Pop‐Busui, Rodica

OBJECTIVE In many individuals, type 2 diabetes (T2D) remains poorly controlled despite taking multiple glucose-lowering therapies. Several studies have demonstrated that endogenous hypercortisolism is prevalent among these individuals. We tested whether cortisol-directed therapy improves their glycemic control. RESEARCH DESIGN AND METHODS In this prospective, multicenter, double-blind study, 136 individuals with T2D (hemoglobin A1c [HbA1c] 7.5%–11.5% [58–102 mmol/mol] on multiple medications) and hypercortisolism (by dexamethasone suppression test) were randomized 2:1 to the glucocorticoid receptor antagonist mifepristone (300–900 mg once daily; n = 91) or placebo (n = 45) for 24 weeks, with stratification by presence/absence of an adrenal imaging abnormality. The primary end point was the change in HbA1c. Secondary end points included changes in glucose-lowering medications, weight, and waist circumference and safety. RESULTS Mean baseline HbA1c in the study cohort was 8.55% (69.9 mmol/mol). At 24 weeks, the least squares mean (LSM) difference from placebo in HbA1c was −1.32% (95% CI −1.81 to −0.83; P < 0.001). Participants receiving mifepristone experienced reductions in body weight and waist circumference (placebo-adjusted LSM differences of −5.12 kg [95% CI −8.20 to −2.03] and −5.1 cm [−8.23 to −1.99], respectively). Of participants on mifepristone, 46% discontinued therapy, compared with 18% on placebo. Adverse events with mifepristone (>10% of participants) included hypokalemia, fatigue, nausea, vomiting, headache, peripheral edema, diarrhea, and dizziness, consistent with mifepristone’s known tolerability profile. Increases in blood pressure also occurred. CONCLUSIONS In individuals with inadequately controlled T2D and hypercortisolism, cortisol-directed medical therapy with mifepristone reduced HbA1c, with a manageable tolerability profile.

OBJECTIVE Despite the use of multiple glucose-lowering medications, glycemic targets are not met in a significant fraction of people with type 2 diabetes. In this prospective, observational study we assessed the prevalence of hypercortisolism, a potential contributing factor to inadequate glucose control. RESEARCH DESIGN AND METHODS Individuals with type 2 diabetes and HbA1c 7.5%–11.5% (58–102 mmol/mol) on two or more glucose-lowering medications with or without micro-/macrovascular complications or taking multiple blood pressure–lowering medications were screened with a 1-mg dexamethasone suppression test. Common causes of false-positive DSTs were excluded. The primary end point was the prevalence of hypercortisolism, defined as post-DST cortisol >1.8 μg/dL (50 nmol/L). Characteristics associated with hypercortisolism were assessed with multiple logistic regression. The percentage and characteristics of participants with hypercortisolism and adrenal imaging abnormalities were also assessed. RESULTS Post-DST cortisol was unsuppressed in 252 of 1,057 participants (prevalence 23.8%; 95% CI 21.3, 26.5). Hypercortisolism prevalence was 33.3% among participants with cardiac disorders and 36.6% among those taking three or more blood pressure–lowering medications. Adrenal imaging abnormalities were reported in 34.7% of participants with hypercortisolism. Use of sodium–glucose cotransporter 2 inhibitors (odds ratio 1.558), maximum-dose glucagon-like peptide 1 receptor agonists (1.544), tirzepatide (1.981), or a higher number of blood pressure–lowering medications (1.390); older age (1.316); BMI <30 kg/m2 (1.639); non-Latino/Hispanic ethnicity (3.718); and use of fibrates (2.676) or analgesics (1.457) were associated with higher prevalence (all P < 0.03). CONCLUSIONS Hypercortisolism was associated with hyperglycemia in approximately one-quarter of individuals with inadequately controlled type 2 diabetes despite multiple medications.

AbstractWe performed a cross‐sectional study to determine associations between cognition and MRI‐derived brain outcomes, with obesity, diabetes duration, and metabolic risk factors in 51 Pima American Indians with longstanding type 2 diabetes (T2d) (mean [SD] age: 48.4 [11.3] years, T2d duration: 20.1 [9.1] years). Participants had similar cognition (NIH Toolbox Cognition Battery composite: 45.3 [9.8], p = 0.64, n = 51) compared to normative data. T2d duration, but not other metabolic risk factors, associated with decreased cortical thickness (Point Estimate (PE): −0.0061, 95%CI: −0.0113, −0.0009, n = 45), gray matter volume (PE: −830.39, 95%CI: −1503.14, −157.64, n = 45), and increased white matter hyperintensity volume (PE: 0.0389, 95%CI: 0.0049, 0.0729, n = 45).

Background: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data. Methods: We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low–glucose and low-glucose hypoglycemia; very high–glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation. Results: The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals. Conclusion: The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.

Objective: To evaluate glycemic outcomes in the Wireless Innovation for Seniors with Diabetes Mellitus (WISDM) randomized clinical trial (RCT) participants during an observational extension phase. Research Design and Methods: WISDM RCT was a 26-week RCT comparing continuous glucose monitoring (CGM) with blood glucose monitoring (BGM) in 203 adults aged ≥60 years with type 1 diabetes. Of the 198 participants who completed the RCT, 100 (98%) CGM group participants continued CGM (CGM-CGM cohort) and 94 (98%) BGM group participants initiated CGM (BGM-CGM cohort) for an additional 26 weeks. Results: CGM was used a median of >90% of the time at 52 weeks in both cohorts. In the CGM-CGM cohort, median time <70 mg/dL decreased from 5.0% at baseline to 2.6% at 26 weeks and remained stable with a median of 2.8% at 52 weeks ( P < 0.001 baseline to 52 weeks). Participants spent more time in range 70–180 mg/dL (TIR) (mean 56% vs. 64%; P < 0.001) and had lower hemoglobin A1c (HbA1c) (mean 7.6% [59 mmol/mol] vs. 7.4% [57 mmol/mol]; P = 0.01) from baseline to 52 weeks. In BGM-CGM, from 26 to 52 weeks median time <70 mg/dL decreased from 3.9% to 1.9% ( P < 0.001), TIR increased from 56% to 60% ( P = 0.006) and HbA1c decreased from 7.5% (58 mmol/mol) to 7.3% (57 mmol/mol) ( P = 0.025). In BGM-CGM, a severe hypoglycemic event was reported for nine participants while using BGM during the RCT and for two participants during the extension phase with CGM ( P = 0.02). Conclusions: CGM use reduced hypoglycemia without increasing hyperglycemia in older adults with type 1 diabetes. These data provide further evidence for fully integrating CGM into clinical practice. Clinicaltrials.gov (NCT03240432)