Kyu Yeon Hur, Min Kyong Moon, Jong Suk Park, Soo-Kyung Kim, Seung-Hwan Lee, Jae-Seung Yun, Jong Ha Baek, Junghyun Noh, Byung-Wan Lee, Tae Jung Oh, Suk Chon, Ye Seul Yang, Jang Won Son, Jong Han Choi, Kee Ho Song, Nam Hoon Kim, Sang Yong Kim, Jin Wha Kim, Sang Youl Rhee, You-Bin Lee, Sang-Man Jin, Jae Hyeon Kim, Chong Hwa Kim, Dae Jung Kim, SungWan Chun, Eun-Jung Rhee, Hyun Min Kim, Hyun Jung Kim, Donghyun Jee, Jae Hyun Kim, Won Seok Choi, Eun-Young Lee, Kun-Ho Yoon, Seung-Hyun Ko, Committee of Clinical Practice Guidelines, Korean Diabetes Association
Diabetes Metab J. 2021;45(4):461-481. Published online July 30, 2021
The Committee of Clinical Practice Guidelines of the Korean Diabetes Association (KDA) updated the previous clinical practice guidelines for Korean adults with diabetes and prediabetes and published the seventh edition in May 2021. We performed a comprehensive systematic review of recent clinical trials and evidence that could be applicable in real-world practice and suitable for the Korean population. The guideline is provided for all healthcare providers including physicians, diabetes experts, and certified diabetes educators across the country who manage patients with diabetes or the individuals at the risk of developing diabetes mellitus. The recommendations for screening diabetes and glucose-lowering agents have been revised and updated. New sections for continuous glucose monitoring, insulin pump use, and non-alcoholic fatty liver disease in patients with diabetes mellitus have been added. The KDA recommends active vaccination for coronavirus disease 2019 in patients with diabetes during the pandemic. An abridgement that contains practical information for patient education and systematic management in the clinic was published separately.
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The role of ectopic adipose tissue infiltration into skeletal muscle (i.e., myosteatosis) for metabolic disorders has received considerable and increasing attention in the last 10 years. The purpose of this review was to evaluate and summarize existing studies focusing on computed tomography (CT)-derived measures of myosteatosis and metabolic disorders. There is consistent evidence that CT-derived myosteatosis contributes to dysglycemia, insulin resistance, type 2 diabetes mellitus, and inflammation, and, to some extent, dyslipidemia, independent of general obesity, visceral fat, and other relevant risk factors, suggesting that it may serve as a tool for metabolic risk prediction. Identification of which muscles should be examined, and the standardized CT protocols to be employed, are necessary to enhance the applicability of findings from epidemiologic studies of myosteatosis. Additional and longer longitudinal studies are necessary to confirm a role of myosteatosis in the development of type 2 diabetes mellitus, and examine these associations in a variety of muscles across multiple race/ethnic populations. Given the emerging role of myosteatosis in metabolic health, well-designed intervention studies are needed to investigate relevant lifestyle and pharmaceutical approaches.
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Cardiovascular disease is the primary cause of mortality in women and men with diabetes. Due to age and worsening of risk factors over the menopausal transition, risk of coronary heart disease events increases in postmenopausal women with diabetes. Randomized studies have conflicted regarding the beneficial impact of estrogen therapy upon intermediate cardiovascular disease markers and events. Therefore, estrogen therapy is not currently recommended for indications other than symptom management. However, for women at low risk of adverse events, estrogen therapy can be used to minimize menopausal symptoms. The risk of adverse events can be estimated using risk engines for the calculation of cardiovascular risk and breast cancer risk in conjunction with screening tools such as mammography. Use of estrogen therapy, statins, and anti-platelet agents can be guided by such calculators particularly for younger women with diabetes. Risk management remains focused upon lifestyle behaviors and achieving optimal levels of cardiovascular risk factors, including lipids, glucose, and blood pressure. Use of pharmacologic therapies to address these risk factors, particularly specific hypoglycemic agents, may provide some additional benefit for risk prevention. The minimal benefit for women with limited life expectancy and risk of complications with intensive therapy should also be considered.
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Background Using real-world data, cardiovascular safety was investigated in metformin users newly starting sodium glucose cotransporter 2 (SGLT2) inhibitors compared with other glucose-lowering drugs in Korea.
Methods This was a retrospective observational study using the National Health Insurance Service claims database in Korea. The study period was from September 2014 to December 2016. The study included subjects who were newly prescribed SGLT2 inhibitors or other glucose-lowering drugs while on metformin monotherapy; cohort 1 was composed of new users of SGLT2 inhibitors versus dipeptidyl peptidase-4 (DPP-4) inhibitors and cohort 2 included new users of SGLT2 inhibitors versus sulfonylureas. To balance the patient characteristics, propensity score matching was performed at a 1:1 ratio. Cardiovascular outcomes included hospitalization for heart failure (HHF), all-cause mortality, HHF plus all-cause mortality, myocardial infarction (MI), stroke, and modified major adverse cardiovascular events (MACEs).
Results After propensity score matching, each cohort group was well balanced at baseline (21,688 pairs in cohort 1 and 20,120 pairs in cohort 2). As the second-line treatment, use of SGLT2 inhibitors was associated with a lower risk of HHF and HHF plus all-cause mortality compared with DPP-4 inhibitors. In addition, use of SGLT2 inhibitors versus sulfonylurea as add-on therapy to metformin was associated with decreased risks of HHF, all-cause mortality, HHF plus all-cause mortality, MI, stroke, and modified MACEs.
Conclusion SGLT2 inhibitors can be a good second-line drug to reduce the incidence of cardiovascular diseases compared with DPP-4 inhibitors or sulfonylureas in people with type 2 diabetes mellitus.
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Background Previously developed prediction models for type 2 diabetes mellitus (T2DM) have limited performance. We developed a deep learning (DL) based model using a cohort representative of the Korean population.
Methods This study was conducted on the basis of the National Health Insurance Service-Health Screening (NHIS-HEALS) cohort of Korea. Overall, 335,302 subjects without T2DM at baseline were included. We developed the model based on 80% of the subjects, and verified the power in the remainder. Predictive models for T2DM were constructed using the recurrent neural network long short-term memory (RNN-LSTM) network and the Cox longitudinal summary model. The performance of both models over a 10-year period was compared using a time dependent area under the curve.
Results During a mean follow-up of 10.4±1.7 years, the mean frequency of periodic health check-ups was 2.9±1.0 per subject. During the observation period, T2DM was newly observed in 8.7% of the subjects. The annual performance of the model created using the RNN-LSTM network was superior to that of the Cox model, and the risk factors for T2DM, derived using the two models were similar; however, certain results differed.
Conclusion The DL-based T2DM prediction model, constructed using a cohort representative of the population, performs better than the conventional model. After pilot tests, this model will be provided to all Korean national health screening recipients in the future.
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Background Diabetic peripheral neuropathy (DPN) is one of the most serious complications of type 2 diabetes mellitus (T2DM). DPN increases the risk of ulcers, foot infections, and noninvasive amputations, ultimately leading to long-term disability.
Methods Seven hundred patients with T2DM were investigated from 2013 to 2017 in the Sanlin community by obtaining basic data from the electronic medical record system (EMRS). From September 2018 to July 2019, 681 patients (19 missing) were investigated using a questionnaire, physical examination, biochemical index test, and follow-up Toronto clinical scoring system (TCSS) test. Patients with a TCSS score ≥6 points were diagnosed with DPN. After removing missing values, 612 patients were divided into groups in a 3:1 ratio for external validation. Using different Lasso analyses (misclassification error, mean squared error, –2log-likelihood, and area under curve) and a logistic regression analysis of the training set, models A, B, C, and D were established. The receiver operating characteristic (ROC) curve, calibration plot, dynamic component analysis (DCA) measurements, net classification improvement (NRI) and integrated discrimination improvement (IDI) were used to validate discrimination and clinical practicality of the model.
Results Through data analysis, model A (containing four factors), model B (containing five factors), model C (containing seven factors), and model D (containing seven factors) were built. After calibration, ROC curve, DCA, NRI and IDI, models C and D exhibited better accuracy and greater predictive power.
Conclusion Four prediction models were established to assist with the early screening of DPN in patients with T2DM. The influencing factors in model C and D are more important factors for patients with T2DM diagnosed with DPN.
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Background This study aimed to evaluate the dose-dependent effects of smoking on risk of diabetes among those quitting smoking.
Methods We analyzed clinical data from a total of 5,198,792 individuals age 20 years or older who received health care check-up arranged by the national insurance program of Korea between 2009 and 2016 using the Korean National Health Insurance Service database. Cumulative smoking was estimated by pack-years. Smokers were classified into four categories according to the amount of smoking: light smokers (0.025 to 5 smoking pack-years), medium smokers (5 to 14 smoking pack-years), heavy smokers (14 to 26 smoking pack-years), and extreme smokers (more than 26 smoking pack-years).
Results During the study period, 164,335 individuals (3.2% of the total population) developed diabetes. Compared to sustained smokers, the risk of diabetes was significantly reduced in both quitters (hazard ratio [HR], 0.858; 95% confidence interval [CI], 0.838 to 0.878) and nonsmokers (HR, 0.616; 95% CI, 0.606 to 0.625) after adjustment for multiple risk factors. The risk of diabetes gradually increased with amount of smoking in both quitters and current smokers. The risk of diabetes in heavy (HR, 1.119; 95% CI, 1.057 to 1.185) and extreme smokers (HR, 1.348; 95% CI, 1.275 to 1.425) among quitters was much higher compared to light smokers among current smokers.
Conclusion Smoking cessation was effective in reducing the risk of diabetes regardless of weight change. However, there was a potential dose-dependent association between smoking amount and the development of diabetes. Diabetes risk still remained in heavy and extreme smokers even after smoking cessation.
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Background Fetal abdominal obesity (FAO) has been reported to be affected at gestational diabetes mellitus (GDM) diagnosis at 24 to 28 weeks of gestation in older and/or obese women. This study investigated whether the management of GDM improves FAO in GDM subjects near term.
Methods Medical records of 7,099 singleton pregnant women delivering at CHA Gangnam Medical Center were reviewed retrospectively. GDM was diagnosed by 100-g oral glucose tolerance test after 50-g glucose challenge test based on Carpenter–Coustan criteria. GDM subjects were divided into four study groups according to maternal age and obesity. FAO was defined as ≥90th percentile of fetal abdominal overgrowth ratios (FAORs) of the ultrasonographically estimated gestational age (GA) of abdominal circumference per actual GA by the last menstruation period, biparietal diameter, or femur length, respectively.
Results As compared with normal glucose tolerance (NGT) subjects near term, FAORs and odds ratio for FAO were significantly higher in old and/or obese women with GDM but not in young and nonobese women with GDM. For fetuses of GDM subjects with FAO at the time of GDM diagnosis, the odds ratio for exhibiting FAO near term and being large for GA at birth were 7.87 (95% confidence interval [CI], 4.38 to 14.15) and 10.96 (95% CI, 5.58 to 20.53) compared with fetuses of NGT subjects without FAO at GDM diagnosis.
Conclusion Despite treatment, FAO detected at the time of GDM diagnosis persisted until delivery. Early diagnosis and treatment might be necessary to prevent near term FAO in high-risk older and/or obese women.
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Background Organochlorine pesticides (OCPs) exposure may induce an endocrine disruption which may lead to the risk of developing diabetes through alteration and disturbance of glucose metabolism, insulin resistance, and destruction of β-cells. The present study determines the recent trend of OCPs residue in blood samples and their association with the known risk factors responsible for developing the risk of diabetes among the North Indian population.
Methods Blood sample of 300 patients (100 each of normal glucose tolerance [NGT], prediabetes and newly detected diabetes mellitus [DM]) between the age group of 30 to 70 years were collected. OCPs residue in whole blood samples was analyzed by using gas chromatography equipped with a 63Ni selective electron capture detector.
Results Significantly higher levels of β-hexachlorocyclohexane (HCH), dieldrin, and p,p’-dichloro-diphenyl-dichloroethylene (DDE) were found in the prediabetes and newly detected DM groups as compared to NGT group. Insulin resistance showed to be significantly positive correlation with β-HCH and dieldrin. Also, fasting and postprandial glucose levels were significantly positively correlated with levels of β-HCH, dieldrin, and p,p’-DDE. Further, when OCPs level was adjusted for age and body mass index (BMI), it was found that β-HCH, dieldrin, and p,p’-DDE levels in blood increases the risk of diabetes by 2.70, 2.83, and 2.55 times respectively. Moreover, when we adjust OCPs level based on BMI categories (BMI <23, ≥23, and ≤25, and >25 kg/m2); β-HCH and p,p’-DDE showed a significant risk of developing newly detected DM with BMI >25 and ≥23 and ≤25 kg/m2.
Conclusion The OCPs level present in the environment may be responsible for biological, metabolic, and endocrine disruptions within the human body which may increase the risk of developing newly detected DM. Hence, OCPs exposure can play a crucial role in the etiology of diabetes.
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Background Recently, a metabolic syndrome severity score (MS score) using a dataset of the Korea National Health and Nutrition Examination Surveys has been developed. We aimed to determine whether the newly developed score is a significant predictor of cardiovascular (CV) events among the Korean population.
Methods From the Korean National Health Insurance System, 2,541,364 (aged 40 to 59 years) subjects with no history of CV events (ischemic stroke or myocardial infarction [MI]), who underwent health examinations from 2009 to 2011 and were followed up until 2014 to 2017, were identified. Cox proportional hazard model was employed to investigate the association between MS score and CV events. Model performance of MS score for predicting CV events was compared to that of conventional metabolic syndrome diagnostic criteria (Adult Treatment Program III [ATP-III]) using the Akaike information criterion and the area under the receiver operating characteristic curve.
Results Over a median follow-up of 6 years, 15,762 cases of CV events were reported. MS score at baseline showed a linear association with incident CV events. In the multivariable-adjusted model, the hazard ratios (95% confidence intervals) comparing the highest versus lowest quartiles of MS score were 1.48 (1.36 to 1.60) for MI and 1.89 (1.74 to 2.05) for stroke. Model fitness and performance of the MS score in predicting CV events were superior to those of ATP-III.
Conclusion The newly developed age- and sex-specific continuous MS score for the Korean population is an independent predictor of ischemic stroke and MI in Korean middle-aged adults even after adjusting for confounding factors.
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Background Vascular complications are the major morbid consequences of type 2 diabetes mellitus (T2DM). The transcription factor 7-like 2 (TCF7L2), potassium voltage-gated channel subfamily Q member 1 (KCNQ1), and inwardly-rectifying potassium channel, subfamily J, member 11 gene (KCNJ11) are common T2DM susceptibility genes in various populations. However, the associations between polymorphisms in these genes and diabetic complications are controversial. This study aimed to investigate the effects of combined gene-polymorphisms within TCF7L2, KCNQ1, and KCNJ11 on vascular complications in Thai subjects with T2DM.
Methods We conducted a case-control study comprising 960 T2DM patients and 740 non-diabetes controls. Single nucleotide polymorphisms in TCF7L2, KCNQ1, and KCNJ11 were genotyped and evaluated for their association with diabetic vascular complications.
Results The gene variants TCF7L2 rs290487-T, KCNQ1 rs2237892-C, and KCNQ1 rs2237897-C were associated with increased risk of T2DM. TCF7L2 rs7903146-C, TCF7L2 rs290487-C, KCNQ1 rs2237892-T, and KCNQ1 rs2237897-T revealed an association with hypertension. The specific combination of risk-alleles that have effects on T2DM and hypertension, TCF7L2 rs7903146-C, KCNQ1 rs2237892-C, and KCNQ1 rs2237897-T, as genetic risk score (GRS), pronounced significant association with coronary artery disease (CAD), cumulative nephropathy and CAD, and cumulative microvascular and macrovascular complications (respective odds ratios [ORs] with 95% confidence interval [95% CI], comparing between GRS 2–3 and GRS 5–6, were 7.31 [2.03 to 26.35], 3.92 [1.75 to 8.76], and 2.33 [1.13 to 4.79]).
Conclusion This study demonstrated, for the first time, the effect conferred by specific combined genetic variants in TCF7L2 and KCNQ1 on diabetic vascular complications, predominantly with nephropathy and CAD. Such a specific pattern of gene variant combination may implicate in the progression of T2DM and life-threatening vascular complications.
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Background We previously, reported that granulocyte-colony stimulating factor (G-CSF) reduces cardiomyocyte apoptosis in diabetic cardiomyopathy. However, the underlying mechanisms are not yet fully understood. Therefore, we investigated whether the mechanisms underlying of the anti-apoptotic effects of G-CSF were associated with autophagy using a rat model of diabetic cardiomyopathy.
Methods Diabetic cardiomyopathy was induced in rats through a high-fat diet combined with low-dose streptozotocin and the rats were then treated with G-CSF for 5 days. Rat H9c2 cardiac cells were cultured under high glucose conditions as an in vitro model of diabetic cardiomyopathy. The extent of apoptosis and protein levels related to autophagy (Beclin-1, microtubule-binding protein light chain 3 [LC3]-II/LC3-I ratio, and P62) were determined for both models. Autophagy determination was performed using an Autophagy Detection kit.
Results G-CSF significantly reduced cardiomyocyte apoptosis in the diabetic myocardium in vivo and led to an increase in Beclin-1 level and the LC3-II/LC3-I ratio, and decreased P62 level. Similarly, G-CSF suppressed apoptosis, increased Beclin-1 level and LC3-II/LC3-I ratio, and decreased P62 level in high glucose-induced H9c2 cardiac cells in vitro. These effects of G-CSF were abrogated by 3-methyladenine, an autophagy inhibitor. In addition, G-CSF significantly increased autophagic flux in vitro.
Conclusion Our results suggest that the anti-apoptotic effect of G-CSF might be significantly associated with the up-regulation of autophagy in diabetic cardiomyopathy.
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Diabetes Metab J. 2021;45(4):606-612. Published online September 9, 2020
The purpose of this extension study was to assess the long-term efficacy and safety of gemigliptin 50 mg in patients with type 2 diabetes mellitus (T2DM). Patients with T2DM who had completed the initial 24-week study comparing gemigliptin monotherapy with placebo were eligible to enrol. In the open-label, 28-week extension study, all enrolled patients received gemigliptin, regardless of the treatment received during the initial 24-week study period. The mean reduction±standard deviation (SD) in glycosylated hemoglobin (HbA1c) observed after 24 weeks of treatment (–0.6%±1.1%) was further decreased for the gemi-gemi group and the mean change in HbA1c at week 52 from baseline was –0.9%±1.2% (P<0.0001). For the pbo-gemi group, HbA1c decreased after they were switched to gemigliptin, and the mean change in HbA1c at week 52 from baseline was –0.7%±1.2% (P<0.0001). Furthermore, the overall incidence of adverse events demonstrated that gemigliptin was safe and well tolerated up to 52 weeks.
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