• Journal of Korean Critical Care Nursing
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• v.8 no.2
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• pp.1-12
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• 2015

Purpose: The study sought to determine the state of blood glucose control, and the consequent clinical effects and variation in blood glucose level, of adult patients admitted to intensive care units following cardiothoracic surgery by comparing the blood glucose levels before and after the application of a blood glucose control protocol. Methods: The protocol was developed by modifying and supplementing the Yale protocol, and was first used in 2012. The resulting blood glucose data of an experimental group (n = 314), to which the blood glucose control protocol had been applied, and a control group (n = 347), whose blood glucose levels had been controlled according to physicians'prescriptions without the protocol, were collected through the medical records. Results: The target blood glucose ratio increased significantly in the experimental group, and the low blood glucose ratio decreased significantly in the experimental group. The two groups exhibited a significant difference (p < .001) in the degree of variation in the blood glucose levels. The duration of the use of a ventilator was significantly reduced in the experimental group (p < .001). Conclusion: It is expected that the protocol can be used for the safe and effective control of critically ill cardiothoracic surgery patients' blood glucose levels.

• Journal of The Korean Society of Clinical Toxicology
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• v.13 no.2
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• pp.55-61
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• 2015

Purpose: Many studies have examined the mechanisms of impaired glucose homeostasis after organophosphate (OP) exposure, however no study has evaluated the clinical utility of blood glucose measurements in patients with OP poisoning. The current study was conducted to evaluate the initial glucose level at presentation and the glycemic variables during the first 3 days after admission as a predictor of mortality. Methods: This retrospective observational case series included 228 patients with a history of OP poisoning. Among other clinical data, information on the initial glucose level at presentation and mean glucose level, delta glucose level, and the presence of a hypoglycemic event during the first 3 days of admission, was collected. Results: Survivors had lower initial glucose levels at presentation and glucose variability during the first 3 days of admission compared to non-survivors. The frequency of hypoglycemic events was higher in non-survivors. In multivariate analysis, the initial glucose level (> 233 mg/dl) was an independent predictor of mortality, along with age. Conclusion: The initial glucose level at presentation can be helpful in prediction of mortality in cases of OP intoxication at bedside. The physician should pay attention to patients with a glucose level >233 mg/dl at presentation after ingestion of OP.

• Journal of Gastric Cancer
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• v.21 no.4
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• pp.325-334
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• 2021

Purpose: Although dumping symptoms are thought to involve postprandial glycemic changes, postprandial glycemic variability without dumping symptoms remains poorly understood due to the lack of a method that allows the easy and continuous measurement of blood glucose levels. Materials and Methods: Patients having undergone distal gastrectomy with Billroth-I (DG-BI) or Roux-en-Y reconstruction (DG-RY), total gastrectomy with RY (TG-RY) and pylorus preserving gastrectomy (PPG) for gastric cancer 3 months to 3 years prior, diagnosed as pathological stage I or II, were prospectively enrolled from March 2018 to January 2020. The interstitial tissue glycemic levels were measured every 15 min, up to 14 days by continuous glucose monitoring. Moreover, using a diary recording the diet and symptoms, asymptomatic glucose profiles without sugar supplementation within 3 h postprandially were compared among the four procedures. Results: A total of 40 patients were enrolled, 10 patients for each of the four procedures. There were 47 glucose profiles with DG-BI, 46 profiles with DG-RY, 38 profiles with TG-RY, and 46 profiles with PPG. PPG showed the slowest increase with a subsequent gradual decrease in glucose fluctuations, without hyperglycemia or hypoglycemia, among the four procedures. In contrast, TG-RY and DG-RY showed spike-like glycemic variability, sharp rises during meals, and rapid drops. The glucose profiles of DG-BI were milder than those of RY. Conclusions: The asymptomatic glycemic changes after meals differ among the types of surgical procedures for gastric cancer. Given the mild glycemic fluctuations in PPG and the glucose spikes in TG-RY and DG-RY, pylorus preservation and physiological reconstruction without changes in food pathways may optimize postprandial glucose profiles after gastrectomy.

• Journal of Digital Convergence
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• v.19 no.9
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• pp.257-269
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• 2021

The purpose of this study is to collect biosignal data in a non-invasive and non-restrictive manner using a BCG (Ballistocardiogram) sensor, and utilize artificial intelligence machine learning algorithms in ICT and high-performance computing environments. And it is to present and study a method for developing and validating a data-based blood glucose prediction model. In the blood glucose level prediction model, the input nodes in the MLP architecture are data of heart rate, respiration rate, stroke volume, heart rate variability, SDNN, RMSSD, PNN50, age, and gender, and the hidden layer 7 were used. As a result of the experiment, the average MSE, MAE, and RMSE values of the learning data tested 5 times were 0.5226, 0.6328, and 0.7692, respectively, and the average values of the validation data were 0.5408, 0.6776, and 0.7968, respectively, and the coefficient of determination (R²) was 0.9997. If research to standardize a model for predicting blood sugar levels based on data and to verify data set collection and prediction accuracy continues, it is expected that it can be used for non-invasive blood sugar level management.

• Journal of Korean Academy of Nursing
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• v.41 no.6
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• pp.788-794
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• 2011

Purpose: Reduced heart rate variability significantly increases cardiovascular mortality. Metabolic syndrome increases the cardiac autonomic dysfunction. Recently, increasing cardiovascular mortality has been reported in patients with schizophrenia. This study was done to compare heart rate variability between adults with and without schizophrenia and to compare the relationship of heart rate variability to metabolic syndrome in hospitalized patients with schizophrenia. Methods: This was a descriptive and correlational study in which 719 adults without schizophrenia and 308 adults with schizophrenia took part between May and June 2008. We measured the following: five-minute heart rate variability; high-frequency, low-frequency, the ratio of low-frequency to high-frequency, and the Standard Deviation of all the normal RR intervals. Data was also collected on metabolic syndrome, abdominal obesity, triglycerides, HDL cholesterol, blood pressure and fasting glucose. Results: The Standard Deviation of all the normal RR intervals values of heart rate variability indices were $1.53{\pm}0.18$. The low-frequency and high-frequency values of heart rate variability indices were significantly higher in hospitalized patients with schizophrenia ($3.89{\pm}1.36$; $3.80{\pm}1.20$) than those in the healthy participants ($2.20{\pm}0.46$; $2.10{\pm}0.46$). There were no significant differences between the schizophrenic patients with and without metabolic syndrome. Conclusion: The results of this study indicate that schizophrenia patients have significantly lower cardiac autonomic control, but they have significantly higher low-frequency and high-frequency values than those of healthy adults. Use of antipsychotic drug may affect the autonomic nervous system in schizophrenic patients. Metabolic syndrome was not associated with cardiac autonomic control in schizophrenia patients.

• The Journal of the Society of Stroke on Korean Medicine
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• v.21 no.1
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• pp.11-20
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• 2020

■ Objectives The purpose of this study is to report on a case that showed improvement in type 2 diabetic patients by using herbal medicine, Yeoldahansotang-gami. ■ Methods Yeoldahansotang-gami was given to patients with type 2 diabetes for 71days. To evaluate the effect, blood glucose was measured 4 times a day. As measured blood sugar, the frequency of hyperglycemia, changes in fasting blood sugar, changes in postprandial blood sugar, and changes in glucose variability were analyzed. The patient's insulin injection dose change was observed, and HbA1c and glycated albumin were measured. Follow-up was performed for 7 months to observe whether the treatment effect was maintained. ■ Results During treatment, the patient's blood sugar control, glucose variability, and HbA1c were improved, and insulin injection dose was gradually reduced and stopped. HbA1c and glycated albumin levels maintained improvement without insulin injection during the follow-up period. ■ Conclusion This study showed the effect of yeoldahansotang-gami on type 2 diabetes patient.

• Diabetes and Metabolism Journal
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• v.42 no.6
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• pp.496-512
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• 2018

Background: This study aimed to investigate the association between the presence and severity of cardiovascular autonomic neuropathy (CAN) and development of long-term glucose fluctuation in subjects with type 2 diabetes mellitus. Methods: In this retrospective cohort study, subjects with type 2 diabetes mellitus who received cardiovascular autonomic reflex tests (CARTs) at baseline and at least 4-year of follow-up with ${\geq}6$ measures of glycosylated hemoglobin (HbA1c) were included. The severity of CAN was categorized as normal, early, or severe CAN according to the CARTs score. HbA1c variability was measured as the standard deviation (SD), coefficient of variation, and adjusted SD of serial HbA1c measurements. Results: A total of 681 subjects were analyzed (294 normal, 318 early, and 69 severe CAN). The HbA1c variability index values showed a positive relationship with the severity of CAN. Multivariable logistic regression analysis showed that CAN was significantly associated with the risk of developing higher HbA1c variability (SD) after adjusting for age, sex, body mass index, diabetes duration, mean HbA1c, heart rate, glomerular filtration rate, diabetic retinopathy, coronary artery disease, insulin use, and anti-hypertensive medication (early CAN: odds ratio [OR], 1.65; 95% confidence interval [CI], 1.12 to 2.43) (severe CAN: OR, 2.86; 95% CI, 1.47 to 5.56). This association was more prominent in subjects who had a longer duration of diabetes (>10 years) and lower mean HbA1c (<7%). Conclusion: CAN is an independent risk factor for future higher HbA1c variability in subjects with type 2 diabetes mellitus. Tailored therapy for stabilizing glucose fluctuation should be emphasized in subjects with CAN.

• BMB Reports
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• v.40 no.1
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• pp.29-35
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• 2007

During the past decade, many salivary parameters have been used to characterize disease states. Ghrelin (GAH) is recently-discovered peptide hormone secreted mainly from the stomach but also produced in a number of other tissues including salivary glands. The aim of this work was to examine the relationship between active (aGAH) and inactive (dGAH) ghrelin in the saliva and other salivary parameters in type II diabetic patients and healthy controls. Salivary parameters were assessed in a single measurement of unstimulated whole saliva from 20 obese and 20 non-obese type II diabetes patients, and in 22 healthy controls. Total protein and alpha-amylase were determined by colorimetric methods, and glucose by the glucose-oxidase method. Saliva aGAH and dGAH levels were measured using a commercial radioimmunoassay (RIA) kit. Salivary concentrations of aGAH and dGAH ghrelin were more markedly decreased in obese diabetic subjects than in the two other groups. Glucose and alpha-amylase levels were higher in diabetic subjects than in controls. Furthermore, there were correlations between GAH levels and BMI, and between GAH and blood pressure. However, there was no marked variability in saliva flow rates among the groups. These results indicate that measurement of salivary GAH and its relationship to other salivary parameters might help to provide insight into the role of ghrelin in diabetes.

• Journal of Sericultural and Entomological Science
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• v.39 no.2
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• pp.119-133
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• 1997

Isozyme was used to characterize general protein patterns of genetic relationships among 303 silkworm stocks preserved in National Sericultural and Entomology Research Institute, RDA. Six isozymes (esterase, acid phosphatase, alkaline phosphatase, amylase, glucose-6-phosphate dehydrogenase and sucrase) from hemolymph, midgut, and digestive juice were employed to construct dendograms(UPGMA method) using a polycrylamide gel electrophoresis. A cluster analysis revealed four major group, which were divided into several subgroups within each group, contained assemglages of Japanese and Chinese races. Especially, genetic differentiation in the first and second group was greatest rather than within Japanese and Chinese races repectively and was concordant with the hypothesis of phyletic sorting of initial variability in China many years ago. Hypothesized recent introgression between groups was also plausible, but the eviednce suggested bidirectional gene flow between the Chinese and the Japnaese lineages. Interpreting the results in light of evidence from the current study, the genetic diversity and relationship showed in Korean silkworm race, Hansammyun reflected early and independent evolution from the Chinese ancestor, limited addition of new variability and phyletic sorting within Korean peninsula more than 4,000 years.

• 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.