Over 450 million people worldwide are living with diabetes, leading to an associated estimated global healthcare expenditure of $850 billion in the year 2017.1 By the year 2030, global costs of diabetes are estimated exceed 2015 levels by 88%, accounting for 2.2% of the global GDP (compared with 1.8% in 2015).2 In addition to the socioeconomic burden on national healthcare systems and global economies, diabetes disproportionally affects older adults. It is estimated that one in five individuals over the age of 65 years has diabetes in the United States (U.S.).3 Not only are older individuals more likely to have diabetes, but those with diabetes are three times more likely to require hospital admission compared to younger individuals.4 Glycemic control in the hospital setting is important for reducing complications and mortality.5–7 However, maintaining strict or tight glycemic control in the inpatient setting has been associated with poor outcomes related to iatrogenic hypoglycemia.8 The balance between achieving glycemic control and avoiding hypoglycemia is especially challenging in older individuals with longer diabetes duration, diabetes-related complications, multiple medical comorbidities and functional decline. It is important to consider the following factors when determining glycemic targets and diabetes treatment regimens in elderly patients, including: functional status, life expectancy, level of frailty, and cognitive impairment. Research focused on inpatient diabetes management in older patients has been limited.9 We review the prevalence, clinical presentation, the assessment of older adults with diabetes in the hospital. We also explore the role of multidisciplinary team approach, diabetes education, glycemic control strategies, and recommendations for discharge regimens in this population.

Introduction: Multiple daily injection insulin therapy frequently fails to meet hospital glycemic goals and is prone to hypoglycemia. Automated insulin delivery (AID) with remote glucose monitoring offers a solution to these shortcomings. Research Design and Methods: In a single-arm multicenter pilot trial, we tested the feasibility, safety, and effectiveness of the Omnipod 5 AID System with real-time continuous glucose monitoring (CGM) for up to 10 days in hospitalized patients with insulin-requiring diabetes on nonintensive care unit medical–surgical units. Primary endpoints included the proportion of time in automated mode and percent time-in-range (TIR 70–180 mg/dL) among participants with >48 h of CGM data. Safety endpoints included incidence of severe hypoglycemia and diabetes-related ketoacidosis (DKA). Additional glycemic endpoints, CGM accuracy, and patient satisfaction were also explored. Results: Twenty-two participants were enrolled; 18 used the system for a total of 96 days (mean 5.3 ± 3.1 days per patient), and 16 had sufficient CGM data required for analysis. Median percent time in automated mode was 95% (interquartile range 92%–98%) for the 18 system users, and the 16 participants with >48 h of CGM data achieved an overall TIR of 68% ± 16%, with 0.17% ± 0.3% time <70 mg/dL and 0.06% ± 0.2% time <54 mg/dL. Sensor mean glucose was 167 ± 21 mg/dL. There were no DKA or severe hypoglycemic events. All participants reported satisfaction with the system at study end. Conclusions: The use of AID with a disposable tubeless patch-pump along with remote real-time CGM is feasible in the hospital setting. These results warrant further investigation in randomized trials.

OBJECTIVE: The efficacy and safety of continuous glucose monitoring (CGM) in adjusting inpatient insulin therapy have not been evaluated. RESEARCH DESIGN AND METHODS: This randomized trial included 185 general medicine and surgery patients with type 1 and type 2 diabetes treated with a basal-bolus insulin regimen. All subjects underwent point-of-care (POC) capillary glucose testing before meals and bedtime. Patients in the standard of care (POC group) wore a blinded Dexcom G6 CGM with insulin dose adjusted based on POC results, while in the CGM group, insulin adjustment was based on daily CGM profile. Primary end points were differences in time in range (TIR; 70–180 mg/dL) and hypoglycemia (<70 mg/dL and <54 mg/dL). RESULTS: There were no significant differences in TIR (54.51% ± 27.72 vs. 48.64% ± 24.25; P = 0.14), mean daily glucose (183.2 ± 40 vs. 186.8 ± 39 mg/dL; P = 0.36), or percent of patients with CGM values <70 mg/dL (36% vs. 39%; P = 0.68) or <54 mg/dL (14 vs. 24%; P = 0.12) between the CGM-guided and POC groups. Among patients with one or more hypoglycemic events, compared with POC, the CGM group experienced a significant reduction in hypoglycemia reoccurrence (1.80 ± 1.54 vs. 2.94 ± 2.76 events/patient; P = 0.03), lower percentage of time below range <70 mg/dL (1.89% ± 3.27 vs. 5.47% ± 8.49; P = 0.02), and lower incidence rate ratio <70 mg/dL (0.53 [95% CI 0.31–0.92]) and <54 mg/dL (0.37 [95% CI 0.17–0.83]). CONCLUSIONS: The inpatient use of real-time Dexcom G6 CGM is safe and effective in guiding insulin therapy, resulting in a similar improvement in glycemic control and a significant reduction of recurrent hypoglycemic events compared with POC-guided insulin adjustment.

OBJECTIVE: Administration of supplemental sliding scale insulin for correction of hyperglycemia in non–intensive care unit (ICU) patients with type 2 diabetes is frequently used with basal-bolus insulin regimens. In this noninferiority randomized controlled trial we tested whether glycemic control is similar with and without aggressive sliding scale insulin treatment before meals and bedtime in patients treated with basal-bolus insulin regimens. RESEARCH DESIGN AND METHODS: Patients with type 2 diabetes with admission blood glucose (BG) 140–400 mg/dL treated with basal-bolus insulin were randomized to intensive (correction for BG >140 mg/dL, n = 108) or to nonintensive (correction for BG >260 mg/dL, n = 107) administration of rapid-acting sliding scale insulin before meals and bedtime. The groups received the same amount of sliding scale insulin for BG >260 mg/dL. Primary outcome was difference in mean daily BG levels between the groups during hospitalization. RESULTS: Mean daily BG in the nonintensive group was noninferior to BG in the intensive group with equivalence margin of 18 mg/dL (intensive 172 ± 38 mg/dL vs. nonintensive 173 ± 43 mg/dL, P = 0.001 for noninferiority). There were no differences in the proportion of target BG readings of 70–180 mg/dL, <70 or <54 mg/dL (hypoglycemia), or >350 mg/dL (severe hyperglycemia) or total, basal, or prandial insulin doses. Significantly fewer subjects received sliding scale insulin in the nonintensive (n = 36 [34%]) compared with the intensive (n = 98 [91%] [P < 0.0001]) group with no differences in sliding scale insulin doses between the groups among those who received sliding scale insulin (intensive 7 ± 4 units/day vs. nonintensive 8 ± 4 units/day, P = 0.34). CONCLUSIONS: Among non-ICU patients with type 2 diabetes on optimal basal-bolus insulin regimen with moderate hyperglycemia (BG <260 mg/dL), a less intensive sliding scale insulin treatment did not significantly affect glycemic control.

Hyperglycaemia in people with and without diabetes admitted to the hospital is associated with a substantial increase in morbidity, mortality, and health-care costs. Professional societies have recommended insulin therapy as the cornerstone of inpatient pharmacological management. Intravenous insulin therapy is the treatment of choice in the critical care setting. In non-intensive care settings, several insulin protocols have been proposed to manage patients with hyperglycaemia; however, meta-analyses comparing different treatment regimens have not clearly endorsed the benefits of any particular strategy. Clinical guidelines recommend stopping oral antidiabetes drugs during hospitalisation; however, in some countries continuation of oral antidiabetes drugs is commonplace in some patients with type 2 diabetes admitted to hospital, and findings from clinical trials have suggested that non-insulin drugs, alone or in combination with basal insulin, can be used to achieve appropriate glycaemic control in selected populations. Advances in diabetes technology are revolutionising day-to-day diabetes care and work is ongoing to implement these technologies (ie, continuous glucose monitoring, automated insulin delivery) for inpatient care. Additionally, transformations in care have occurred during the COVID-19 pandemic, including the use of remote inpatient diabetes management—research is needed to assess the effects of such adaptations.

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 m 2). 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: Obesity is associated with increased risk of diabetes, hypertension and cardiovascular mortality. Several studies have reported increased length of hospital stay and complications; however, there are also reports of obesity having a protective effect on health, a phenomenon coined the 'obesity paradox'. We aimed to investigate the impact of overweight and obesity on complications and mortality in hospitalized patients with hyperglycemia and diabetes. RESEARCH DESIGN AND METHODS: This retrospective analysis was conducted on 29 623 patients admitted to two academic hospitals in Atlanta, Georgia, between January 2012 and December 2013. Patients were subdivided by body mass index into underweight (body mass index <18.5 kg/m(2)), normal weight (18.5-24.9 kg/m(2)), overweight (25-29.9 kg/m(2)) and obese (>30 kg/m(2)). Hyperglycemia was defined as a blood glucose >10 mmol/L during hospitalization. Hospital complications included a composite of pneumonia, acute myocardial infarction, respiratory failure, acute kidney injury, bacteremia and death. RESULTS: A total of 4.2% were underweight, 29.6% had normal weight, 30.2% were overweight, and 36% were obese. 27.2% of patients had diabetes and 72.8% did not have diabetes (of which 75% had hyperglycemia and 25% had normoglycemia during hospitalization). A J-shaped curve with higher rates of complications was observed in underweight patients in all glycemic groups; however, there was no significant difference in the rate of complications among normal weight, overweight, or obese patients, with and without diabetes or hyperglycemia. CONCLUSIONS: Underweight is an independent predictor for hospital complications. In contrast, increasing body mass index was not associated with higher morbidity or mortality, regardless of glycemic status. There was no evidence of an obesity paradox among inpatients with diabetes and hyperglycemia.

Objectives: Safe and easily implemented treatment regimens are needed for the management of patients with type 2 diabetes mellitus (T2DM) in long-term care (LTC) and skilled nursing facilities. Design: This 6-month open-label randomized controlled trial compared the efficacy and safety of a DPP4 inhibitor (linagliptin) and basal insulin (glargine) in LTC residents with T2DM. Settings: Three LTC institutions affiliated with a community safety-net hospital, US Department of Veterans Affairs and Emory Healthcare System in Atlanta, Georgia. Participants: A total of 140 residents with T2DM treated with oral antidiabetic agents or low-dose insulin (≤0.1 U/kg/d), with fasting or premeal blood glucose (BG) > 180 mg/dL and/or HbA1c >7.5%. Intervention: Baseline antidiabetic therapy, except metformin, was discontinued on trial entry. Residents were treated with linagliptin 5 mg/d (n = 67) or glargine at a starting dose of 0.1 U/kg/d (n = 73). Both groups received supplemental rapid-acting insulin before meals for BG > 200 mg/dL. Measurements: Primary outcome was mean difference in daily BG between groups. Main secondary endpoints included differences in frequency of hypoglycemia, glycosylated hemoglobin (HbA1c), complications, emergency department visits, and hospital transfers. Results: Treatment with linagliptin resulted in no significant differences in mean daily BG (146 ± 34 mg/dL vs. 157 ± 36 mg/dL, P =.07) compared to glargine. Linagliptin treatment resulted in fewer mild hypoglycemic events <70 mg/dL (3% vs. 37%, P <.001), but there were no differences in BG < 54 mg/dL (P =.06) or <40 mg/dL (P =.05) compared to glargine. There were no significant between-group differences in HbA1c, length of stay, complications, emergency department visits, or hospitalizations. Conclusion: Treatment with linagliptin resulted in noninferior glycemic control and in significantly lower risk of hypoglycemia compared to insulin glargine in long-term care and skilled nursing facility residents with type 2 diabetes.

We present the case of multiple sclerosing pneumocytomas (SPs) associated with ACTH-secreting carcinoid tumorlets responsible for an ectopic Cushing syndrome (ECS). SP is a rare benign tumor originating from pulmonary epithelial cells. An 18-year-old male presented with shortness of breath and right-sided chest pain after exercise. Chest radiograph indicated right pneumothorax and bilateral lung nodules. CT imaging showed innumerable bilateral hypodense pulmonary nodules and a wedge resection gave the definitive diagnosis of SP with associated carcinoid tumorlets. Two years later, he presented with severe back pain in context of thoracic vertebral compression fracture. He had central fat accumulation, violaceous striae, proximal muscle weakness, hypertension, and diabetes. MRI of the pituitary gland showed a 7-mm adenoma. Inferior petrosal sinus sampling with no central-to-periphery gradient suggested an ectopic origin of ACTH, which was confirmed by ACTH expression in a subset of tumorlet cells in the lung lesions. The patient was started on ketoconazole and subsequently underwent a bilateral adrenalectomy. During follow-up, CT scans showed no growth of the lesions, except for the most recent CT scan, in which an increase in the size of the largest nodule was described. Ten years after the diagnosis, the patient remains asymptomatic of his pulmonary lesions. This article provides a case of ECS in the setting of multiple SP with associated carcinoid tumorlets.

The past two decades have witnessed many advances in the prevention, treatment, and control of diabetes mellitus (DM) and its complications. Increased screening has led to a greater recognition of type 2 diabetes mellitus (type 2 DM) and prediabetes; however, Hispanics/Latinos, the largest minority group in the US, have not fully benefited from these advances. The Hispanic/Latino population is highly diverse in ancestries, birth places, cultures, languages, and socioeconomic backgrounds, and it populates most of the Western Hemisphere. In the US, the prevalence of DM varies among Hispanic/Latino heritage groups, being higher among Mexicans, Puerto Ricans, and Dominicans, and lower among South Americans. The risk and prevalence of diabetes among Hispanics/Latinos are significantly higher than in non-Hispanic Whites, and nearly 40% of Hispanics/Latinos with diabetes have not been formally diagnosed. Despite these striking facts, the representation of Hispanics/Latinos in pharmacological and non-pharmacological clinical trials has been suboptimal, while the prevalence of diabetes in these populations continues to rise. This review will focus on the epidemiology, etiology and prevention of type 2 DM in populations of Latin American origin. We will set the stage by defining the terms Hispanic, Latino, and Latin American, explaining the challenges identifying Hispanics/Latinos in the scientific literature and databases, describing the epidemiology of diabetes-including type 2 DM and gestational diabetes mellitus (GDM)-and cardiovascular risk factors in Hispanics/Latinos in the US and Latin America, and discussing trends, and commonalities and differences across studies and populations, including methodology to ascertain diabetes. We will discuss studies on mechanisms of disease, and research on prevention of type 2 DM in Hispanics/Latinos, including women with GDM, youth and adults; and finalize with a discussion on lessons learned and opportunities to enhance research, and, consequently, clinical care oriented toward preventing type 2 DM in Hispanics/Latinos in the US and Latin America.