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Cukry a sladidla v lidské výživě
Otrusinová, Kateřina
The bachelor thesis deals with the characteristics and classification of sweet substances with a focus on classification of sugars and sweeteners. The paper deals in detail with structure, occurrence, physiological effect and use of individual representatives from the group of monosaccharides, disaccharides and natural and synthetic sweeteners and those synthetic ones identical to natural. Attention is paid to sugar absorption, blood glucose concentration and glycemic index. It is also focused on effects of sweet substances consumption on the body and related diseases such as diabetes mellitus or obesity that is associated with fructose in context of mutation of the thrifty genes.
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Vliv glykemického indexu potravin na glykémii člověka
Šafránková, Anna
This bachelor thesis focuses on the glycemic index of food in connection with its effect on human glycemia (blood sugar levels). It contains carbohydrates' primary classification and properties and explains carbohydrate metabolism and their digestion and absorption into the body. A substantial part of the work explains the glycemic index itself and the factors affecting the glycemic index and glycemia. Food is divided into appropriate groups based on the glycemic index and its effect on glycemia. The work also presents the method of measuring the glycemic index. There is also described the effect of carbohydrates on hu-man health, the principles of a diet based on the glycemic index, and diseases associated with excessive or insufficient carbohydrate intake arising in connection with the consump-tion of food with a high glycemic index. At the end of the work, the term glycemic load is introduced in connection with the glycemic index.
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Stress hyperglycemia during extreme cycling sports
Hájková, Michaela ; Heller, Jan (advisor) ; Šteffl, Michal (referee)
Introduction: This work focuses on the differences in metabolism in patients with type 1 diabetes associated with the stress response and interaction of insulin with epinephrine and cortisol. The main topic is increased hyperglycaemia during and immediately after a stress situation and the possibilities of regulation in this disease. The practical part consists of a case study of a subject with type 1 diabetes mellitus and his state of hyperglycemia during races of extreme cycling disciplines. Objectives: The main aim of this work is to introduce and descript this phenomen in Czech language, to clarify the issues of this phenomen and to conduct a case study to verify results of theoretical part. Methods: Methods that were used in this work includes literature rewiew summerising available materials on this topic and in the practical part a qualitative research method, a case study, examining one subject. Data from platform Diasend were observed and compared and the subject provided an interview. Results: The results of the case study support the findings of the literature review. The highest glucose levels during sport related stress reached up to 20.0 mmol/l despite increased basal and bolus doses. Keywords: glucose metabolism, diabetes mellitus, glycaemia, epinephrine, cortisol
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Health assessment using smart devices
Vargová, Enikö ; Filipenská, Marina (referee) ; Němcová, Andrea (advisor)
This thesis deals with the possibilities of non-invasive determination of blood glucose from photoplethysmographic signals. Elevated blood sugar is often associated with disease called diabetes mellitus. Diabetes is one of the world’s major chronic diseases. Untreated diabetes is often a cause of death. The aim of the work is to propose methods for glycemic classification and prediction. Two datasets have been created by recording the PPG signals using two smart devices (a smart wristband and a smartphone), along with their blood glucose levels measured in an invasive way. The PPG signals were preprocessed, and suitable features were extracted from them. Various machine-learning models for glycemic classification and prediction were created.
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Accuracy of Personal Glucometers
Kroulíková, Markéta ; Němcová, Andrea (referee) ; Sekora, Jiří (advisor)
This thesis deals with accuracy measurement of personal glucometers. The theoretical part is focused on processing information about glucose and its role in organism, diabetes mellitus, procedures and devices used in self-monitoring of glucose. The next part is focused on preparation of practical part, especially describing available personal glucometer, testing its measuring accuracy, the calculation of necessary measurements to perform the experiment and a description of the reference sample for data measurement.
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Regime of a Diabetic Patient during Hospitalization in the Surgical Ward at IKEM
Slavíková, Petra ; Bakusová, Tereza (advisor) ; Komínek, Tomáš (referee)
The bachelor's thesis focuses on research during the hospitalization of three type II. diabetics at the Transplantation Surgery Clinic at IKEM. The thesis is divided into theoretical and practical parts. The theoretical part describes the anatomy, history of diabetes, diagnosis, possible complications of diabetes, potential therapy, education of diabetics, and nursing care for diabetics. The practical part focuses on independent research of the regime by monitoring the diabetics for two days during their hospitalization. The aim of the thesis is to focus on the precise course of hospitalization for diabetics. The aim is not to control the correct course, but rather to examine the regime that is provided to diabetics on the surgical ward at IKEM. The thesis evaluates the regularity and amount of food intake, blood glucose measurements, insulin administration, and adherence to dietary measures. The thesis describes the individual nutrition of the selected diabetics, with precisely measured blood glucose values and the amount of insulin administered. It also includes final questioning of the patients on specific questions closely related to the regime. The goal of the interview was to identify potential complications that patients suffer from. Keywords: Diabetes Mellitus, blood glucose, IKEM, nursing care
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The effect of a low carbohydrate diet on the compensation of type 2 diabetes mellitus
Sedlářová, Lenka ; Sucharda, Petr (advisor) ; Sadílková, Aneta (referee)
Type 2 diabetes mellitus (T2D) is a chronic metabolic disease characterized by insulin resistance and several secondary complications. The prevalence of patients is constantly increasing, and thus the effort to improve the quality of therapy, new findings, and procedures capable of being applied in clinical practice are sought. Patients live with the disease for a long time, and the purpose of treatment is to improve the quality of life of diabetics and delay the onset of associated health complications. A combination of regimen measures is essential for successful treatment. Dietary measures in the form of a low-carbohydrate diet are still a popular choice of dietary options among diabetics. The aim of the practical part of the work was to prove the positive effect of a low- carbohydrate diet on T2D compensation. The primary objective was to demonstrate a significant reduction in glycated hemoglobin (HbA1c) in patients who eat or have eaten according to the principles of a low-carbohydrate diet for at least 12 months. Secondary objectives were set as follows: reduction of relative weight (BMI), reduction of pharmacotherapy and/or reduction of daily doses of antidiabetic drugs, reduction of fasting blood glucose and improvement of the lipid spectrum. The research group included patients from the...
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Health assessment using smart devices
Vargová, Enikö ; Filipenská, Marina (referee) ; Němcová, Andrea (advisor)
This thesis deals with the possibilities of non-invasive determination of blood glucose from photoplethysmographic signals. Elevated blood sugar is often associated with disease called diabetes mellitus. Diabetes is one of the world’s major chronic diseases. Untreated diabetes is often a cause of death. The aim of the work is to propose methods for glycemic classification and prediction. Two datasets have been created by recording the PPG signals using two smart devices (a smart wristband and a smartphone), along with their blood glucose levels measured in an invasive way. The PPG signals were preprocessed, and suitable features were extracted from them. Various machine-learning models for glycemic classification and prediction were created.
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