Impact of hypoglycemia at the time of hospitalization for heart failure from emergency department on major adverse cardiovascular events in patients with and without type 2 diabetes.

BACKGROUND: Few studies have examined the association between hypoglycemic episodes among people with type 2 diabetes (T2DM) at the time of hospitalization for heart failure (HF) and cardiovascular outcomes. METHODS: From March 2016 to June 2018, we conducted a retrospective cohort study to investigate hypoglycemia during HF hospitalization in the emergency department, three-point major adverse cardiovascular events (3P-MACE), and all-cause mortality; these were followed up through June 2021. HF hospitalization was defined according to American Heart Association criteria. Hypoglycemia was defined as a glucose level < 3.9 mmol/L at the time of HF hospitalization. We classified the enrolled patients into three groups (reference group, those without T2DM or hypoglycemia; those diagnosed with T2DM without hypoglycemia; and those with hypoglycemia and T2DM). We used Cox proportional hazard regression analysis to investigate the association between the three groups and the development of the first occurrence of 3P-MACE and all-cause mortality. RESULTS: During a median of 25 months of follow-up, a total of 783 patients admitted due to HF were analyzed. In total, 159 (20.3%) cases of 3P-MACE were identified, and the mortality rate was 20.2% (n = 158). The median age of patients was 76.0 (65.0-82.0) years, and 49.0% were men. Patients with 3P-MACE had a lower body mass index (22.6 [20.4-25.1] vs. 23.8 [21.3-26.7]), higher frequency of previous history of HF (24.5% vs. 15.7%), T2DM (64.2% vs. 47.3%), higher rates of hypoglycemia at the time of HF hospitalization (19.5% vs. 7.7%), and lower eGFR levels (61.1 [36.0-80.7] mL/min/1.73 m2 vs. 69.2 [45.8-89.5] mL/min/1.73 m2) than those without 3P-MACE. The multivariable adjusted HR of 3P-MACE was as follows: group with hypoglycemia and T2DM: HR, 2.29; 95% CI: 1.04-5.06; group with T2DM without hypoglycemia: HR: 1.42; 95% CI: 0.86-2.33; and all-cause mortality group with hypoglycemia and T2DM: HR: 2.58; 95% CI: 1.26-5.31, group with T2DM without hypoglycemia: HR: 1.32; 95% CI: 0.81-2.16; compared to the reference group (group without T2DM or hypoglycemia). CONCLUSIONS: T2DM and hypoglycemia are independent risk factors for 3P-MACE and all-cause mortality compared to those without hypoglycemia during HF hospitalization.

A deep learning model for screening type 2 diabetes from retinal photographs.

BACKGROUND AND AIMS: We aimed to develop and evaluate a non-invasive deep learning algorithm for screening type 2 diabetes in UK Biobank participants using retinal images. METHODS AND RESULTS: The deep learning model for prediction of type 2 diabetes was trained on retinal images from 50,077 UK Biobank participants and tested on 12,185 participants. We evaluated its performance in terms of predicting traditional risk factors (TRFs) and genetic risk for diabetes. Next, we compared the performance of three models in predicting type 2 diabetes using 1) an image-only deep learning algorithm, 2) TRFs, 3) the combination of the algorithm and TRFs. Assessing net reclassification improvement (NRI) allowed quantification of the improvement afforded by adding the algorithm to the TRF model. When predicting TRFs with the deep learning algorithm, the areas under the curve (AUCs) obtained with the validation set for age, sex, and HbA1c status were 0.931 (0.928-0.934), 0.933 (0.929-0.936), and 0.734 (0.715-0.752), respectively. When predicting type 2 diabetes, the AUC of the composite logistic model using non-invasive TRFs was 0.810 (0.790-0.830), and that for the deep learning model using only fundus images was 0.731 (0.707-0.756). Upon addition of TRFs to the deep learning algorithm, discriminative performance was improved to 0.844 (0.826-0.861). The addition of the algorithm to the TRFs model improved risk stratification with an overall NRI of 50.8%. CONCLUSION: Our results demonstrate that this deep learning algorithm can be a useful tool for stratifying individuals at high risk of type 2 diabetes in the general population.

Efficacy of Personalized Diabetes Self-care Using an Electronic Medical Record-Integrated Mobile App in Patients With Type 2 Diabetes: 6-Month Randomized Controlled Trial.

BACKGROUND: A system that combines technology and web-based coaching can help treat chronic conditions such as diabetes. However, the effectiveness of apps in mobile health (mHealth) interventions is inconclusive and unclear due to heterogeneous interventions and varying follow-up durations. In addition, randomized controlled trial data are limited, and long-term follow-up is lacking, especially for apps integrated into electronic medical records. OBJECTIVE: We aimed to assess the effect of an electronic medical record-integrated mobile app for personalized diabetes self-care, focusing on the self-monitoring of blood glucose and lifestyle modifications, on glycemic control in patients with type 2 diabetes mellitus. METHODS: In a 26-week, 3-arm, randomized, controlled, open-label, parallel group trial, patients with type 2 diabetes mellitus and a hemoglobin A1c (HbA1c) level of ≥7.5% were recruited. The mHealth intervention consisted of self-monitoring of blood glucose with the automatic transfer of glucose, diet, and physical activity counseling data (iCareD system). Participants were randomly assigned to the following three groups: usual care (UC), mobile diabetes self-care (MC), and MC with personalized, bidirectional feedback from physicians (MPC). The primary outcome was the change in HbA1c levels at 26 weeks. In addition, diabetes-related self-efficacy, self-care activities, and satisfaction with the iCareD system were assessed after the intervention. RESULTS: A total of 269 participants were enrolled, and 234 patients (86.9%) remained in the study at 26 weeks. At 12 weeks after the intervention, the mean decline in HbA1c levels was significantly different among the 3 groups (UC vs MC vs MPC: -0.49% vs -0.86% vs -1.04%; P=.02). The HbA1c level decreased in all groups; however, it did not differ among groups after 26 weeks. In a subgroup analysis, HbA1c levels showed a statistically significant decrease after the intervention in the MPC group compared with the change in the UC or MC group, especially in patients aged <65 years (P=.02), patients with a diabetes duration of ≥10 years (P=.02), patients with a BMI of ≥25.0 kg/m2 (P=.004), patients with a C-peptide level of ≥0.6 ng/mL (P=.008), and patients who did not undergo treatment with insulin (P=.004) at 12 weeks. A total of 87.2% (137/157) of the participants were satisfied with the iCareD system. CONCLUSIONS: The mHealth intervention for diabetes self-care showed short-term efficacy in glycemic control, and the effect decreased over time. The participants were comfortable with using the iCareD system and exhibited high adherence. TRIAL REGISTRATION: Clinical Research Information Service, Republic of Korea KCT0004128; https://tinyurl.com/bdd6pa9m.

Optimal fasting plasma glucose and haemoglobin A1c levels for screening of prediabetes and diabetes according to 2-hour plasma glucose in a high-risk population: The Korean Diabetes Prevention Study.

BACKGROUND: The primary aim of this study was to assess the utility of fasting plasma glucose (FPG) and HbA1c to identify diabetes by the 2-hour plasma glucose (PG) criterion in the Korean population at high risk for diabetes. METHODS: A total of 1646 participants with a body mass index of ≥23 kg/m2 without having a history of diabetes were recruited in this study. The cut-off values of FPG and HbA1c for detecting diabetes were identified using the Youden index using receiver operating characteristic (ROC) analysis. The gold standard for diabetes prediction was defined by the 2-hour PG level of ≥200 mg/dL. RESULTS: The participants comprised 54.0% women, and the mean age of all participants was 55.0 ± 8.1 years. At baseline, FPG was 104.1 ± 14.2 mg/dL, the 2-hour PG value was 162.9 ± 55.3 mg/dL, and HbA1c was 5.9% ± 0.5%. Four hundred and forty-six subjects (27.1%) were diagnosed with diabetes and 976 subjects (59.3%) were determined to be at prediabetes. The area under the ROC curve (AUC) of FPG and HbA1c for diabetes were 0.776 and 0.802, while the AUC of FPG and HbA1c for prediabetes were 0.515 and 0.477. The optimal cut-off value for diagnosing diabetes of FPG and HbA1c were 104.5 mg/dL (sensitivity 75.8%, specificity 67.5%) and 5.9% (sensitivity 80.6%, specificity 63.8%), respectively. CONCLUSIONS: FPG of 104.5 mg/dL and HbA1c value of 5.9% (41 mmol/mol) can be used as an optimal screening value for diabetes by 2-hour PG criterion in the Korean population at high risk for diabetes.

Severe hypoglycemia and the risk of cardiovascular disease and mortality in type 2 diabetes: a nationwide population-based cohort study.

BACKGROUND: We investigated the association regarding severe hypoglycemia episodes with cardiovascular disease risk and all-cause mortality in patients with type 2 diabetes. METHODS: Baseline and follow-up data (n = 1,568,097) from patients with type 2 diabetes were retrieved from the National Health Insurance System database (covering the entire Korean population). Type 2 diabetes, severe hypoglycemia, and major comorbidities were identified using International Classification of Diseases 10 codes and medication information. Individuals who were classified as type 2 diabetes in the year of 2009 were screened, and we counted severe hypoglycemia episodes from 2007 to 2009. The primary outcome was newly developed myocardial infarction (MI), stroke, heart failure, or all-cause mortality. Participants were followed from the baseline index date to the date of death or until December 31, 2015. RESULTS: In total, 19,660 (1.2%) patients developed at least one severe hypoglycemia event during the period from 2007 to 2009. Mean follow-up was 5.7 years. After adjustment for confounding factors, the hazard ratio (HR) of MI significantly and sequentially increased: 0 vs. 1 episode, HR 1.56, 95% CI 1.46-1.64; 0 vs. 2 episodes, HR 1.86, 95% CI 1.61-2.15; 0 vs. 3 or more episodes, HR 1.86, 95% CI 1.48-2.35, P for trend < 0.001. Similar findings were noted regarding the relationship of severe hypoglycemia episodes with stroke, heart failure, and all-cause mortality. Risks for all outcomes were highest within 1 year from the index date and showed decreasing trends with follow-up. Sensitivity analyses of the data from the subgroup population and 797,544 subjects who received a national health examination did not change the significance of the main findings. CONCLUSION: Among adult Korean patients with type 2 diabetes, a severe hypoglycemia episode is associated with increased risk for cardiovascular outcomes and all-cause mortality. Significant results from dose-response, temporal, and sensitivity analyses may suggest the possibility of direct causality between severe hypoglycemia and cardiovascular outcomes and mortality.

Progression of cardiovascular autonomic neuropathy and cardiovascular disease in type 2 diabetes.

BACKGROUND: To examine whether the progression rate of cardiovascular autonomic neuropathy (CAN) stage is an independent predictive factor for cardiovascular disease (CVD) in type 2 diabetes. METHODS: Standardized cardiovascular autonomic reflex tests (CARTs) using traditional Ewing method were performed at baseline. The follow-up CARTs was recommended once every two years. We estimated the primary CVD endpoint, defined as coronary artery disease and ischemic stroke. The association between the progression rate of CAN stage and CVD was examined using time-dependent Cox proportional hazard models. RESULTS: At baseline, 578 patients completed follow-up CARTs; the cohort comprised 329 women (56.9%) with a mean age of 58.3 ± 10.3 years and a mean diabetes duration of 10.1 ± 6.2 years. One hundred and seventy-six patients (30.4%) developed CAN progression between baseline and follow-up CARTs. In the multivariable Cox proportional hazards regression analysis, patients with CAN progression demonstrated a 3.32 times higher risk (95% confidence interval, CI 1.81-6.14, P < 0.001) of CVD than those without CAN progression. Patients who experienced CAN progression from the normal to definite stage had the greatest risk of CVD compared to other patients (hazard ratio 4.91, 95% CI 2.05-11.77, P for trend = 0.001). CONCLUSIONS: CAN stage progression was associated with an increased risk of CVD in this type 2 diabetes cohort. Patients with rapid CAN progression had the greatest risk of CVD. Thus, regular screening and risk management of CAN progression is necessary to prevent CVD.

A comparison of effects of DPP-4 inhibitor and SGLT2 inhibitor on lipid profile in patients with type 2 diabetes.

BACKGROUND: Previous studies suggest that dipeptidyl peptidase-4 (DPP-4) inhibitors and sodium glucose cotransporter 2 (SGLT2) inhibitors have different effects on the lipid profile in patients with type 2 diabetes. We investigated the effects of DPP-4 inhibitors and SGLT2 inhibitors on the lipid profile in patients with type 2 diabetes. METHODS: From January 2013 to December 2015, a total of 228 patients with type 2 diabetes who were receiving a DPP-4 inhibitor or SGLT2 inhibitor as add-on therapy to metformin and/or a sulfonylurea were consecutively enrolled. We compared the effects of DPP-4 inhibitors and SGLT2 inhibitors on the lipid profile at baseline and after 24 weeks of treatment. To compare lipid parameters between the two groups, we used the analysis of covariance (ANCOVA). RESULTS: A total of 184 patients completed follow-up (mean age: 53.1 ± 6.9 years, mean duration of diabetes: 7.1 ± 5.7 years). From baseline to 24 weeks, HDL-cholesterol (HDL-C) levels were increased by 0.5 (95% CI, -0.9 to 2.0) mg/dl with a DPP-4 inhibitor and by 5.1 (95% CI, 3.0 to 7.1) mg/dl with an SGLT2 inhibitor (p = 0.001). LDL-cholesterol (LDL-C) levels were reduced by 8.4 (95% CI, -14.0 to -2.8) mg/dl with a DPP-4 inhibitor, but increased by 1.3 (95% CI, -5.1 to 7.6) mg/dl with an SGLT2 inhibitor (p = 0.046). There was no significant difference in the mean hemoglobin A1c (8.3 ± 1.1 vs. 8.0 ± 0.9%, p = 0.110) and in the change of total cholesterol (TC) (p = 0.836), triglyceride (TG) (p = 0.867), apolipoprotein A (p = 0.726), apolipoprotein B (p = 0.660), and lipoprotein (a) (p = 0.991) between the DPP-4 inhibitor and the SGLT2 inhibitor. CONCLUSIONS: The SGLT2 inhibitor was associated with a significant increase in HDL-C and LDL-C after 24 weeks of SGLT2 inhibitor treatment in patients with type 2 diabetes compared with those with DPP-4 inhibitor treatment in this study. TRIAL REGISTRATION: This study was conducted by retrospective medical record review.

Community-based randomized controlled trial of diabetes prevention study for high-risk individuals of type 2 diabetes: lifestyle intervention using web-based system.

BACKGROUND: The trend of increasing numbers of patients with type 2 diabetes emphasizes the need for active screening of high-risk individuals and intensive lifestyle modification (LSM). METHODS/DESIGN: The community-based Korean Diabetes Prevention Study (C-KDPS) is a randomized controlled clinical trial to prevent type 2 diabetes by intensive LSM using a web-based program. The two public healthcare centers in Korea are involved, and 420 subjects are being recruited for 6 months and will be followed up for 22 months. The participants are allocated randomly to intensive LSM (18 individual sessions for 24 weeks) and usual care (control group). The major goals of the C-KDPS lifestyle intervention program are: 1) a minimum of 5-7% loss of initial body weight in 6 months and maintenance of this weight loss, 2) increased physical activity (≥ 150 min/week of moderate intensity activity), 3) balanced healthy eating, and 4) quitting smoking and alcohol with stress management. The web-based program includes education contents, video files, visit schedules, and inter-communicable keeping track sites. Primary outcomes are the diagnoses of newly developed diabetes. A 75-g oral glucose tolerance test with hemoglobin A1c level determination and cardiovascular risk factor assessment is scheduled at 6, 12, 18, and 22 months. DISCUSSION: Active screening of high-risk individuals and an effective LSM program are an essential prerequisite for successful diabetes prevention. We hope that our C-KDPS program can reduce the incidence of newly developed type 2 diabetes and be implemented throughout the country, merging community-based public healthcare resources and a web-based system. TRIAL REGISTRATION: Clinical Research Information Service (CRIS), Republic of Korea (No. KCT0001981 ). Date of registration; July 28, 2016.

Heart rate-corrected QT interval prolongation is associated with decreased heart rate variability in patients with type 2 diabetes.

We investigated the association between the heart rate-corrected QT interval (QTc interval) measured by standard electrocardiography and heart rate variability (HRV) in patients with type 2 diabetes mellitus (T2DM). From March 1, 2009, to December 12, 2009, 411 patients with T2DM who underwent resting 12-lead electrocardiography and cardiovascular autonomic function testing concurrently without the exclusion criteria were consecutively recruited in this cross-sectional study. Time- and frequency-domain HRV variables were assessed for 5 minutes by beat-to-beat HRV recording. The QT interval was corrected for the heart rate using Bazett's formula. QTc interval measurements of >440 ms were considered abnormally prolonged. The mean age and diabetes duration were 56.3 ± 10.6 years and 9.6 ± 7.3 years, respectively. A total of 90 patients had QTc interval prolongation (21.9%). The participants with a prolonged QTc interval were older (59.4 ± 10.1 years vs 55.5 ± 10.6 years, P = .002), were more likely to be a woman (72.2% vs 51.7%, P = .001), had a higher prevalence of hypertension (46.7% vs 33.4%, P = .022), had a higher hemoglobin A1c level (8.8% ± 2.2% vs 8.2% ± 1.8%, P = .045), and had decreased values for the variables measuring HRV, except for the low frequency (LF)/high frequency (HF) ratio (total power [TP], 147.7 [74.1-335.9] ms vs 328.7 [185.7-721.7] ms, P = .002). After adjusting for multiple confounders, QTc interval prolongation was associated with the lowest quartile of the HRV parameters of TP (odds ratio [OR] = 3.99; 95% confidence interval [CI]: 2.29-6.96), HF (OR = 3.20; 95% CI: 1.84-5.58), LF (OR = 3.68; 95% CI: 2.10-6.43), standard deviation of the normal-to-normal interval (OR = 3.31; 95% CI: 1.89-5.77), and root-mean-square of the successive differences (OR = 1.98; 95% CI: 1.13-3.47) in patients with T2DM. Decreased values for the variables measuring HRV, except for the LF/HF ratio, might be associated with QTc interval prolongation in patients with T2DM.

Prediction of cardiovascular events by central blood pressure using radial tonometry in type 2 diabetes mellitus patients.

BACKGROUND: High blood pressure (BP) and type 2 diabetes mellitus (T2DM) are major causes of atherosclerotic cardiovascular disease (ASCVD) and heart failure (HF). Central blood pressure (CBP) is more predictive of ASCVD than is brachial BP; however, an association of CBP with ASCVD has not been found in T2DM patients. We evaluated the impact of CBP and the association between optimal level of noninvasively measured CBP and office BP in T2DM patients based on composite outcome of ASCVD, HF, and complications of hypertension. METHODS: Patients were enrolled from June 2011 to December 2015 and were followed up through December 2019. CBP was measured using radial tonometry. The primary endpoints were composite outcome of ASCVD, HF, and hypertension-induced complications such as left ventricular hypertrophy, retinopathy, and proteinuria. RESULTS: During the 6.5-year follow-up period, 515 patients were enrolled in the study. A total of 92 patients (17.9%) developed primary endpoints. The mean age of subjects was 61.3 ± 12.1 years and 55% (n = 283) were male. Patients who developed primary endpoints were older (65.3 ± 9.5 years vs. 60.5 ± 12.4 years) and had lower high-density lipoprotein (36.6 ± 9.4 mg/dL vs. 41.8 ± 11.1 mg/dL), higher CBP (123.6 ± 20.6 mmHg vs. 118.0 ± 20.6 mmHg), and higher pulse pressure (61.3 ± 16.6 mmHg vs. 56.5 ± 15.1 mmHg) than subjects without primary endpoint development. After adjustment for various risk factors, CBP was an independent predictor for primary endpoints (hazard ratio, 1.14; 95% confidence interval, 1.02-1.27; P = 0.016). In addition, the association of CBP and primary endpoints showed a U-shaped curve with the lowest incidence at CBP 118 mmHg and systolic BP about 128 mmHg. CONCLUSIONS: We show the importance of CBP measurements in T2DM patients and present a cutoff value for ASCVD events and hypertension-induced complications.

External validation and clinical application of the predictive model for severe hypoglycemia.

Objective: An internally validated, one-year risk prediction model for severe hypoglycemia (SH) in type 2 diabetes was evaluated in a general hospital setting to externally verify and validate its performance. Research design and methods: Between December 2017 to December 2019, 2,645 adult patients with type 2 diabetes who visited the diabetes center were enrolled. The receiver operating characteristics curve and Harrell C-statistics were compared to identify the discrimination of the model. The predicted and actual incidence of SH for one year in the development and validation cohorts were compared by ranking participants by deciles of predicted risk. Results: The concordance index was 0.878 in the external validation cohort. The sensitivity and specificity of the predictive model were 0.833 and 0.847, respectively. Based on the predicted risk, we stratified the groups into four categories: low (<0.05%), intermediate (0.05% to <0.5%), high (0.5% to <2.0%), and very high-risk group (≥2.0%). The actual annual incidence of SH gradually increased with the increased risk score level for the decile group (P for trend <0.001). The actual annual SH incidence significantly increased with increase in SH risk scores, which proportionately increased with age, duration of diabetes, glycated hemoglobin, and albuminuria and decreased with body mass index, renal function (p for trends <0.001 for all) in type 2 diabetes. Conclusion: On external validation, the novel one-year SH prediction model showed excellent discrimination in participants with type 2 diabetes and can effectively screen high-risk patients for SH, even in the general hospital setting.

Severe hypoglycemia and the risk of end stage renal disease in type 2 diabetes.

We investigated the association between the incidence of severe hypoglycemia and the risk of end-stage renal disease (ESRD) in patients with type 2 diabetes. Baseline and follow-up data for 988,333 participants with type 2 diabetes were retrieved from the National Health Insurance System database. The number of severe hypoglycemia episodes experienced from 2007 to 2009 was determined. The primary outcome was the development of ESRD after the baseline evaluation. Participants were followed from the baseline until death or December 31, 2016, during this period 14,545 participants (1.5%) developed ESRD. In the crude model, compared with those who experienced no severe hypoglycemia, the hazard ratios (95% confidential intervals) for developing ESRD were 4.96 (4.57-5.39), 6.84 (5.62-8.32), and 9.51 (7.14-12.66) in participants who experienced one, two, and three or more episodes of severe hypoglycemia, respectively. Further adjustment for various confounding factors attenuated the association between severe hypoglycemia and ESRD; the significance of the association between severe hypoglycemia and ESRD was maintained. Having three or more severe hypoglycemia episodes was associated with a nearly two-fold increased risk of developing ESRD. Prior episodes of severe hypoglycemia were associated with an increased risk of ESRD among Korean adults with type 2 diabetes.

Impaired fasting glucose levels in overweight or obese subjects for screening of type 2 diabetes in Korea.

BACKGROUND/AIMS: We examined the concordance rate among fasting plasma glucose (FPG), 2-hour post-challenge glucose (2hr PG), and hemoglobin A1c (HbA1c) in the diagnosis of diabetes in a population with a high-risk for type 2 diabetes mellitus (T2DM) in Korea. METHODS: Among the participants from the Korean Diabetes Prevention Study, individuals with FPG ≥ 100 mg/dL, body mass index (BMI) ≥ 23.0 kg/m2, and no previous history of T2DM were consecutively enrolled after a 75 g glucose tolerance test. We analyzed the differences in the clinical characteristics in subjects with stage 1 (FPG, 100 to 109 mg/dL) and stage 2 (FPG, 110 to 125 mg/dL) impaired fasting glucose (IFG). RESULTS: Of 1,637 participants, 27.2% had T2DM and 59.3% had IFG and/or impaired glucose tolerance (IGT). The mean age was 55.0 ± 8.1 years and the mean BMI was 26.3 ± 2.7 kg/m2. Based on FPG criteria, 515 (31.4%) and 352 (21.5%) subjects were classified as having stage 1 and stage 2 IFG, respectively. The 19.0% of stage 1 and 43.5% of stage 2 subjects showed 2hr PG levels in the diabetic range. Even for those in the normal FPG range, 63 (9.5%) participants showed a 2hr PG level of ≥ 200 mg/dL. Of 446 subjects with newly-diagnosed diabetes, 340 (76.2%) showed FPG levels < 126 mg/dL. CONCLUSION: The oral glucose tolerance test should be actively considered for Korean adults who are overweight or obese with the IFG range (FPG, 100 to 125 mg/ dL) to allow for early detection of diabetes and prompt intervention.

Personalized Type 2 Diabetes Management Using a Mobile Application Integrated with Electronic Medical Records: An Ongoing Randomized Controlled Trial.

Controlling type 2 diabetes (T2DM) requires a comprehensive approach including patient education, self-monitoring of blood glucose, individualized behavioral strategies, and frequent contact with healthcare professionals (HCPs). We aimed to compare the efficacy of a personalized lifestyle intervention based on a mobile phone application with regular care in participants with T2DM. This is an ongoing randomized controlled open-label parallel-group trial with a target accrual of 282 participants, of which 181 have been enrolled to date. Participants are randomly assigned to one of three groups: (1) regular care; (2) mobile diabetes management; or (3) mobile diabetes management with HCP feedback. The mobile application is enabled to integrate with both electronic medical records (EMR) and a web-based diabetes management system for HCPs. It can send customized messages based on participants' responses to lifestyle questionnaires administered at the baseline. The intervention period is 26 weeks followed by observation for 26 weeks. We evaluate the intervention's features in order to assess its clinical utility and efficacy and compare outcomes with regular care considering relevant clinical factors, such as age, baseline HbA1c, etc. We expect our study to provide new evidence in support of customized mobile application tools for the management of T2DM.

Short-Term Effects of the Internet-Based Korea Diabetes Prevention Study: 6-Month Results of a Community-Based Randomized Controlled Trial.

The aims of this study were to determine the short-term effectiveness of an internet-based lifestyle modification (LSM) program in preventing the onset of type 2 diabetes mellitus (T2DM) in prediabetes patients in community settings. A total of 415 subjects who were diagnosed with prediabetes were randomly assigned to the LSM and standard management (SM) groups. After the 6-month intervention, the LSM group had a statistically significant reduction in body weight, body mass index compared to the SM group participants. In the LSM group, blood glucose levels were significantly decreased after intervention and the clinical improvement effect was evident in the group that achieved the target weight loss of 5% or more of the initial weight for 6 months. Internet-based 6-month-intensive LSM programs conducted by public health center personnel are an effective way to provide lifestyle intervention programs and encourage maintenance of healthy behaviors in subjects with a high risk of T2DM in community settings.

Time- and frequency-domain measures of heart rate variability predict cardiovascular outcome in patients with type 2 diabetes.

AIMS: To evaluate the association between impaired heart rate variability (HRV) and cardiovascular disease (CVD) in patients with type 2 diabetes (T2DM). METHODS: A total of 655 patients with T2DM who underwent cardiovascular autonomic function testing were consecutively recruited and followed up prospectively. Time- and frequency-domain HRV were assessed for 5 min by beat-to-beat heart rate recording. We estimated the development of CVD events during a follow-up period. RESULTS: During a median follow-up of 7.8 years, 9.6% (n = 49) of patients developed CVD (10.6 per 1000 patient-years). The mean age and diabetes duration were 54.9 ±â€¯8.6 years and 9.4 ±â€¯7.3 years, respectively. Patients who had cardiovascular autonomic neuropathy (CAN) had decreased HRV compared with those with normal autonomic function. Multivariable cox hazard regression analysis revealed the lowest 10th percentile of the SD of the normal-to-normal interval (HR 2.62; 95% CI 1.30-5.31), total power (HR 2.81; 95% CI 1.37-5.79), low-frequency power (HR 2.68; 95% CI 1.28-5.59), and high-frequency power (HR 2.24; 95% CI 1.09-4.59) were significant predictors for developing CVD in patients with T2DM. CONCLUSIONS: Time- and frequency-domain measures of HRV independently predicted cardiovascular outcome in patients with T2DM.

Development and validation of a risk prediction model for severe hypoglycemia in adult patients with type 2 diabetes: a nationwide population-based cohort study.

PURPOSE: There is a scarcity of long-term prediction models for severe hypoglycemia (SH) in subjects with type 2 diabetes mellitus (T2DM). In this study, a model was developed and validated to predict the risk of SH in adult patients with T2DM. PATIENTS AND METHODS: Baseline and follow-up data from patients with T2DM who received health evaluations from January 1, 2009, to December 31, 2010 (n=1,676,885) were analyzed as development (n=1,173,820) and validation (n=503,065) cohorts using the National Health Insurance Database (DB) in Korea. New SH episodes were identified using ICD-10 codes. A Cox proportional hazards regression model and Cox model coefficients were used to derive a risk scoring system, and 14 predictive variables were selected. A risk score nomogram based on the risk prediction model was created to estimate the 1-year risk of SH. RESULTS: In the development cohort, a total of 5,325 (0.45%) patients experienced SH episodes during the follow-up period. After multivariable adjustment, older age, female sex, current smoker, drinking, low body mass index, lack of exercise, previous SH events, insulin or multiple oral hypoglycemic agent use, presence of hypertension or chronic kidney disease, longer duration of diabetes, low or high glucose level, and high Charlson Comorbidity Index score were found to be significant risk factors for the development of SH and were incorporated into the risk model. The concordance indices were 0.871 (95% confidence interval, 0.863-0.881) in development cohort and 0.866 (95% CI, 0.856-0.879) in the validation cohort. The calibration plot showed a nearly 45° line, which indicates that this model predicts well an absolute SH event. CONCLUSION: This 14-variable prediction model for SH events may be a useful tool to identify high-risk patients and guide prevention of SH in adult patients with T2DM.

Severe hypoglycemia is a risk factor for atrial fibrillation in type 2 diabetes mellitus: Nationwide population-based cohort study.

AIMS: This study investigated the association between severe hypoglycemia (SH) and new onset atrial fibrillation (AF) and all-cause mortality in adult patients with type 2 diabetes mellitus (T2DM). METHODS: Retrospective data on patients with T2DM aged between 30 and 75years who received healthcare checkups from January 1, 2005 to December 31, 2008 were analyzed using the National Health Insurance Database in Korea. The primary outcome was newly diagnosed non-valvular AF occurring after SH episode using ICD-10 codes. RESULTS: Among 1,509,280 subjects, 10,864 (0.72%) patients had experienced SH events in the three years prior to health examination, and a total of 48,916 (3.24%) first-time AF episodes occurred during the follow-up period of 8.5years. The incidence of AF was significantly higher in the group with SH than the group without SH. After multivariable adjustment, previous SH was a significant risk factor for the development of AF (HR 1.10, 95% CI 1.01-1.19). All-cause mortality was also significantly increased in patients with previous SH events and prior SH with subsequent AF occurrence, compared to patients without SH events. CONCLUSIONS: Prior SH events were associated with a higher risk of new onset AF and all-cause mortality in patients with T2DM.

Depth and combined infection is important predictor of lower extremity amputations in hospitalized diabetic foot ulcer patients.

BACKGROUND/AIMS: As the prevalence of diabetes mellitus and its complications increase rapidly, diabetic foot ulcers (DFUs), which are a major diabetic complication, are expected to increase. For prevention and effective treatment, it is important to understand the clinical course of DFUs. The aim of this study was to investigate the natural course and predictors of amputation in patients with DFUs who required hospitalization. METHODS: A total of 209 patients with type 2 diabetes, aged 30 to 85 years, who visited emergency department or needed hospitalization due to DFUs were consecutively enrolled from May 2012 to January 2016, by retrospective medical record review. The main outcome was lower extremity amputation (LEA). RESULTS: Among 192 patients who completed follow-up, 113 patients (58.9%) required LEAs. Compared to patients without amputation, baseline levels of white blood cell counts and C-reactive protein were higher in patients with amputation. In addition, bone and joint involvement was more frequently observed in patients with amputation. Multivariable regression analysis revealed that combined infection (odds ratio [OR], 11.39; 95% confidence interval [CI], 2.55 to 50.93; p = 0.001) and bone or joint involvement (OR, 3.74; 95% CI, 1.10 to 12.70; p = 0.035) were significantly associated with an increased risk of LEA. CONCLUSION: The depth of the wound and combined infection of DFU, rather than the extent of the wound, were significant prognostic factors of LEAs in patients with type 2 diabetes.

Increased risk of thyroid diseases in patients with systemic lupus erythematosus: A nationwide population-based Study in Korea.

We investigated the association between autoimmune thyroid disease and systemic lupus erythematosus (SLE) using nationwide insurance claims data for the entire Korean population. Claims data for the period 2009-2013 were retrieved from the National Health Insurance System database. SLE and thyroid disease were identified using the International Classification of Diseases codes and medication information. Logistic regression analyses were used to evaluate the association between SLE and thyroid disease. The study used records from 17,495 patients with SLE and 52,485 age- and sex-matched control subjects. A greater prevalence of Graves' disease (0.94% vs. 0.46%, P < 0.001), Hashimoto's thyroiditis (2.68% vs. 0.80%, P < 0.001), and thyroid cancer (1.81% vs. 1.30%, P < 0.001) was observed in SLE patients than in control subjects. Multivariate regression analyses demonstrated that SLE was significantly associated with an increased risk of both autoimmune thyroid disease and thyroid cancer (Graves' disease: odds ratio [OR] 2.07, 95% confidence interval [CI] 1.70-2.53; Hashimoto's thyroiditis: OR 3.42, 95% CI 3.00-3.91; thyroid cancer: OR 1.40, 95% CI 1.22-1.60). Age- and sex- stratified analyses revealed that the risk of autoimmune thyroid disease in SLE patients was increased for all age groups and the female group. An association between thyroid cancer and SLE was identified only in the 20- to 59-year-old age group and in the female group. Using a large population-based study, we demonstrated that patients with SLE are at a greater risk of developing thyroid disease than matched control individuals.