Viscoelastic Glucose Theory (VGT #28) & Nonlinear Plastic Glucose Theory (NPGT #7): Nonlinear Dynamic Plastic and Viscoplastic Glucose Behaviors Versus Linear Elastic Glucose Behavior of Postprandial Plasma Glucose (PPG) Waveforms over a 3.8-Year Period from 5/8/2018 to 2/18/2022 along with the Plastic PPG Waveforms Impact on the Cardiovascular Disease Risk Probability Based on the GH-Method: Math-Physical Medicine (No. 609)

Abstract

Recently, the author applied theories of elasticity, plasticity, viscoelasticity, and viscoplasticity from engineering and perturbation theory from quantum mechanics, along with the wave theory and energy theory from physics to conduct his biomedical research on certain output biomarkers, such as glucose (symptoms or behaviors) resulting from a selected input biomarker, such as the carbs/sugar amount, exercise level, or others (causes or stressors). In this article, he chose his synthesized postprandial plasma glucose (PPG) data and waveform over the past 3.8 years as the strain (ε or output, symptom). Since 5/8/2018, he has been utilizing a continuously monitoring glucose sensor (CGM) device to collect 96 glucose data each day and 13 glucose data each meal at 15-minute time intervals. In order to investigate and learn the behaviors of the strain (ε) or PPG, and its stress (σ) or input/cause as defined to be the estimated average glucose (eAG) change rate multiplied by a selected viscosity factor (η), which is the carbs/sugar intake amount. In this study, he selected “elastic” PPG case with average “Finger-piercing PPG <120 mg/dL along with four “plastic” PPG cases, >120 mg/dL, >140 mg/dL, >180 mg/dL, and >200 mg/dL. The procedure of the analysis contains four steps. Step 1, he draws the 5 PPG (1 elastic and 4 plastic) waveforms in a timedomain (TD) with 15-minutes time interval within a 3-hour time span. Step 2, he calculates the stress values to draw the corresponding stress-strain diagram in a spatial-domain (SD). Step 3, he calculates 4 predicted plastic PPG values using the viscoelastic perturbation model. Step 4, he calculates the corresponding cardiovascular disease (CVD) risk probabilities induced by the 5 cases.