Joong-Yeol Park

Aims: To evaluate the efficacy and safety of add‐on dapagliflozin in patients with type 2 diabetes mellitus (T2D) who had inadequate glycaemic control with metformin and linagliptin. Materials and Methods: A total of 235 patients with inadequate response to metformin (≥1000 mg/day) plus linagliptin (5 mg/day) were randomized to receive either dapagliflozin/linagliptin fixed‐dose combination (FDC [AJU‐A51]) 10/5 mg/day ( n = 117) or linagliptin 5 mg plus placebo ( n = 118) for 24 weeks. After the main treatment period, patients who received linagliptin plus placebo were treated with AJU‐A51 for an additional 28 weeks. Change in glycated haemoglobin (HbA1c) from baseline to Week 24 was the primary endpoint. Results: AJU‐A51 significantly reduced HbA1c levels (from 7.93% ± 0.82% to 7.11% ± 0.61%) compared with linagliptin plus placebo (from 7.80% ± 0.71% to 7.87% ± 0.94%), with a least squares mean difference of −0.88% (95% confidence interval −1.07 to −0.68; p < 0.0001) at 24 weeks. The AJU‐A51 group had a significantly higher proportion of patients who achieved HbA1c p < 0.001). The AJU‐A51 group maintained glycaemic efficacy up to 52 weeks, whereas the control group showed a substantial reduction in HbA1c after switching to AJU‐A51 in the extension study period. Both groups had similar incidence of treatment‐emergent and serious adverse events, and no cases of symptomatic hypoglycaemia were reported. Conclusions: Dapagliflozin and linagliptin FDC (AJU‐A51) showed potent glucose‐lowering effects, with good tolerability, in patients with T2D who had poor glycaemic control on metformin and linagliptin ( ClinicalTrials.gov [NCT06329674]).

Cho YK, et al. J Lipid Atheroscler. 2022 May;11(2):178-186. https://doi.org/10.12997/jla.2022.11.2.178

The triglyceride glucose (TyG) index has been suggested as a marker for insulin resistance; however, few studies have investigated the clinical implications of markers that combine obesity markers with the TyG index. This study aimed to investigate the associations between non-alcoholic fatty liver disease (NAFLD) and TyG-related markers in healthy subjects in Korea. We enrolled 21,001 asymptomatic participants who underwent hepatic ultrasonography. The homeostasis model assessment of insulin resistance (HOMA-IR), TyG index, TyG-body mass index, and TyG-waist circumference (WC) were subsequently analyzed. NAFLD was diagnosed using hepatic ultrasonography. A multiple logistic regression analysis was performed to evaluate the associations between the quartiles of each parameter and the risk of NAFLD. The increase in the NAFLD risk was most evident when the TyG-WC quartiles were applied; the multivariate-adjusted odds ratios for NAFLD were 4.72 (3.65–6.10), 13.28 (10.23–17.24), and 41.57 (31.66–54.59) in the 2nd, 3rd, and 4th TyG-WC quartiles, respectively, when compared with the lowest quartile. The predictability of the TyG-WC for NAFLD was better than that of the HOMA-IR using the area under the curve. The TyG-WC index was superior to the HOMA-IR for identifying NAFLD in healthy Korean adults, especially in the non-obese population.

The triglyceride glucose (TyG) index, a product of triglyceride and fasting glucose, is a reliable marker for insulin resistance. We aimed to investigate the association between the TyG-related markers and coronary artery calcification (CAC) progression. We enrolled 1145 asymptomatic participants who underwent repeated CAC score measurements during routine health examinations. Homeostasis model assessment of insulin resistance (HOMA-IR), TyG index, TyG-BMI (body mass index), and TyG-WC (waist circumference) were calculated. Progression of CAC was defined as (1) incident CAC in a CAC-free population, or an (2) increase of ≥2.5 units between the baseline and final square root of the CAC scores in participants with detectable CAC. According to the quartiles of parameters, we stratified the subjects into four groups. The prevalence of progression increased with the TyG-WC quartile (15.0%, 24.1%, 31.0%, and 32.2% for each of the groups; p < 0.001). The multivariate-adjusted odds ratio (95% confidence interval) for CAC score progression was 1.66 (1.01–2.77) when the highest and lowest TyG-WC index quartiles were compared. Furthermore, the predictability of TyG-WC for CAC progression was better than the other indices in terms of the area under the curve. The TyG-WC index predicted CAC progression better than other indices and could be a potential marker of future coronary atherosclerosis.

Background: The effectiveness of personal health records (PHRs) in diabetes management has already been verified in several clinical trials; however, evidence of their effectiveness in real-world scenarios is also necessary. To provide solid real-world evidence, an analysis that is more accurate than the analyses solely based on patient-generated health data should be conducted. Objective: This study aimed to conduct a more accurate analysis of the effectiveness of using PHRs within electronic medical records (EMRs). The results of this study will provide precise real-world evidence of PHRs as a feasible diabetes management tool. Methods: We collected log data of the sugar function in the My Chart in My Hand version 2.0 (MCMH 2.0) app from Asan Medical Center (AMC), Seoul, Republic of Korea, between December 2015 and April 2018. The EMR data of MCMH 2.0 users from AMC were collected and integrated with the PHR data. We classified users according to whether they were continuous app users. We analyzed and compared their characteristics, patterns of hemoglobin A1c (HbA1c) levels, and the proportion of successful HbA1c control. The following confounders were adjusted for HbA1c pattern analysis and HbA1c regulation proportion comparison: age, sex, first HbA1c measurement, diabetes complications severity index score, sugar function data generation weeks, HbA1c measurement weeks before MCMH 2.0 start, and generated sugar function data count. Results: The total number of MCMH 2.0 users was 64,932, with 7453 users having appropriate PHRs and diabetes criteria. The number of continuous and noncontinuous users was 133 and 7320, respectively. Compared with noncontinuous users, continuous users were younger (P<.001) and had a higher male proportion (P<.001). Furthermore, continuous users had more frequent HbA1c measurements (P=.007), shorter HbA1c measurement days (P=.04), and a shorter period between the first HbA1c measurement and MCMH 2.0 start (P<.001). Diabetes severity–related factors were not statistically significantly different between the two groups. Continuous users had a higher decrease in HbA1c (P=.02) and a higher proportion of regulation of HbA1c levels to the target level (P=.01). After adjusting the confounders, continuous users had more decline in HbA1c levels than noncontinuous users (P=.047). Of the users who had a first HbA1c measurement higher than 6.5% (111 continuous users and 5716 noncontinuous users), continuous users had better regulation of HbA1c levels with regard to the target level, 6.5%, which was statistically significant (P=.04). Conclusions: By integrating and analyzing patient- and clinically generated data, we demonstrated that the continuous use of PHRs improved diabetes management outcomes. In addition, the HbA1c reduction pattern was prominent in the PHR continuous user group. Although the continued use of PHRs has proven to be effective in managing diabetes, further evaluation of its effectiveness for various diseases and a study on PHR adherence are also required.

Introduction Ezetimibe/statin combination therapy has been reported to provide additional cardioprotective effects compared to statin monotherapy. The apolipoprotein B/A1 (apoB/A1) ratio is an effective predictor of cardiovascular diseases. The aim of this study was to compare the efficacy and safety of rosuvastatin/ezetimibe combination therapy versus rosuvastatin monotherapy using the apoB/A1 ratio in patients with diabetes and hypercholesterolemia. Methods In this randomized, multicenter, open-label, parallel-group study, patients were randomly assigned to receive the combination therapy of rosuvastatin 5 mg/ezetimibe 10 mg once daily (n = 68) or monotherapy with rosuvastatin 10 mg once daily (n = 68), for 8 weeks. Results After the 8-week treatment, percentage change (least-square means ± standard error) in the apoB/A1 ratio in the rosuvastatin/ezetimibe group was significantly decreased compared to the rosuvastatin group (− 46.14 ± 1.58% vs. − 41.30 ± 1.58%, respectively; P = 0.03). In addition, the proportion of patients achieving > 50% reduction in low-density lipoprotein-cholesterol (LDL-C) and in the comprehensive lipid target (LDL-C < 70 mg/dL, non-HDL-cholesterol [non-HDL-C] < 100 mg/dL, and apoB < 80 mg/dL) was significantly different between the two groups (76.5 and 73.5% in the rosuvastatin/ezetimibe group and 47.1 and 45.6% in the rosuvastatin group, respectively; P < 0.001). The reduction in total cholesterol, non-HDL-C, LDL-C, and apoB were greater in the rosuvastatin/ezetimibe group than in the rosuvastatin group. Both treatments were well tolerated, and no between-group differences in drug-related adverse events were observed. Conclusion The apoB/A1 ratio was significantly reduced in patients receiving combination therapy with ezetimibe and rosuvastatin compared to those receiving rosuvastatin monotherapy. Both treatments were well tolerated in patients with type 2 diabetes and hypercholesterolemia. Trial Registration NCT03446261.

The aim of this study was to investigate the association of nonalcoholic fatty liver disease (NAFLD) with diabetes and the impact of waist circumference (WC) changes in subjects with prediabetes. We enrolled 6240 subjects with prediabetes who underwent health check-ups in 2007 and revisited our hospital at least once for a follow-up examination between 2008 and 2013. Subjects were stratified by WC changes into three groups. The relative risks (RRs) for diabetes according to the NAFLD status and WC change were evaluated. The prevalence of NAFLD was 45.4% (2830/6240). During follow-up, the incidence of diabetes was 8.1% (505/6240). Subjects with NAFLD had a higher incidence of diabetes and the adjusted RRs were 1.81 (95% confidence interval [CI], 1.47 to 2.21), after adjustment for potential confounding factors. The adjusted RRs were related to WC changes. The adjusted RRs for diabetes according to tertiles of WC change (first, second, and third tertile) were 1.64 (95% CI, 1.08 to 2.49), 1.73 (95% CI, 1.28 to 2.34), and 2.04 (95% CI, 1.42 to 2.93), respectively. NAFLD has significantly increased risk of incident diabetes in subjects with prediabetes. The risk for diabetes is gradually increased with tertiles of WC change.

BACKGROUND The effectiveness of personal health records (PHRs) in diabetes management has already been verified in several clinical trials; however, evidence of their effectiveness in real-world scenarios is also necessary. To provide solid real-world evidence, an analysis that is more accurate than the analyses solely based on patient-generated health data should be conducted. OBJECTIVE This study aimed to conduct a more accurate analysis of the effectiveness of using PHRs within electronic medical records (EMRs). The results of this study will provide precise real-world evidence of PHRs as a feasible diabetes management tool. METHODS We collected log data of the sugar function in the My Chart in My Hand version 2.0 (MCMH 2.0) app from Asan Medical Center (AMC), Seoul, Republic of Korea, between December 2015 and April 2018. The EMR data of MCMH 2.0 users from AMC were collected and integrated with the PHR data. We classified users according to whether they were continuous app users. We analyzed and compared their characteristics, patterns of hemoglobin A1c (HbA1c) levels, and the proportion of successful HbA1c control. The following confounders were adjusted for HbA1c pattern analysis and HbA1c regulation proportion comparison: age, sex, first HbA1c measurement, diabetes complications severity index score, sugar function data generation weeks, HbA1c measurement weeks before MCMH 2.0 start, and generated sugar function data count. RESULTS The total number of MCMH 2.0 users was 64,932, with 7453 users having appropriate PHRs and diabetes criteria. The number of continuous and noncontinuous users was 133 and 7320, respectively. Compared with noncontinuous users, continuous users were younger (P<.001) and had a higher male proportion (P<.001). Furthermore, continuous users had more frequent HbA1c measurements (P=.007), shorter HbA1c measurement days (P=.04), and a shorter period between the first HbA1c measurement and MCMH 2.0 start (P<.001). Diabetes severity–related factors were not statistically significantly different between the two groups. Continuous users had a higher decrease in HbA1c (P=.02) and a higher proportion of regulation of HbA1c levels to the target level (P=.01). After adjusting the confounders, continuous users had more decline in HbA1c levels than noncontinuous users (P=.047). Of the users who had a first HbA1c measurement higher than 6.5% (111 continuous users and 5716 noncontinuous users), continuous users had better regulation of HbA1c levels with regard to the target level, 6.5%, which was statistically significant (P=.04). CONCLUSIONS By integrating and analyzing patient- and clinically generated data, we demonstrated that the continuous use of PHRs improved diabetes management outcomes. In addition, the HbA1c reduction pattern was prominent in the PHR continuous user group. Although the continued use of PHRs has proven to be effective in managing diabetes, further evaluation of its effectiveness for various diseases and a study on PHR adherence are also required.

Kang YM, et al. Diabetes Metab J. 2019 Jan;43:e37. https://doi.org/10.4093/dmj.2018.0092