Flexible insulin therapy improves metabolic control and decreases the risk of hypoglycemia in type 1 diabetic patients.

INTRODUCTION: flexible insulin therapy (FIT) is considered as a crucial turning point in the management of type 1 diabetes. The purpose of this study was to evaluate the impact of this optimum therapeutic approach on improving metabolic control and decreasing hypoglycemic events in patients with type 1 diabetes. METHODS: thirty-seven type 1 diabetic patients were included in a five days training programme of FIT. They had an HbA1c between 7.5 and 10%. Those patients were enrolled in a flexible insulin program and we evaluate clinical and metabolic parameters (glycated haemoglobin (HbA1c), hypoglycemic events, body mass index (BMI) and the rate of blood glucose measurements) before the course of FIT and 3, 6 and 9 months after the course. RESULTS: over a 9 months period of the study, the frequency of mild hypoglycemia decreased from 11.7 to 1.7 episodes/3 months (p = 0.005). The baseline HbA1c value improved by 1% at 3 months with an increase of 0.2% at 6 months, which remained unchanged at 9 months (p = <0.0001). Patients who were poorly controlled (HbA1c ≥ 8%) improved their baseline HbA1c value from 9.2% to 8.0% (p = <0.0001). CONCLUSION: the present study confirms that a structured training programme for FIT improves glycemic control and decreases hypoglycemic events in patients with type 1 diabetes and it can be adopted in countries with weak or intermediate income (e.g. Morocco), which allows those patients to take advantages of this therapeutic approach.

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.

Principles of self-adjustment of insulin dose in people with diabetes type 2 and flexible insulin therapy.

AIMS: Structured treatment and education programmes for people with type 2 diabetes mellitus (T2DM) and flexible insulin therapy provide rules for self-adjustment of insulin dose, that are extensively trained. The aim of this cohort study was to register current principles and the frequency of self-adjustment of insulin dose and their association with metabolic control in people with T2DM. METHODS: Details of insulin dose adjustment were assessed by a structured interview in 149 people with T2DM on flexible insulin therapy (mean HbA1c 7.1%/53.8mmol/mol, age 65y, diabetes duration 19.0y, BMI 33.8kg/m(2)) in a tertiary care centre. The frequency of insulin dose adjustments was obtained from the last 28days of the patients' diaries. RESULTS: Insulin dose adjustment by adjustment rules was used by 33 people (22.1%) and by personal experience/feeling in 111 participants (74.5%). People adjusting by rules were younger (60.9±9.8 vs. 65.7±9.2, p=0.011) and did more insulin dose adjustments per 28days (50.0±31.0 vs. 33.4±23.5, p=0.016). HbA1c and incidence of hypoglycaemia were comparable. There were no differences in satisfaction of treatment, quality of life as well as current well-being between the groups. CONCLUSIONS: Only a fifth of the participants used the rule trained within the education programme to adjust their insulin dose. The majority adjusted their insulin dose by personal experience/feeling. However, people in both groups were able to adjust their insulin dose. Although people using adjustment rules adjust their insulin dose more frequently, HbA1c and the incidence of hypoglycaemia was similar compared to those using personal experience/feeling.

Impact of flexible insulin therapy on blood glucose variability, oxidative stress and inflammation in type 1 diabetic patients: the VARIAFIT study.

AIMS: HbA1c only partially predicts vascular risk in patients with type 1 diabetes (T1D), and a role for blood glucose variability (BGV) is a matter of debate. For this reason, this study investigated the impact of an educational programme of flexible insulin therapy (FIT) on BGV and oxidative stress. METHODS: Tests were conducted on 30 adult T1D patients in a prospective, single-centre trial at baseline (M0), and at 3 and 6 months (M3 and M6, respectively) of the FIT programme to determine BGV, as reflected by mean amplitude of glycaemic excursions (MAGE), low blood glucose index (LBGI), lability index (LI), average daily risk range (ADRR), glycaemic lability (scored by two diabetologists), urinary leukotriene E4 (LTE4), 11-dehydro-thromboxane B2 (TXB2) and 8-iso-prostaglandin F2α (PGF2). RESULTS: HbA1c (7.7 ± 0.9%), ADRR, MAGE, LBGI and LI did not change from M0 to M3 and M6, although ADRR and LBGI significantly improved at M3 and M6 in patients with the highest baseline indices (≥ 40 and ≥ 5, respectively). TXB2 declined at M6 (832 ± 625 vs. 633 ± 972 pg/mg; P=0.048), whereas LTE4 and PGF2 remained stable. ADRR showed the strongest correlation with glycaemic lability scores at all visits (r≥0.84, P<0.0001). CONCLUSION: A FIT educational programme improved BGV only in patients with the highest baseline variability, and led to no changes in HbA1c, while ADRR closely correlated with glycaemic lability score. Our data do not support a relationship between BGV and oxidative stress in T1D patients, although the impact of variability on TXB2 deserves further investigation (ClinicalTrials.gov NCT00973492).