Carbohydrate counting knowledge and ambulatory glucose profile in persons living with type 1 diabetes.

CONTEXT: The amount of consumed carbohydrates is the strongest factor influencing glucose levels during the four hours following a meal. Our aim was to evaluate the association between carbohydrate counting knowledge and continuous glucose monitoring (CGM) parameters in patients with type 1 diabetes (T1D) using different insulin regimens. METHOD: In this multicenter prospective study, the GluciQuizz questionnaire was used to evaluate carbohydrate knowledge. CGM data for the 14 days preceding completion of the questionnaire were analyzed. The primary endpoint was evaluation of the correlation between the GluciQuizz total score and time in range (TIR) in the study population. RESULTS: The mean age of the 170 participants was 40.7 ± 14.8 years and duration of T1D 18.8 ± 12.1 years. The mean GluciQuizz total score for all participants was 66 ± 13 %. Mean TIR was 58.6 ± 18.7 %. GluciQuizz total score positively correlated with TIR (r = 0.3001; p < 0.0001). This correlation was observed in CSII users (r = 0.2526; p < 0.05) but not in MDI (r = 0.2510; p = 0.1134) and HCL users (r = -0.1065; p = 0.4914). TIR was also negatively correlated with the mean carb count error in all study participants (r = -0.2317; p < 0.01). CONCLUSION: In conclusion, as the Gluciquizz score was associated with metabolic control, this easy-to-use self-administered questionnaire could be used widely on a routine basis to assess the carbohydrate knowledge of T1D patients and to offer them targeted education tailored to their needs.

Congenital adrenal hyperplasia: New biomarkers and adult treatments.

Congenital adrenal hyperplasia (CAH) is a genetic disease caused by an enzyme deficiency interrupting adrenal steroidogenesis. It most frequently involves 21-hydroxylase, which induces adrenal insufficiency with hyperandrogenism. Restoring hormonal balance is difficult with glucocorticoids, which are the gold-standard treatment. Strict normalization of conventional biomarkers (17-hydroxyprogesterone and delta-4 androstenedione) is often obtained at the cost of iatrogenic hypercortisolism. Optimizing the management of these patients first involves using more specific biomarkers of adrenal steroidogenesis in difficult situations, and secondly using therapeutics targeting the induced hypothalamic-pituitary-adrenal axis disorder. 11-oxygenated androgens are candidates for biochemical monitoring of Congenital adrenal hyperplasia (CAH), in particular 11-ketotestosterone. Numerous new therapeutic agents are currently being explored, the prime goal being to reduce glucocorticoid exposure, as no strategy can fully replace it at present. They can be divided into 3 categories. The first includes "more physiological" hydrocortisone administration (modified-release hydrocortisone and continuous subcutaneous infusion of hydrocortisone hemisuccinate); the second includes corticotropin releasing hormone (CRH) and adrenocorticotropic hormone (ACTH) receptor antagonists and anti-ACTH antibodies; and the third includes steroidogenesis inhibitors. Finally, experiments on gene and cell therapies suggest the possibility of lasting remission or even cure in the future.

Safety and Efficacy of Sustained Automated Insulin Delivery Compared With Sensor and Pump Therapy in Adults With Type 1 Diabetes at High Risk for Hypoglycemia: A Randomized Controlled Trial.

OBJECTIVE: Assess the safety and efficacy of automated insulin delivery (AID) in adults with type 1 diabetes (T1D) at high risk for hypoglycemia. RESEARCH DESIGN AND METHODS: Participants were 72 adults with T1D who used an insulin pump with Clarke Hypoglycemia Perception Awareness scale score >3 and/or had severe hypoglycemia during the previous 6 months confirmed by time below range (TBR; defined as sensor glucose [SG] reading <70 mg/dL) of at least 5% during 2 weeks of blinded continuous glucose monitoring (CGM). Parallel-arm, randomized trial (2:1) of AID (Tandem t:slim ×2 with Control-IQ technology) versus CGM and pump therapy for 12 weeks. The primary outcome was TBR change from baseline. Secondary outcomes included time in target range (TIR; 70-180 mg/dL), time above range (TAR), mean SG reading, and time with glucose level <54 mg/dL. An optional 12-week extension with AID was offered to all participants. RESULTS: Compared with the sensor and pump (S&P), AID resulted in significant reduction of TBR by -3.7% (95% CI -4.8, -2.6), P < 0.001; an 8.6% increase in TIR (95% CI 5.2, 12.1), P < 0.001; and a -5.3% decrease in TAR (95% CI -87.7, -1.8), P = 0.004. Mean SG reading remained similar in the AID and S&P groups. During the 12-week extension, the effects of AID were sustained in the AID group and reproduced in the S&P group. Two severe hypoglycemic episodes occurred using AID. CONCLUSIONS: In adults with T1D at high risk for hypoglycemia, AID reduced the risk for hypoglycemia more than twofold, as quantified by TBR, while improving TIR and reducing hyperglycemia. Hence, AID is strongly recommended for this specific population.

Prospective Independent Evaluation of the Carbohydrate Counting Accuracy of Two Smartphone Applications.

INTRODUCTION: Smartphone applications (apps) have been designed that help patients to accurately count their carbohydrate intake in order to optimize prandial insulin dose matching. Our aim was to evaluate the accuracy of two carbohydrate (carb) counting apps. METHODS: Medical students, in the role of mock patients, evaluated meals using two smartphone apps: Foodvisor® (which uses automatic food photo recognition technology) and Glucicheck® (which requires the manual entry of carbohydrates with the help of a photo gallery). The macronutrient quantifications obtained with these two apps were compared to a reference quantification. RESULTS: The carbohydrate content of the entire meal was underestimated with Foodvisor® (Foodvisor® quantification minus gold standard quantification = - 7.2 ± 17.3 g; p < 0.05) but reasonably accurately estimated with Glucicheck® (Glucicheck® quantification minus gold standard quantification = 1.4 ± 13.4 g; ns). The percentage of meals with an absolute error in carbohydrate quantification above 20 g was greater for Foodvisor® compared to Glucicheck® (30% vs 14%; p < 0.01). CONCLUSION: The carb counting accuracy was slightly better when using Glucicheck® compared to Foodvisor®. However, both apps provided a lower mean absolute carb counting error than that usually made by T1D patients in everyday life, suggesting that such apps may be a useful adjunct for estimating carbohydrate content.