Treatment of obesity includes diet therapy, exercise therapy, cognitive behavioral therapy, drug therapy, and bariatric surgery. Most obese patients lose weight by combining diet, exercise, cognitive behavioral therapy or medication. But, in some cases, only one of these treatments is preferred. A 56-year-old male patient had a body mass index (BMI) of 33.1 kg/m2 and a waist circumference of 108 cm. He had been treated for hypertension; diabetes and dyslipidemia were diagnosed but not treated. However, at the initial visit to treat obesity, he was diagnosed with type 2 diabetes mellitus and dyslipidemia again. So he decided to treat these two diseases with drugs first and modify his lifestyle. He started walking more than 20,000 steps every day and then he really walked about 15,000 steps every day during 5 months, although diet calorie or alcohol drinking amount was not significantly decreased. After about 6 months, the patient's weight decreased by 10.1 kg, the BMI decreased by 4.1 kg/m2, the waist circumference decreased by 10 cm, the glycated hemoglobin (HbA1c) decreased by 4.59%, the visceral fat area decreased by 115 cm2, and the subcutaneous fat decreased by 38 cm2. As a result of body composition analysis, muscle mass increased by 1.2 kg, and the percentage of body fat decreased by 10.4%. The walking exercise does not have any space restrictions and has high accessibility by using a mobile phone app. Therefore, considering the patient's situation, it would be better to treat obese patients by first recommending walking exercises and increasing the number of steps to lose weight and improve the comorbidities.
Jung, Seulgi;Kim, Yoojin;Park, Jeongok;Choi, Miyoung;Kim, Sue
여성건강간호학회지
/
제27권2호
/
pp.75-92
/
2021
Purpose: This study aimed to analyze the content and effectiveness of psychosocial support interventions for women with gestational diabetes mellitus (GDM). Methods: The following databases were searched with no limitation of the time period: Ovid-MEDLINE, Cochrane Library, Ovid-Embase, CINAHL, PsycINFO, NDSL, KoreaMed, RISS, and KISS. Two investigators independently reviewed and selected articles according to the predefined inclusion/exclusion criteria. ROB 2.0 and the RoBANS 2.0 checklist were used to evaluate study quality. Results: Based on the 14 selected studies, psychosocial support interventions were provided for the purpose of (1) informational support (including GDM and diabetes mellitus information; how to manage diet, exercise, stress, blood glucose, and weight; postpartum management; and prevention of type 2 diabetes mellitus); (2) self-management motivation (setting goals for diet and exercise management, glucose monitoring, and enhancing positive health behaviors); (3) relaxation (practicing breathing and/or meditation); and (4) emotional support (sharing opinions and support). Psychosocial supportive interventions to women with GDM lead to behavioral change, mostly in the form of self-care behavior; they also reduce depression, anxiety and stress, and have an impact on improving self-efficacy. These interventions contribute to lowering physiological parameters such as fasting plasma glucose, glycated hemoglobin, and 2-hour postprandial glucose levels. Conclusion: Psychosocial supportive interventions can indeed positively affect self-care behaviors, lifestyle changes, and physiological parameters in women with GDM. Nurses can play a pivotal role in integrative management and can streamline the care for women with GDM during pregnancy and following birth, especially through psychosocial support interventions.
Objectives: The purpose of this study is to assess the antidiabetic effect and safety of Galgunhwangryunhwanggum-tang for type 2 diabetes without complications by analyzing related research. Methods: For a systematic review and meta-analysis, we searched for the antidiabetic effect and safety of Galgunhwangryunhwanggum-tang for type 2 diabetes without complications in 10 databases up to September 2021. Only randomized controlled trials were chosen. Results: In the treatment effectiveness analysis and meta-analysis, Galgunhwangryunhwanggum-tang had significant improvement effects on fasting plasma glucose level, 2-hour postprandial glucose level, glycated hemoglobin, fasting insulin, and homeostasis model assessment for insulin resistance compared to the control group when treated in parallel with oral glycemic drugs. Conclusion: Galgunhwangryunhwanggum-tang is effective in improving blood sugar and insulin resistance in type 2 diabetes patients without complications and can especially be considered in parallel treatment with oral hypoglycemic drugs. A large-scale randomized controlled clinical trial is required to complement the limitations presented in this study in the future.
This study evaluated the nutrient adequacy ratio (NAR) and depression based on the sleep duration of adult women using data from the Korea National Health and Nutrition Examination Survey (KNHANES) 2016 and 2018. A total of 4,507 subjects were divided into two groups: sleep hours<7 (lack of sleep, LS) and 7≤sleep hours (normal sleep, NS). For a more detailed analysis, the subjects were further divided into normal sleep with no depression (NSND) and lack of sleep with depression (LSWD) groups. When compared with NS group, the nutrient intake of the LS group was observed to be higher in carbohydrates (P<0.05) and thiamine (P<0.01), but had a significantly lower mean nutrient adequacy ratio (P<0.05). Also, the LS group showed a higher frequency of early menopause (P<0.001) and depression (P<0.05) than the NS group. In the analysis of anthropometry and blood parameters of the subjects based on their sleep duration, the LS group showed a lower body mass index (BMI, P<0.05), lower blood creatinine (P<0.01), glycated hemoglobin (P<0.05), and high-density lipoprotein (HDL) cholesterol (P<0.01) levels adjusted by age and menopause than the NS group. When compared to the NSND group, the LSWD group had a lower intake of cholesterol (P<0.05), vitamin A (P<0.05), vitamin C (P<0.05), and folic acid (P<0.05). There was no variation in the menopausal status, NAR, and mean nutrient adequacy ratio between the NSND and LSWD groups. However, there were differences in total blood cholesterol (P<0.05) and depression based on sleep duration. Apart from nutritional status, differences in BMI and blood parameters were observed based on sleep duration.
Treatment-induced neuropathy in diabetes (TIND) is a reversible neuropathy that occurs in patients with diabetes, usually after a fast improvement in glycemic control. TIND is defined as the sudden onset of neuropathic pain or autonomic dysfunction with a large improvement in glycemic control (glycated hemoglobin [HbA1c] level of ≥ 2% over 3 months). We report the first case of a 24-year-old woman with type 1 diabetes mellitus who developed TIND in Korea. Her HbA1c level had decreased from 16.7% to 7.3% within a 3-month period. She developed acute-onset, severe, and continuous burning pain affecting her back and lower extremities. She was administered tapentadol (50 mg), pregabalin (75 mg), and vitamin B with minerals twice daily for neuropathic pain. She complained of orthostatic hypotension; thus, midodrine (2.5 mg) and anti-embolic stockings were prescribed. She almost completely recovered 6 months after the onset. A physician should be aware of TIND and gradually reduce HbA1c levels to prevent the occurrence of TIDN. They must also try to provide relief from severe pain or autonomic dysfunction and emphasize on an almost complete recovery.
Purpose: The purpose of this study was to investigate the effect of family-centered interventions on improving health outcomes in children and adolescents with type 1 diabetes mellitus (T1DM). Methods: A literature search was conducted according to the PRISMA guidelines, using six electronic databases: EMBASE, CINAHL, Medline, CENTRAL, Scopus, and Web of Science. The inclusion criteria encompassed studies with populations of children and adolescents (age <18 years) and at least one parent/caregiver, or only parents/caregivers if the children were very young, and studies that investigated the health outcomes of children and parents/caregivers diagnosed with T1DM. Results: From 2,746 published studies, only nine studies met the inclusion criteria. The key interventions were non-technology-based interventions (n=4), technology-based interventions (n=2), and combined technology- and non-technology-based interventions (n=3). The interventions had effects on glycated hemoglobin, adherence to diabetes management, diabetes self-management behaviors, and parent-child teamwork in diabetes management. Other essential effects were children's quality of life, children's problem-solving skills, parents' quality of life, and parents' coping and depression. Conclusion: Family-centered interventions can effectively improve health outcomes in children and adolescents with T1DM. In the future, family-centered interventions integrated with other approaches, theories, and models should be developed to achieve the best possible outcomes.
Purpose: Systemic health has a profound effect on dental treatment. The aim of this study was to evaluate peri-implant bone loss and health screening data to discover factors that may influence peri-implant diseases. Methods: This study analyzed the panoramic X-rays of patients undergoing health screenings at the Health Promotion Center at Seoul St. Mary's Hospital in 2018, to investigate the relationship between laboratory test results and dental data. The patients' physical data, such as height, weight, blood pressure, hematological and urine analysis data, smoking habits, number of remaining teeth, alveolar bone level, number of implants, and degree of bone loss around the implant, were analyzed for correlations. Their associations with glycated hemoglobin, glucose, blood urea nitrogen (BUN), creatinine, and severity of periodontitis were evaluated using univariate and multivariate regression analysis. Results: In total, 2,264 patients opted in for dental health examinations, of whom 752 (33.2%) had undergone dental implant treatment. These 752 patients had a total of 2,658 implants, and 129 (17.1%) had 1 or more implants with peri-implant bone loss of 2 mm or more. The number of these implants was 204 (7%). Body mass index and smoking were not correlated with peri-implant bone loss. Stepwise multivariate regression analysis revealed that the severity of periodontal bone loss (moderate bone loss: odds ratio [OR], 3.154; 95% confidence interval [CI], 1.175-8.475 and severe bone loss: OR, 7.751; 95% CI, 3.003-20) and BUN (OR, 1.082; 95% CI, 1.027-1.141) showed statistically significant predictive value. The severity of periodontitis showed greater predictive value than the biochemical parameters of blood glucose, renal function, and liver function. Conclusions: The results of this study showed that periodontal bone loss was a predictor of peri-implant bone loss, suggesting that periodontal disease should be controlled before dental treatment. Diligent maintenance care is recommended for patients with moderate to severe periodontal bone loss.
The prevalence of metabolic syndrome (MetS) and its cost are increasing due to lifestyle changes and aging. This study aimed to develop a deep neural network model for prediction and classification of MetS according to nutrient intake and other MetS-related factors. This study included 17,848 individuals aged 40-69 years from the Korea National Health and Nutrition Examination Survey (2013-2018). We set MetS (3-5 risk factors present) as the dependent variable and 52 MetS-related factors and nutrient intake variables as independent variables in a regression analysis. The analysis compared and analyzed model accuracy, precision and recall by conventional logistic regression, machine learning-based logistic regression and deep learning. The accuracy of train data was 81.2089, and the accuracy of test data was 81.1485 in a MetS classification and prediction model developed in this study. These accuracies were higher than those obtained by conventional logistic regression or machine learning-based logistic regression. Precision, recall, and F1-score also showed the high accuracy in the deep learning model. Blood alanine aminotransferase (β = 12.2035) level showed the highest regression coefficient followed by blood aspartate aminotransferase (β = 11.771) level, waist circumference (β = 10.8555), body mass index (β = 10.3842), and blood glycated hemoglobin (β = 10.1802) level. Fats (cholesterol [β = -2.0545] and saturated fatty acid [β = -2.0483]) showed high regression coefficients among nutrient intakes. The deep learning model for classification and prediction on MetS showed a higher accuracy than conventional logistic regression or machine learning-based logistic regression.
BACKGROUND: To assess the interventricular septum (IVS) volume of fetuses from pre-gestational diabetes mellitus (DM) pregnant women by 3-dimensional ultrasound using spatiotemporal image correlation (STIC) and virtual organ computer-aided analysis (VOCAL) methods. METHODS: This was a prospective cross-sectional study of 45 fetuses from pre-gestational DM and 45 fetuses from healthy pregnant women (controls). Only singleton pregnancies between 20 and 34 + 6 weeks of gestation were included. The fetal IVS volumes were obtained off-line using STIC and VOCAL methods. To analyze differences among variables, the Student's t-test and Mann-Whitney U test were used. The correlation among continuous variables was determine using Spearman's correlation test (r). RESULTS: The median of fetal IVS volume was significantly higher in pre-gestational DM than in healthy pregnant women (0.3 cm3 vs. 0.2 cm3, p = 0.032). A strong positive correlation was observed between fetal IVS volume and gestational age at the time of ultrasound examination (r = 0.75, R2 = 0.48, p < 0.0001) and between fetal IVS volume and estimated fetal weight (r = 0.63, R2 = 0.37, p < 0.0001). No significant correlation was noted between fetal IVS volume and glycated hemoglobin levels (r = -0.16, R2 = 0.01, p = 0.540) in the pre-gestational DM pregnant women. CONCLUSIONS: Significant differences were observed in fetal IVS volumes between pre-gestational and healthy mothers, with higher values in the fetuses of pre-gestational DM pregnant women.
Background: Statins reduce the risk of cardiovascular events in patients with chronic kidney disease (CKD). Although diabetes mellitus (DM) is a reported side effect of statin treatment, some studies have indicated that pitavastatin does not cause DM. The present study investigated the effect of pitavastatin on the fatty acid (FA) content of erythrocyte membranes, which affects the occurrence of DM and cardiovascular diseases. In addition, changes in adiponectin and glycated hemoglobin (HbA1c) levels were evaluated after pitavastatin treatment. Methods: A total of 45 patients were enrolled, 28 of whom completed the study. Over 24 weeks, 16 patients received 2 mg pitavastatin and 12 patients received 10 mg atorvastatin. Dosages were adjusted after 12 weeks if additional lipid control was required. There were 10 and nine patients with DM in the pitavastatin and atorvastatin groups, respectively. Erythrocyte membrane FAs and adiponectin levels were measured using gas chromatography and enzyme-linked immunosorbent assay, respectively. Results: In both groups, saturated FAs, palmitic acid, trans-oleic acid, total cholesterol, and low-density lipoprotein cholesterol levels were significantly lower than those at baseline. The arachidonic acid (AA) content in the erythrocyte membrane increased significantly in the pitavastatin group, but adiponectin levels were unaffected. HbA1c levels decreased in patients treated with pitavastatin. No adverse effects were associated with statin treatment. Conclusion: Pitavastatin treatment in patients with CKD may improve glucose metabolism by altering erythrocyte membrane AA levels. In addition, pitavastatin did not adversely affect glucose control in patients with CKD and DM.
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