素抵抗(IR)和肥胖有关的疾病。 IR和肥胖诊断的现有方法分别是HOMA-IR和体重指数(BMI)。这些方法对诊断有局限性。该研究的目的是提出使用人类测量剂和生物化学变量(腰围,高度,体重,收缩压,舒张压和甘油三酯)诊断患有IR和肥胖的受试者的无量纲指标。使用接收器操作特性(ROC)曲线和829个科目的数据库来评估由πvaschy-buckingham定理设计的三维无量纲指标。索引π. 1 ,用变量构建:腰围,甘油三酯高度和重量;获得了作为IR和肥胖的分类器的更好的性能,在ROC曲线下呈现0.78的区域,敏感性为0.82,红外诊断的特异性为0.68,ROC曲线下的面积为0.68,灵敏度为0.66,特异性为0.65肥胖诊断。 π 1 本研究中设计的无量纲指数是一种简单的方法,允许诊断可以从可以在常规体检中收集的变量的两个病理学。

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