Thyroid and Adrenal Peptides in Thyroid Therapy

Today, doctors are faced with a new type of pathology - premature (or accelerated) aging. The symptoms are the same everywhere - exhaustion and slow destruction of vital systems of the body: the immune system, endocrine system, nervous system, cardiovascular system, reproductive system, visual system.

Comparison of Sevelamer and Calcium Carbonate on Lipid Profile & Hba1c in Diabetic Kidney Disease

Diabetic is a worldwide health issue and diabetic kidney disease is a dreaded complication of the disease. Drugs that can impair intestinal absorption of advanced glycation end products (AGE) can improve glycemic control and lipid profile. Sevelamer is a calcium free phosphate binder and has postulated to have a role in prevention of absorption of age. The aim of the study was to compare the mean change HbA1c and lipid profile in diabetic kidney disease by selvelamer vs calcium carbonate. The mean of the patient was 58.53 years. Sevelamer showed a mean decrease in HbA1c and lipid profile as compared to calcium carbonate (-0.57 + 45, -8.35 ± 9.006, -1.40 ± 7.07, -4.20 ± 4.26, vs -0.08 ± 0.21, 0.10 ± 2.51, 0.62 ± 1.03, 1.00 ± 1.55). However there was a mean rise in C-reactive protein. We concluded that sevelamer caused greater mean decrease that in HBA1c and lipid profile as compared to calcium carbonate but failed to decrease C- reactive protein.

COVID -19 and Cardio Metabolic Practice at MENA Regions. Policy Analysis & Recommendations

Health systems were not expected COVID -19 pandemic which made Pressure on that systems. Practice at Cancer field had different nature at COVID -19. Due to the following (patients type, Diagnosis Process and patient journey) the objective of this research is finding out impact of COVID -19 on cardio metabolic practice. Methods: Integration analysis between International guidelines like (ESC, NHS, WHO) and conducting local survives with local Physicians at previous countries. Results: Periodization criteria was very influencer at practice elements this leaded to medications plans changing through different solutions one of those solutions was health technologies Conclusion: Dynamic prioritization criteria was founded the corner stone for Practice adaption for Safety enhancement through Time reducing plans managed Effective leadership elements through technology solutions .

Covid-19 Pandemic and Possible Links with Mthfr Mutations, Homocysteinemia, and Metabolic Disturbances: Short Review

Coronovirus-19 (COVID-19) is an associate degree infection caused by the SARS-CoV-2 virus inflicting a worldwide pandemic and chiefly characterized by respiratory symptoms, many times accompanied by a cytokine storm. It causes migration of the neutrophils, macrophages and inflammatory cytokines resulting in the destruction of the alveolar-capillary walls. Coagulopathy in patients with COVID-19 may be a common complication that jeopardizes the clinical course and is related to poorer outcomes and probable death. The methylenetetrahydrofolate enzyme (MTHFR) is coded by the gene with the image MTHFR on chromosome one location p36.3 in humans, and there are desoxyribonucleic acid sequence variants (genetic polymorphisms) related to this gene. However, the 2 commonest ones are C677T and A1298C. Deficiencies within the production of this accelerator are related to raise risk of cardiac muscle infarctions, stroke, thrombosis, and several conditions. Homocysteine (Hcy) is a chemical in the blood formed when the amino acid methionine, a building block of the proteins, is naturally metabolized to be excreted in the urine; throughout this breakdown method, our body will recycle homocysteine to be reused to make different proteins. For this utilization, we need vitamins B12, B6, and folate. Also, for utilization to be the foremost economical, the accelerator MTHFR is needed. Transmissible mutations within the factor that create the MTHFR accelerator will result in an associate degree accelerator that’s not optimally active and should result in elevated homocysteine levels. Several medical conditions, like vascular disorders, obesity, diabetic disorder, peripheral neuropathy, and thrombophilia’s inside others, are associated with high Hcy levels and MTHFR mutations. Few reports link the high risk and poor prognosis with COVID-19 with MTHFR mutation and metabolic disorders like obesity and Diabetes mellitus. In this this review, we provide recommendations to prevent complications in patients with COVID, MTHFR mutations, Diabetes, and Obesity.

A biophysical investigation on the relationships between the inputs of meal quantity percentage, carbs/sugar amount, and exercise, along with the outputs of postprandial plasma glucose, and body weight using GH-Method: Math-physical medicine (No. 295)

This research note describes the author’s investigation on differences among his three meals, which include breakfast, lunch, and dinner, in terms of their influential factors and their respective PPG data and waveforms. He further described the relationship between his body weight and meal quantity percentage for his normal portion. During this period, from 5/5/2018 to 7/14/2020, he collected detailed information of his 2,403 meals and ~64,000 glucose data.

Diabetic Retinopathy study via metabolism improvements and chronic diseases medical conditions control of HbA1C, SBP, and Triglycerides (GH-Method: math-physical medicine)

The author used his own medical data to investigate the impact on his diabetic retinopathy condition and its risk probability percentage or hazard ratio (HR) over a period of 7-years.

PPG prediction methodology by analyzing a simple lunch using GH-Method:math-physical medicine

This paper discusses both predicted and measured postprandial plasma glucose (PPG) results from a simple lunch of one small bag of Quaker oatmeal: 18 grams carbs and 0 grams of sugar using the GH-Method: math-physical medicine (MPM). He developed MPM by applying mathematics, physics, engineering modeling, and computer science (big data analytics and AI). He believes in “prediction” and has developed five models, including metabolism index, weight, fasting plasma glucose (FPG), postprandial plasma glucose (PPG), and hemoglobin A1C. All prediction models have reached to 95% to 99% accuracy. His focus is on preventive medicine, especially on diabetes control via lifestyle management.

Understanding glucose via postprandial plasma glucose sensor data segmentation analysis (GH-Method: math-physical medicine)

In this paper, the author analyzed and interpreted a type 2 diabetes (T2D) patient’s postprandial plasma glucose (PPG) waveforms (i.e. curve sets), data, and key characteristics, with mathematical tools to study the physical behaviors of glucose in detail, utilizing his developed GH-Method: math-physical medicine approach.

Diabetes Management in The Face of the Coronavirus Pandemic

In the midst of the COVID-19 pandemic, many diabetics have found themselves lost in trying to understand how to best manage diabetes symptoms and complications. Current research shows that diabetics are more at risk of acquiring serious complications as a result of COVID-19 such as diabetic ketoacidosis, adult respiratory distress syndrome, etc. These risks come from the fact that the COVID-19 virus attacks a similar receptor which is upregulated in most diabetic patients’ cases. Therefore, extra precautions must be taken for this population group in regard to management and treatment of symptoms in order to curb the potential for decreased outcomes.

Using Time-Series and Spatial Analysis (Math-Physical Medicine) to Investigate the Relationships among Weight, Blood Pressure,Glucose, Food and Exercise

The author uses his own type 2 diabetes metabolic conditions control as a case study using the “math-physical medicine” approach of a non-traditional methodology in medical research. Math-physical medicine (MPM) starts with the observation of the human body’s physical phenomena (not biological or chemical characteristics), collecting elements of the disease related data (preferring big data), utilizing applicable engineering modeling techniques, developing appropriate mathematical equations (not just statistical analysis), and finally predicting the direction of the development and control mechanism of the disease.