A Step-by-Step Explanation on How to Apply the Distributional Data Analysis Tool of the Glucose Density (GD) with Collected Finger-Piercing Daily Glucose Data over 8.5 Months for Two Type 2 Diabetes Patients Based on GH-Method: Math-Physical Medicine (No. 517)

Abstract

Gerald C Hsu

Recently, the author conducted a series of medical research projects by applying a distributional data density analysis tool on his weight, glucose, blood pressure (BP), and heart conditions, while using his collected big data regarding certain biomarker’s density distribution for certain selected years. In this particular article, he explains the step-by-step procedures on how to apply the Biomarker Density % (BMD%) tool, especially the glucose density % (GD%) to help with the type 2 diabetes (T2D) diagnosis and treatment using two T2D patients finger-piercing daily glucose (eAG) data as an illustrative example. There is no need to introduce the background of these patients since their glucose data comparison is the focus. In summary, the author outlines the step-by-step process on how to apply the GD% concept and tool using two T2D clinical cases. Patient A has a higher hyperglycemic risk, while Patient B has a lower risk of hypoglycemia. Overall, Patient B, with a mean glucose of 105 mg/dL, has better diabetes control compared Patient A, with a mean glucose of 124 mg/dL. Once the readers learn the concept and method of these BMD tools, they can apply them to patients with different chronic diseases. Those who have an interest in learning more can visit the author’s website: (www. eclairemd.com) and search for articles with the key word “density”.

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