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Diabetes mellitus is a heterogeneous disease that encompasses a wide range of conditions, from mild cases to severe conditions where survival depends on insulin therapy. The Korean Diabetes Association Task Force Team for Diabetes with β-Cell Failure has established the term to classify severe refractory disease with β-cell failure. Individuals with β-cell failure are at high risk of diabetes-related complications. We propose that diabetes with β-cell failure can be diagnosed when individuals treated with multiple daily insulin injections or insulin pumps meet at least one of the following criteria: fasting C-peptide ≤ 0.6 ng/mL, non-fasting C-peptide ≤ 1.8 ng/mL, 24-hour urine C-peptide < 30 μg/day, or spot urine C-peptide/creatinine ratio ≤ 0.6 nmol/mmol. Among cases of diabetes with β-cell failure, β-cell failure with absolute insulin deficiency can be diagnosed when at least one of the following criteria is met: fasting C-peptide < 0.24 ng/mL, non-fasting C-peptide < 0.6 ng/mL, or spot urine C-peptide/creatinine ratio < 0.2 nmol/mmol. Multiple daily insulin injections with long-acting insulin analogs and rapid-acting insulin analogs or insulin pumps are required for treatment of diabetes with β-cell failure. Continuous glucose monitoring and an automated insulin delivery system, sensor-augmented pump, or smart insulin pen, along with structured education, are necessary. We call for improvements in the relevant systems to ensure that such treatments can be provided. [ABSTRACT FROM AUTHOR]

Background: The glycemia risk index (GRI) is a novel composite continuous glucose monitoring (CGM) metric that gives greater weight to hypoglycemia than to hyperglycemia and to extreme hypo/hyperglycemia over less extreme hypo/hyperglycemia. This study aimed at validating the effectiveness of GRI and at comparing it with time in range (TIR) in assessing glycemic quality in clinical practice. Methods: A total of 524 ninety-day CGM tracings of 194 insulin-treated adults with diabetes were included in the analysis. GRI was assessed according to standard metrics in ambulatory glucose profiles. Both cross-sectional and longitudinal analyses were performed to compare the GRI and TIR. Results: The GRI was strongly correlated not only with TIR (r = −0.974), but also with the coefficient of variation (r = 0.683). To identify whether the GRI differed by hypoglycemia even with a similar TIR, CGM tracings were grouped according to TIR (50% to <60%, 60% to <70%, 70% to <80%, and ≥80%). In each TIR group, the GRI increased as time below range (TBR)<70 mg/dL increased (P < 0.001 for all TIR groups). In longitudinal analysis, as TBR<70 mg/dL improved, the GRI improved significantly (P = 0.003) whereas TIR did not (P = 0.704). Both GRI and TIR improved as time above range (TAR)>180 mg/dL improved (P < 0.001 for both). The longitudinal change was easily identifiable on a GRI grid. Conclusions: The GRI is a useful tool for assessing glycemic quality in clinical practice and reflects hypoglycemia better than does TIR. [ABSTRACT FROM AUTHOR]

Background: We aimed to determine whether there are racial differences in glucose management indicator (GMI) equation for Asians and propose an adjusted GMI equation specific to Asians. Methods: This was a 24-week, prospective, observational study. A total of 106 Korean subjects with type 1 diabetes was included in the analyses. Continuous glucose monitoring (CGM: Dexcom G5) data and glycated hemoglobin (HbA1c) were obtained at the end of 3 months (n = 106) and 6 months (n = 70) of use of a CGM device. Full 3-month CGM data were collected from 176 patients. Results: Linear regression analysis between HbA1c and CGM-derived mean glucose (GMI [%] = 2.814 + 0.026 × mean glucose [mg/dL], R2 = 0.739, P < 0.001) showed significant correlation. An increase corresponding to each 25 mg/dL increase of mean glucose was higher with the Asian-Dexcom-specific GMI (0.7%) than with the published GMI (0.6%). The mean Asian-Dexcom-specific GMI was significantly lower than the published GMI (P = 0.022), especially in patients with HbA1c <7.0% (<6.0%: P = 0.003, 6.0%-6.9%: P = 0.001). Conclusions: The GMI equation specific for Asian Type 1 diabetes was different from the published GMI equation. For a given CGM-derived mean glucose, GMI calculated with the published equation could overestimate HbA1c in Asian subjects with HbA1c <7.0%. Although race partially explains the differences in GMI equation between published and Asian data, future research with larger databases is needed to develop a specific formula for Asian populations. [ABSTRACT FROM AUTHOR]

Aims/Introduction: We aimed to determine whether mean and visit‐to‐visit glycated hemoglobin (HbA1c) variability independently increase the incidence of non‐alcoholic fatty liver disease (NAFLD) across the diabetic continuum from normal glucose tolerance (NGT) to established diabetes. Materials and Methods: In a longitudinal cohort study, 21,123 participants underwent five or more annual health screening checkups. Participants were categorized into diabetes (n = 1,635), prediabetes (n = 6,650) and NGT (n = 12,838) groups. Mean, standard deviation (SD) and coefficient of variation data on HbA1c were obtained from three consecutive measurements. The associations between those data and incident NAFLD were analyzed using Cox regressions. Results: Over a median follow‐up period of 57 months, 3,860 (18.3%) participants developed NAFLD. The risk of NAFLD increased continuously, with the mean HbA1c beginning at 4.9%, even in the NGT group. We found a significant association between increasing HbA1c variability and incident NAFLD (coefficient of variation, adjusted hazard ratio 1.14, 95% confidence interval 1.01–1.29; standard deviation, adjusted hazard ratio 1.19, 95% confidence interval 1.05–1.36) in the diabetes group, but not in the NGT or prediabetes group. Consistent findings were observed when NAFLD patients with a low possibility of fibrosis were excluded. The association between the coefficient of variation of HbA1c and incident NAFLD in the diabetes group was significant only in those with an increasing trend of post‐baseline HbA1c (adjusted hazard ratio 1.24, 95% confidence interval 1.01–1.52). Conclusions: Increased mean HbA1c levels elevated the risk of incident NAFLD, even with NGT. Increases in visit‐to‐visit variability of HbA1c independently elevated the risk of incident NAFLD, but only in the diabetes group. [ABSTRACT FROM AUTHOR]

Background: Heart failure with preserved ejection fraction is an emerging global health issue attributed to an ageing population. However, the association between low skeletal muscle mass, sarcopenic obesity, and left ventricular diastolic dysfunction remains unclear. In the current study, we aimed to investigate the relationship between low skeletal muscle mass, sarcopenic obesity, and diastolic dysfunction in a large cohort of Korean adults. Methods: We conducted a cross‐sectional study of 31 258 subjects who underwent health examinations at Samsung Medical Centre's Health Promotion Centre in Seoul, Republic of Korea. Relative skeletal muscle mass was calculated using the skeletal muscle mass index [SMI (%) = appendicular skeletal muscle mass (kg)/body weight (kg) × 100], which was estimated by bioelectrical impedance analysis. Cardiac structure and function were evaluated by echocardiography. Results: Amongst the 31 258 subjects, 3058 (9.78%) were determined to have diastolic dysfunction. The odds ratio (OR) of diastolic dysfunction was 1.56 [95% confidence interval (CI): 1.31‐1.85; p for trend <0.001] for the lowest SMI tertile relative to the highest SMI tertile following multivariable adjustment. Furthermore, the risk of diastolic dysfunction was much higher in the sarcopenic obesity (OR: 1.70, 95% CI: 1.44‐1.99), followed by in the obesity‐only (OR: 1.40, 95% CI: 1.21‐1.62), and sarcopenia‐only (OR: 1.32, 95% CI: 1.08‐1.61) when compared with the nonobese, nonsarcopenic group. These results remained consistent amongst the elderly (age ≥ 65 years). Conclusions: Our findings demonstrate that lower skeletal muscle mass and sarcopenic obesity are strongly associated with diastolic dysfunction in middle‐aged and older adults. [ABSTRACT FROM AUTHOR]

Aims: Hemoglobin glycation index (HGI), which quantifies interindividual variations in glycated hemoglobin (HbA1c), is known to be associated with diabetic complications and metabolic diseases. However, information on the association between HGI and nonalcoholic fatty liver disease (NAFLD) in healthy population, especially in Asian population is limited. Methods: A total of 14,465 subjects without diabetes who underwent liver ultrasonography during routine health examination were enrolled and stratified in quartiles according to HGI levels. Results: The prevalence of NAFLD significantly increased with HGI quartiles (24.8%, 29.7%, 32.6% and 40.6% in the 1st, 2nd, 3rd, and 4th HGI quartiles, respectively; p-value<0.001). As compared with the lowest HGI quartile group, the highest HGI quartile group had worse metabolic parameters including body weight, waist circumference, body mass index and lipid profiles. In the multiple logistic regression analysis adjusted for multiple factors, the odds ratio of having NAFLD was 1.564 (95% CI: 1.350-1.813, p <0.001) in the highest HGI quartile group. Conclusions: Elevated HGI levels are independently associated with prevalence of NAFLD in a healthy Asian population. Disclosure: J. Yoo: None. W. Lee: None. J. Park: None. J. Lee: None. Y. Kang: None. C. Jung: None. Y. Cho: None. C. Park: None. [ABSTRACT FROM AUTHOR]

We evaluated the effectiveness of the predictive low-glucose suspend (PLGS) algorithm in the DIA:CONN G8. Forty people with type 1 diabetes mellitus (T1DM) who used a DIA:CONN G8 for at least 2 months with prior experience using pumps without and with PLGS were retrospectively analyzed. The objective was to assess the changes in time spent in hypoglycemia (percent of time below range [%TBR]) before and after using PLGS. The mean age, sensor glucose levels, glucose threshold for suspension, and suspension time were 31.1±22.8 years, 159.7±23.2 mg/dL, 81.1±9.1 mg/dL, and 111.9±79.8 min/day, respectively. Overnight %TBR <70 mg/dL was significantly reduced after using the algorithm (differences=0.3%, from 1.4%±1.5% to 1.1%±1.2%, P=0.045). The glycemia risk index (GRI) improved significantly by 4.2 (from 38.8±20.9 to 34.6±19.0, P=0.002). Using the PLGS did not result in a change in the hyperglycemia metric (all P>0.05). Our findings support the PLGS in DIA:CONN G8 as an effective algorithm to improve night-time hypoglycemia and GRI in people with T1DM.

Background: This study demonstrates the difference between glucose management indicator (GMI) and glycated hemoglobin (HbA 1c ) according to sensor mean glucose and HbA 1c status using 2 continuous glucose monitoring (CGM) sensors in people with type 1 diabetes., Methods: A total of 275 subjects (117 Dexcom G6 [G6] and 158 FreeStyle Libre 1 [FL]) with type 1 diabetes was included. The G6 and FL sensors were used, respectively, over 90 days to analyze 682 and 515 glycemic profiles that coincide with HbA 1c ., Results: The mean HbA 1c was 6.6% in Dexcom G6 and 7.2% in FL profiles. In G6 profiles, GMI was significantly higher than HbA 1c irrespective of mean glucose (all P < .001, mean difference: 0.58% ± 0.49%). The GMI was significantly higher than the given HbA 1c when HbA 1c was below 8.0% (all P < .001). The discordance was the highest at 0.9% for lower HbA 1c values (5.0%-5.9%). The proportion of discordance >0.5% improved from 60.1% to 30.9% when using the revised GMI equation in G6 profiles. In FL profile, the overall mean difference between GMI and HbA 1c was 0 ( P = .966). The GMI was significantly lower by 0.9% than HbA 1c of 9.0% to 9.9% and higher by 0.5% in HbA 1c of 5.0% to 5.9% (all P < .001)., Conclusions: The GMI is overestimated in G6 users, particularly those with well-controlled diabetes, but the GMI and HbA 1c discordance improved with a revised equation from the observed data. The FL profile showed greater discordance for lower HbA 1c levels or higher HbA 1c levels., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.