• Korean Journal of Adult Nursing
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• v.20 no.3
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• pp.481-488
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• 2008

Purpose: This study was conducted to identify the effects of diabetes education and telephone counseling on depression in diabetic patients. Methods: 49 diabetic patients(24 in the control group and 25 in the experimental group) completed diabetes education and telephone counseling. Data were analyzed using ${\chi}^2$ test, paired t-test and unpaired t-tests. Results: There were no significant differences in depression between the experimental and control groups. But, Depression scores were much decreased in the experimental group. Conclusion: Depression decreased following the diabetes education and telephone counseling. These findings indicate that diabetes education and telephone counseling could be one of the way to decrease depression.

• Journal of Yeungnam Medical Science
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• v.37 no.1
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• pp.13-21
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• 2020

Maturity-onset diabetes of the young (MODY) is a clinically heterogeneous group of monogenic disorders characterized by ß-cell dysfunction. MODY accounts for between 2% and 5% of all diabetes cases, and distinguishing it from type 1 or type 2 diabetes is a diagnostic challenge. Recently, MODY-causing mutations have been identified in 14 different genes. Sanger DNA sequencing is the gold standard for identifying the mutations in MODY-related genes, and may facilitate the diagnosis. Despite the lower frequency among diabetes mellitus cases, a correct genetic diagnosis of MODY is important for optimizing treatment strategies. There is a discrepancy in the disease-causing locus between the Asian and Caucasian patients with MODY. Furthermore, the prevalence of the disease in Asian populations remains to be studied. In this review, the current understanding of MODY is summarized and the Asian studies of MODY are discussed in detail.

• Korean Journal of Artificial Intelligence
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• v.6 no.1
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• pp.16-20
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• 2018

The development of modern information technology has increased the amount of big data about patients' information and diseases. In this study, we developed a prediction model of diabetes using the health examination data provided by the public data portal in 2016. In addition, we graphically visualized diabetes incidence by sex, age, residence area, and income level. As a result, the incidence of diabetes was different in each residence area and income level, and the probability of accurately predicting male and female was about 65%. In addition, it can be confirmed that the influence of X on male and Y on female is highly to affect diabetes. This predictive model can be used to predict the high-risk patients and low-risk patients of diabetes and to alarm the serious patients, thereby dramatically improving the re-admission rate. Ultimately it will be possible to contribute to improve public health and reduce chronic disease management cost by continuous target selection and management.

• Journal of Multimedia Information System
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• v.5 no.1
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• pp.53-58
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• 2018

The Republic of Korea (ROK) has been putting much effort to deal with diabetes which is being increasingly found in all age groups due to inadequate diet. Diabetes is closely related to one's eating habits and lifestyle that often cause hyperglycemia so that it is essential for the diabetic patients to change them to improve or control the major symptoms of diabetes. This study introduces a software engineering solution to support these patients. The software designed for the solution lets the patients to easily recognize their sugar levels and current treatment schemes and then advises a more effective approach along with the essential information through the embedded push service. The major goal of this study is to support diabetes patients by providing a convenient but effective means to prevent or improve diabetic symptoms by patients themselves who will in turn change their lifestyles in a positive manner.

• Advances in Traditional Medicine
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• v.5 no.2
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• pp.75-91
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• 2005

Great efforts have been made to improve both the quality of life and life expectancy of diabetes by treating problems associated with chronic complications such as neuropathy, retinopathy and nephropathy. In particular, diabetes is an increased risk of developing several types of kidney disease, and the predominant cause of end-stage renal disease in patients with this disorder is diabetic nephropathy. Therefore, prevention of the occurrence and progression of diabetes and its complications has become a very important issue. The scientific observations of an animal model of streptozotocin-induced diabetes, spontaneously occurring diabetes and diabetic nephropathy in this study suggest that one of the Kampo prescriptions, Hachimi-jio-gan comprising eight constituents, is a novel therapeutic agent.

• Journal of Nutrition and Health
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• v.32 no.4
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• pp.401-406
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• 1999

The purpose of this study was to identify some anthropometric characteristics related to the incidence of diabetes mellitus in Korea. The subjects were 165 male and female patients aged 30 to 70 years who had been diagnosed with diabetes mellitus for less than five year, recruied from eight different hospitals in Seoul, Korea. Weight, height, waist circumference, hip circumference and triceps skinfold thickness were measured. Weight before diagnosis of diabetes was also surveyed. The body mass index(BMI) of diabetic patients before diabetic diagnosis was significantly higher than that of reference values. Fifty percent of patients had BMI values greater than 25kg/$m^2$, and female patients were somewhat fatter than male patients. Since many subjects were overweight before diagnosis, obestty could be regarded as a risk factor for the incidence of diabetes mellitus. However, waist-hip ratios(WHR) fell within the normal range, so WHR may not be regarded as an important risk factor for NIDDM in Korea. This study suggests that the risk factors of onset of diabetes in Western populations may not be applicable to the Korea population. More study is needed to clarify the risk factors of Korean diabetes.

• Health Policy and Management
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• v.21 no.1
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• pp.1-22
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• 2011

This study investigated unmet health care needs and associated factors among patients with hypertension and those with diabetes. Patients were identified by medical professionals. Patients who did not take pharmaceuticals to treat their disease(s) were defined as those with unmet health care needs. Using data from 2005 National Health and Nutrition Examination Survey, 3,635 hypertension patients and 1,431 diabetes patients were analyzed. A multivariate logistic regression analysis was employed to examine factors associated with unmet needs. Overall, 16.6% of hypertension patients, 20.3% of those with diabetes presented unmet needs. Common factors associated unmet needs for both hypertension and diabetes were sex, insurance type, self-reported health status and length of disease. Study findings suggest that hypertension and diabetes should be treated in early stage and further study is needed to examine the reasons for unmet needs to improve patient's status effectively.

• IMMUNE NETWORK
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• v.11 no.2
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• pp.95-99
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• 2011

Type 1 diabetes is one of the classical examples of organ-specific autoimmune diseases characterized by lymphocytic infiltration or inflammation in pancreatic islets called 'insulitis'. In contrast, type 2 diabetes has been traditionally regarded as a metabolic disorder with a pathogenesis that is totally different from that of type 1 diabetes. However, recent investigation has revealed contribution of chronic inflammation in the pathogenesis of type 2 diabetes. In addition to type 2 diabetes, the role of chronic inflammation is being appreciated in a wide variety of metabolic disorders such as obesity, metabolic syndrome, and atherosclerosis. In this review, we will cover the role of innate immunity in the pathogenesis of metabolic disorders with an emphasis on NLRP3.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2904-2926
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• 2022

Currently, diabetes is the most common chronic disease in the world, affecting 23.7% of the population in the Kingdom of Saudi Arabia. Diabetes may be the cause of lower-limb amputations, kidney failure and blindness among adults. Therefore, diagnosing the disease in its early stages is essential in order to save human lives. With the revolution in technology, Artificial Intelligence (AI) could play a central role in the early prediction of diabetes by employing Machine Learning (ML) technology. In this paper, we developed a diagnosis system using machine learning models for the detection of type 2 diabetes among adults, through the adoption of two different diabetes datasets: one for training and the other for the testing, to analyze and enhance the prediction accuracy. This work offers an enhanced classification accuracy as a result of employing several pre-processing methods before applying the ML models. According to the obtained results, the implemented Random Forest (RF) classifier offers the best classification accuracy with a classification score of 98.95%.

• Journal of Preventive Medicine and Public Health
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• v.56 no.4
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• pp.384-387
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• 2023

The aim of this study was to present a framework for clinicians to use when discussing electronic cigarette (e-cigarette) use and its association with pre-diabetes. A communication tool was designed using evidence-based strategies from the academic literature. A four-step framework is presented, which includes: step (1) helping patients to understand the association between e-cigarette use and pre-diabetes; step (2) the synergistic health impacts of e-cigarette use and pre-diabetes; step (3) management of diabetes-related lifestyle factors; and step (4) stages of change assessment related to e-cigarette reduction. This communication tool provides support for clinicians to discuss the risk of pre-diabetes associated with e-cigarette use. Moving forward, implementation and evaluation of this model are needed.