OBJECTIVE: Patients with diabetes and end-stage kidney disease (ESKD) may experience “burnt-out diabetes,” defined as having an HbA1c value 6 months. We aim to assess glycemic control by continuous glucose monitoring (Dexcom G6 CGM) metrics and glycemic markers in ESKD patients on hemodialysis with burnt-out diabetes. RESEARCH DESIGN AND METHODS: In this pilot prospective study, glycemic control was assessed by continuous glucose monitoring (CGM), HbA1c measures, and glycated albumin and fructosamine measurements in patients with burnt-out diabetes (n = 20) and without a history of diabetes (n = 20). RESULTS: Patients with burnt-out diabetes had higher CGM-measured daily glucose levels, lower percent time in the range 70–180 mg/dL, higher percent time above range (>250 mg/dL), and longer duration of hyperglycemia >180 mg/dL (hours/day) compared with patients without diabetes (all P < 0.01). HbA1c and fructosamine levels were similar; however, patients with burnt-out diabetes had higher levels of glycated albumin than did patients without diabetes. CONCLUSIONS: The use of CGM demonstrated that patients with burnt-out diabetes have significant undiagnosed hyperglycemia. CGM and glycated albumin provide better assessment of glycemic control than do values of HbA1c and fructosamine in patients with ESKD.

Introduction: There is limited evidence to guide management in patients with end-stage renal disease (ESRD) on chronic hemodialysis admitted with diabetes ketoacidosis. Thus, we investigated the clinical characteristics and outcomes of patients with ESRD admitted with diabetic ketoacidosis (DKA). Methods: In this observational study, we used International Classification of Diseases Ninth/Tenth Revision codes to identify adult (aged 18–80 years) patients admitted to Emory University Hospitals between 1 January 2006 and 31 December 2016. DKA and ESRD diagnoses were confirmed by reviewing medical records and by admission laboratory results. Results: Among 307 patients with DKA meeting the inclusion and exclusion criteria, 22.1% (n: 68) had ESRD on hemodialysis and 77.9% (n: 239) had preserved renal function (estimated glomerular filtration rate >60 mL/min/1.73 m²). Compared with patients with preserved renal function, the admission blood glucose was higher (804.5±362.6 mg/dL vs 472.5±137.7 mg/dL) and the mean hemoglobin A1c was lower (9.6%±2.1 vs 12.0%±2.5) in patients with DKA and ESRD, both p<0.001. The rates of hypoglycemia <70 mg/dL (34% vs 14%, p=0.002) and <54 mg/dL (13% vs 5%, p=0.04) were higher in the ESRD group. During hospitalization, more patients with ESRD develop volume overload (28% vs 3%, p<0.001) and require mechanical ventilation (24% vs 3%, p=<0.001). There were no differences in hospital mortality (3% vs 0%, p=0.21), but length of stay (median 7.0 vs 3.0 days, p<0.001) was longer in the ESRD cohort. After adjusting for multiple covariates, patients with DKA and ESRD have higher odds of hypoglycemia (OR 3.3, 95% CI 1.51 to 7.21, p=0.003) and volume overload (OR 4.22, 95% CI 1.37 to 13.05, p=0.01) compared with patients with DKA with preserved renal function. Conclusions: Patients with DKA and ESRD on chronic hemodialysis had worse clinical outcomes including higher rates of hypoglycemia, volume overload, need for mechanical ventilation and longer length of stay, compared with patients with preserved kidney function.

OBJECTIVE: The role of U300 glargine insulin for the inpatient management of type 2 diabetes (T2D) has not been determined. We compared the safety and efficacy of glargine U300 versus glargine U100 in noncritically ill patients with T2D. RESEARCH DESIGN AND METHODS: This prospective, open-label, randomized clinical trial included 176 patients with poorly controlled T2D (admission blood glucose [BG] 228 ± 82 mg/dL and HbA1c 9.5 ± 2.2%), treated with oral agents or insulin before admission. Patients were treated with a basal-bolus regimen with glargine U300 (n = 92) or glargine U100 (n = 84) and glulisine before meals. We adjusted insulin daily to a target BG of 70–180 mg/dL. The primary end point was noninferiority in the mean difference in daily BG between groups. The major safety outcome was the occurrence of hypoglycemia. RESULTS: There were no differences between glargine U300 and U100 in mean daily BG (186 ± 40 vs. 184 ± 46 mg/dL, P = 0.62), percentage of readings within target BG of 70–180 mg/dL (50 ± 27% vs. 55 ± 29%, P = 0.3), length of stay (median [IQR] 6.0 [4.0, 8.0] vs. 4.0 [3.0, 7.0] days, P = 0.06), hospital complications (6.5% vs. 11%, P = 0.42), or insulin total daily dose (0.43 ± 0.21 vs. 0.42 ± 0.20 units/kg/day, P = 0.74). There were no differences in the proportion of patients with BG 0.99), but glargine U300 resulted in significantly lower rates of clinically significant hypoglycemia (<54 mg/dL) compared with glargine U100 (0% vs. 6.0%, P = 0.023). CONCLUSIONS: Hospital treatment with glargine U300 resulted in similar glycemic control compared with glargine U100 and may be associated with a lower incidence of clinically significant hypoglycemia.

OBJECTIVE: After intensive insulin treatment, many obese African American patients with new-onset diabetic ketoacidosis (DKA) and severe hyperglycemia are able to achieve near-normoglycemia remission. The optimal treatment to prevent hyperglycemic relapses after remission is not known. RESEARCH DESIGN AND METHODS: This prospective, 4-year, placebo-controlled study randomly assigned 48 African American subjects with DKA and severe hyperglycemia to metformin 1,000 mg daily (n = 17), sitagliptin 100 mg daily (n = 16), or placebo (n = 15) after normoglycemia remission. Hyperglycemic relapse was defined as fasting glucose >130 mg/dL (7.2 mmol/L) and HbA1c >7.0% (53 mmol/mol). Oral glucose tolerance tests were conducted at randomization and at 3 months and then every 6 months for a median of 331 days. Oral minimal model and incremental area under the curve for insulin (AUCi) were used to calculate insulin sensitivity (Si) and β-cell function, respectively. Disposition index (DI) was calculated as a product of Si and incremental AUCi. RESULTS: Relapse-free survival was higher in sitagliptin and metformin (P = 0.015) compared with placebo, and mean time to relapse was significantly prolonged in the metformin and sitagliptin groups compared with the placebo group (480 vs. 305 days, P = 0.004). The probability of relapse was significantly lower for metformin (hazard ratio 0.28 [95% CI 0.10–0.81]) and sitagliptin (0.31 [0.10–0.98]) than for placebo. Subjects who remained in remission had a higher DI (P = 0.02) and incremental AUCi (P < 0.001) than those with hyperglycemia relapse without significant changes in Si. CONCLUSIONS: This study shows that near-normoglycemia remission was similarly prolonged by treatment with sitagliptin and metformin. The prolongation of remission was due to improvement in β-cell function.

The COVID-19 pandemic is considered a mass casualty incident of the most severe nature leading to unearthed uncertainties around management, prevention, and care. As of July 2020, more than twelve million people have tested positive for COVID-19 globally and more than 500 000 people have died. Patients with diabetes are among the most severely affected during this pandemic. Healthcare systems have made emergent changes to adapt to this public health crisis, including changes in diabetes care. Adaptations in diabetes care in the hospital (ie, changes in treatment protocols according to clinical status, diabetes technology implementation) and outpatient setting (telemedicine, mail delivery, patient education, risk stratification, monitoring) have been improvised to address this challenge. We describe how to respond to the current public health crisis focused on diabetes care in the USA. We present strategies to address and evaluate transitions in diabetes care occurring in the immediate short-term (ie, response and mitigation), as well as phases to adapt and enhance diabetes care during the months and years to come while also preparing for future pandemics (ie, recovery, surveillance, and preparedness). Implementing multidimensional frameworks may help identify gaps in care, alleviate initial demands, mitigate potential harms, and improve implementation strategies and outcomes in the future.