• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.73-78
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• 2023

Diabetes is chronic disease that is rapidly increasing in prevalence around the world, and mortality from complications continues to rise. This has made blood glucose management a critical challenge for modern society. The main methods used to manage blood glucose are diet, exercise, and medication. Among these, diet is one of the fundamental foundations of blood glucose management, avoiding foods that cause high blood glucose and minimizing blood glucose fluctuations, and is more accessible to people with diabetes as well as the general population. Currently, several platforms, both domestic and international, offer meal planning services, but this is mainly done by users or professional coaches. Accordingly, this paper implements an accurate Kcal calculation model based on DNN and presents a series of dietary algorithms for blood glucose management based on this.

• Journal of Neurocritical Care
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• v.11 no.2
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• pp.81-85
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• 2018

Proper glucose management in hospitalized patients can improve clinical outcomes. In particular, intensive care unit (ICU) patients are known to have significantly higher rates of mortality from changes in blood glucose due to severe comorbidities. Improving glucose control in ICU patients, therefore, can improve mortality and prognosis. Several studies related to the management of blood glucose in the ICU patients have been conducted. Intensive glucose management of surgical ICU patients has been successful. However, studies on medical ICU patients did not demonstrate positive effects of strict glycemic control. There is no independent glucose management goal for neurological ICU patients. However, maintenance of the usual glucose control target of 140-180 mg/dL is recommended for ICU patients. Intravenous insulin infusion is essential for glucose control in ICU patients not consuming a regular diet, and caution should be exercised to prevent hypoglycemia.

• Korean Journal of Adult Nursing
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• v.22 no.3
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• pp.271-280
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• 2010

Purpose: The purpose of this study was to examine relationships among blood glucose, HbA1c, and self management comparing these with general and illness characteristics of subjects with Type II Diabetes living in the community. Methods: Using a comprehensive survey developed for the study, data were collected from 82 type II diabetes patients who were registered at five community health departments. The variables of self management, blood glucose and HbA1c were assessed by nurses. Data were analyzed with descriptive statistics including t-test, ANOVA and Pearson's correlation coefficient to compare self management and level of HbA1c by subject's general and illness characteristics and to examine the relationships among variables. Results: About 73.2% of the subjects' HbA1c were 7.0% or higher and 54.9% of subjects' blood glucose were 200 mg/dL or higher. The level of self management was moderate. Most frequently perceived reasons for failure of blood glucose control were dietary failure (32.9%). There was significant relationship between self management and HbA1c(r=-.223, p=.040). The mean score of self management were higher among female (t=-2.37, p=.021), who are not on diabetes medication (t=6.70, p=.011). Conclusion: Comprehensive intervention is needed to improve dietary self management, especially for male and those who is on diabetes medication.

• Child Health Nursing Research
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• v.18 no.1
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• pp.43-52
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• 2012

Purpose: The purpose of this study was to provide basic data for suitable neonate blood glucose maintenance by investigating and analyzing the blood glucose level of post cardiovascular surgery neonates in the ICU for the effect of blood glucose levels on the following outcomes; ICU stay, hospital stay, mechanical ventilation time, morbidity, and mortality. Methods: The participants were 143 neonates in the ICU after having had cardiovascular surgery. The design for this study was an investigation of the blood glucose levels of the neonates and retrospective analysis of patient outcomes according to blood glucose level. Results: The results for the neonate groups showed that the factors of hospital stay, ICU stay, mechanical ventilation time and mortality, for the group with a blood glucose level over 140 mg/dL were longer and higher than for the group with blood glucose of less than 100 mg/dL or the group between 100-139 mg/dL. Conclusion: The results of this study indicate that when caring for neonates after cardiovascular surgery, it is important to recognize the influence of blood glucose levels on patient outcomes like hospital days, ICU stay, length of time on mechanical ventilation and mortality. Further, care guidelines for neonates' glucose level management need to be developed.

• Electronics and Telecommunications Trends
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• v.36 no.5
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• pp.9-20
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• 2021

A technology to replace the traditional blood sampling method for glucose monitoring has been sought for a long time. It is now possible to measure the blood glucose change rate continuously for more than 24 hours using a minimally invasive method that does not involve blood collection. Furthermore, various technology development efforts are being made for innovative diabetes management through intermittent or continuous blood glucose monitoring in a non-invasive manner. In this paper, we present an overview of diabetes and the need for continuous blood glucose measurement techniques., and then introduce various non-invasive blood glucose measurement techniques currently being studied. In addition, through research and analysis of the recent commercialization development status of minimally invasive, non-invasive, and wearable continuous blood glucose measurement technologies, we examine global development trends of future technologies.

• Journal of Veterinary Clinics
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• v.27 no.4
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• pp.392-396
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• 2010

Blood glucose curves in the management for diabetic patients have several limitations including intermittent assessment of blood glucose concentration, hospitalization, patient restraint, and repeated phlebotomy. The aim of this study was to apply and evaluate a wireless continuous glucose monitoring system (CGMS) in healthy dogs. Subcutaneous interstitial glucose concentrations in 7 dogs were continuously monitored and recorded by wireless CGMS. During induced hyperglycemia, the interstitial glucose concentrations were compared with whole blood glucose concentrations measured by glucometer and serum glucose concentrations measured by automated chemistry analyzer, respectively. There were no significant differences among interstitial, whole blood and serum glucose concentrations. The interstitial glucose concentrations had a good correlation to serum glucose concentrations. The real-time wireless CGMS is a valuable tool for monitoring system of glucose concentrations in dogs. Use of the CGMS for diabetic patients will provide accurate information over traditional blood glucose curves.

• Nutrition Research and Practice
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• v.3 no.4
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• pp.272-278
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• 2009

Postprandial hypoglycemic effect of mulberry leaf (Morus alba L.) was compared in two animal models: Goto-Kakizaki (GK) rats, a spontaneous non-obese animal model for type II diabetes, and their counterpart control Wistar rats. First, the effect of a single oral administration of mulberry leaf aqueous extract (MLE) on postprandial glucose responses was determined using maltose or glucose as substrate. With maltose-loading, MLE reduced peak responses of blood glucose significantly in both GK and Wistar rats (P < 0.05), supporting the inhibition of $\alpha$-glucosidase by MLE in the small intestine. With glucose-loading, MLE also significantly reduced blood glucose concentrations, measured at 30 min, in both animal models (P < 0.01), proposing the inhibition of glucose transport by MLE. Next, dried mulberry leaf powder (MLP) was administered for 8 weeks by inclusion in the diet. By MLP administration, fasting blood glucose was significantly reduced at weeks 4 and 5 (P < 0.05), but then returned to values that were similar to those of the control at the end of experimental period in GK rats. Insulin, HOMA-IR, C-reactive protein, and triglycerides tended to be decreased by MLP treatment in GK rats. All other biochemical parameters were not changed by MLP administration in GK rats. Collectively, these findings support that MLE has significant postprandial hypoglycemic effect in both non-obese diabetic and healthy animals, which may be beneficial as food supplement to manage postprandial blood glucose. Inhibitions of glucose transport as well as $\alpha$-glucosidase in the small intestine were suggested as possible mechanisms related with the postprandial hypoglycemic effect of MLE.

• Korean Journal of Clinical Laboratory Science
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• v.42 no.3
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• pp.125-128
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• 2010

HbA1c test measures the amount of glycated hemoglobin in blood. HbA1c shows the average of blood glucose levels for the past three months, this is a better indicator of how overall diabetes is doing. HbA1c gives a much better idea of how the body is breaking down the glucose. Therefore, this HbA1c is very important tool for maintaining normal glucose levels for pre-and diabetic patients. Total 408 participants were tested HbA1c voluntarily from Chosunilbo Health Expo (8th~11th, July 2010). Through this small-scaled direct HbA1c, about 54.7% (207 out of 408) was shown glucose tolerance and diabetes. However, 61 from 157 participants who were shown under 6.9% HbA1c (normal and pre-diabetic stage) are taking only antidiabetic drugs to maintain a normal blood glucose. Regular HbA1c test can bring an important management and awareness about controlling blood sugar level and prevention of diabetic complications.

• Nutrition Research and Practice
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• v.15 no.1
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• pp.54-65
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• 2021

BACKGROUND/OBJECTIVES: This study aimed to develop healthy, appetizing high-protein snacks with enhanced isolated soy protein for diabetic patients and determine the blood glucose and insulin response after being consumed by these patients. MATERIALS/METHODS: Thirty adult patients aged between 30 and 75 years, with a ≤ 10-year history of type 2 diabetes and hemoglobin A1c of < 7.5%, were enrolled in this study. They made 3 clinical visits at one-week intervals. The control group consumed 50 g carbohydrates (white bread), whereas the test groups consumed high-protein grain (HP_G) or high-protein chocolate (HP_C) after an 8-hrs fast. Blood (2 ㎤) was drawn at 15, 30, 45, 60, 90, and 120 min before and after consumption to analyze the blood glucose and insulin concentrations. RESULTS: Compared to the commercial snacks, the developed high-protein snacks had below-average calorie, carbohydrate, and fat content and a 2.5-fold higher protein content. In diabetic patients who consumed these snacks, the postprandial blood glucose increased between 15 min and 2 h after consumption, which was significantly slower than the time taken for the blood glucose to increase in the patients who consumed the control food product (P < 0.001). Insulin secretion was significantly lower at 45 min after consumption (P < 0.05), showing that the high-protein snacks did not increase the blood glucose levels rapidly. The incremental area under the curve (iAUC), which indicated the degree of blood sugar and insulin elevation after food intake, was higher in the control group than the groups given the 2 developed snacks (P < 0.001), and there was no significant difference in insulin secretion. CONCLUSIONS: The results of the postprandial blood glucose and insulin response suggest that high-protein snacks are potential convenient sources of high-quality protein and serve as a healthier alternative for patients with type 2 diabetes, who may have limited snack product choices. Such snacks may also provide balanced nutrition to pre-diabetic and obese individuals.

• Journal of Digital Policy
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• v.1 no.2
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• pp.61-69
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• 2022

The paper is a study to develop and verify a blood glucose level prediction model based on biosignals obtained from photoplethysmography (PPG) sensors, ICT technology and data. Blood glucose prediction used the MLP architecture of machine learning. The input layer of the machine learning model consists of 10 input nodes and 5 hidden layers: heart rate, heart rate variability, age, gender, VLF, LF, HF, SDNN, RMSSD, and PNN50. The results of the predictive model are MSE=0.0724, MAE=1.1022 and RMSE=1.0285, and the coefficient of determination (R²) is 0.9985. A blood glucose prediction model using bio-signal data collected from digital devices and machine learning was established and verified. If research to standardize and increase accuracy of machine learning datasets for various digital devices continues, it could be an alternative method for individual blood glucose management.