Sex hormone levels are not associated with progression of renal disease in male patients with T2DM.

BACKGROUND: Greater renal function decline (RFD) in type 2 diabetes (T2DM) has been suggested in men compared with women, and imbalances in estrogen/androgen levels have been associated with cardiovascular disease mortality in elderly men, but it remains unclear whether sex hormone disequilibrium is related to diabetic nephropathy (DN) in men with T2DM. OBJECTIVE: This study examined the relationship between sex steroid concentrations and renal outcomes in male T2DM patients. POPULATION AND METHODS: Total testosterone (T), total estradiol (E2), sex hormone-binding globulin (SHBG), and total and calculated free (cf) E2/T ratios were compared in 735 male T2DM patients with (n=513) and without (n=222) DN, using a cross-sectional approach. Also, in a pilot complementary prospective nested case-control cohort, total E2/total T and cfE2/cfT were evaluated according to a hard renal outcome (HRO): end-stage renal disease/doubling of baseline serum creatinine (36 HRO cases, 72 HRO controls) and rate of eGFR decline (68 rapid vs 68 slow RFD). RESULT: With the cross-sectional approach, E2 and cfE2 were higher in DN cases vs DN controls (95.5 vs 86.8pmol/L [P=0.0246] and 2.59 vs 2.36pmol/L [P=0.005], respectively). The difference in E2 persisted on multivariate analysis. In the prospective approach, E2 and T concentrations, and total E2/total T and cfE2/cfT2 ratios did not differ in HRO cases vs controls or in patients with rapid vs slow RFD. CONCLUSION: Although positively related to DN in the cross-sectional analysis, progression of renal disease in male patients with T2DM was not related to either sex hormone levels or aromatase index as reflected by E2/T ratio.

Telemedicine and type 1 diabetes: is technology per se sufficient to improve glycaemic control?

AIM: In the TELEDIAB-1 study, the Diabeo system (a smartphone coupled to a website) improved HbA1c by 0.9% vs controls in patients with chronic, poorly controlled type 1 diabetes. The system provided two main functions: automated advice on the insulin doses required; and remote monitoring by teleconsultation. The question is: how much did each function contribute to the improvement in HbA1c? METHODS: Each patient received a smartphone with an insulin dose advisor (IDA) and with (G3 group) or without (G2 group) the telemonitoring/teleconsultation function. Patients were classified as "high users" if the proportion of "informed" meals using the IDA exceeded 67% (median) and as "low users" if not. Also analyzed was the respective impact of the IDA function and teleconsultations on the final HbA1c levels. RESULTS: Among the high users, the proportion of informed meals remained stable from baseline to the end of the study 6months later (from 78.1±21.5% to 73.8±25.1%; P=0.107), but decreased in the low users (from 36.6±29.4% to 26.7±28.4%; P=0.005). As expected, HbA1c improved in high users from 8.7% [range: 8.3-9.2%] to 8.2% [range: 7.8-8.7%] in patients with (n=26) vs without (n=30) the benefit of telemonitoring/teleconsultation (-0.49±0.60% vs -0.52±0.73%, respectively; P=0.879). However, although HbA1c also improved in low users from 9.0% [8.5-10.1] to 8.5% [7.9-9.6], those receiving support via teleconsultation tended to show greater improvement than the others (-0.93±0.97 vs -0.46±1.05, respectively; P=0.084). CONCLUSION: The Diabeo system improved glycaemic control in both high and low users who avidly used the IDA function, while the greatest improvement was seen in the low users who had the motivational support of teleconsultations.

Type 1 diabetes: dealing with physical activity.

AIM: For patients with type 1 diabetes (T1D) using multiple insulin injections (MII), there are currently no guidelines for insulin dose adjustments in the event of physical activity (PA) and no simple algorithms that can be applied directly. Thus, the objective of this study was to assess the relevance of simple algorithms based on assessments of PA intensity by T1D patients themselves. METHODS: This 4-month observational study was conducted in 35 patients using the Diabeo software system. Algorithms for insulin dose adjustments aimed to reduce the insulin dose of the meal closest to PA by 30 and 50% for moderate and intense PA, respectively. A 50% reduction plus extra carbohydrates was proposed for intense PA of long duration. These algorithms were entered into the Diabeo system. RESULTS: The mean blood glucose (BG) profile in the event of PA (n = 151 triple BG values) was compared with that when no PA was performed (n = 3606). The initial mean FBG values were similar in both groups (7.58 ± 2.70 mmol/L vs. 7.80 ± 3.49 mmol/L; P = 0.36), whereas there was a slight, but significant, increase in 2-hours postprandial BG (PPBG) values related to PA, with a return to similar values before the next meal. The incidence of mild hypoglycaemia was similar, whether PA was undertaken or not, for the 2-hour PPBG and the next fasting/premeal glucose values. CONCLUSION: This appears to be a pragmatic and efficient method for T1D patients using MII to adjust insulin doses in the event of PA that only requires an assessment of PA intensity by the patients themselves to anticipate the magnitude of the reduction in insulin doses.

Telemedicine and diabetes: achievements and prospects.

Health authorities currently have high expectations for telemedicine (TM), as it addresses several major challenges: to improve access to healthcare (especially for patients in underserved or remote areas); to overcome the scarcity of specialists faced with epidemic disease; and to reduce the costs of healthcare while improving quality. The aims of TM in the field of diabetes differ according to the type of diabetes. In type 1 diabetes (T1DM) associated with complex insulin regimens, the goal of TM is to help patients achieve better control of their blood glucose levels through accurate adjustment of insulin doses. In type 2 diabetes (T2DM), while therapeutic adjustments may be necessary, improvement in blood glucose control is based primarily on behavioural changes (reduced calorie and carbohydrate intakes, increased physical activity). Many TM studies focusing on management of blood glucose levels have been published, but most failed to demonstrate any superiority of TM vs traditional care. While previously published meta-analyses have shown a slight advantage at best for TM, these meta-analyses included a mix of studies of varying durations and different populations (both T1DM and T2DM patients, adults and children), and tested systems of inconsistent quality. Studies published to date on TM suggest two currently promising approaches. First, handheld communicating devices, such as smartphones, loaded with software to apply physicians' prescriptions, have been shown to improve glycaemic control. These systems provide immediate assistance to the patient (such as insulin-dose calculation and food choice optimization at meals), and all data stored in the smartphone can be transmitted to authorized caregivers, enabling remote monitoring and even teleconsultation. These systems, initially developed for T1DM, appear to offer many possibilities for T2DM, too. Second, systems combining an interactive Internet system (or a mobile phone coupled to a remote server) with a system of communication between the healthcare provider and the patient by e-mail, texting or phone calls have also shown certain benefits for glycaemic control. These systems, primarily aimed at T2DM patients, generally provide motivational support as well. Although the individual benefits of these systems for glycaemic control are fewer than with smartphones, their widespread use should be of particular value for overcoming the relative shortage of doctors and reducing the health costs associated with a disease of such epidemic proportions.

Telemedicine: what more is needed for its integration in everyday life?

The Health Authorities have huge expectations of telemedicine (TM): improved patient access to healthcare, a solution to the shortage of doctors in the face of an exponentially expanding disease, and reduced healthcare costs with improved quality. There are a host of applications for TM in the area of diabetes. TM has been validated and has been widely used to screen for diabetic retinopathy, and a number of studies are currently underway for the follow-up of diabetic foot ulcers. However, the main indication of TM remains the follow-up and control of blood glucose. In this area, many studies have been conducted to improve glycaemic control. While most of these studies have failed to show any benefits vs. conventional care, a small number have demonstrated great efficacy of this approach with regard to glycaemia. Using these studies, we attempt to define the key qualities of a successful TM system. How can we extend the results of these experiments beyond the framework of clinical studies and integrate them in daily practice so as to improve diabetes management? This is the key challenge for TM, implementation of which will require reorganization of healthcare, given the evolution of medical demographics. This reorganization will involve healthcare providers specialized in diabetes that may intervene in assigning physicians for especially distressed patients. However, such reorganization will require medico-economic evaluation before it can be implemented on a larger scale.

Real-life application and validation of flexible intensive insulin-therapy algorithms in type 1 diabetes patients.

AIMS: Flexible intensive insulin therapy (FIT) has become the reference standard in type 1 diabetes. Besides carbohydrate counting (CHO), it requires the use of algorithms to adjust prandial insulin doses to the number of CHO portions. As recourse to standard algorithms is usual when initiating FIT, the use of personalized algorithms would also allow more precise adjustments to be made. The aim of the present study was to validate personalized prandial algorithms for FIT as proposed by Howorka et al. in 1990. METHODS: We conducted a 4-month observational study of 35 patients with type 1 diabetes, treated with FIT for at least 6 months, who were already using Howorka's prandial algorithms (meal-related and correctional insulin doses for blood glucose increases induced by CHO). These patients were asked to use a personal digital assistant (PDA) phone with an electronic diary (instead of a paper one) to take advantage of the computerized data-collection system to assess the quality of postprandial metabolic control. RESULTS: Whatever the number of CHO portions, mean postprandial blood glucose values remained close to the target of 7.8mmol/L, and the compensatory algorithm allowed precise correction of preprandial hyperglycaemia. In fact, the algorithms for meal-related and correctional insulin doses at the end of the study did not differ significantly from those initially calculated, but they generally differed from one patient to another. CONCLUSION: In type 1 diabetic patients treated with FIT, the use of individualized parameters permits fast and accurate adjustment of mealtime insulin doses, leading to good control of the postprandial state.

Real-time continuous glucose monitoring using GuardianRT: from research to clinical practice.

The limited number of self-monitoring blood glucose measurements is an obstacle for good metabolic control in patients with type 1 diabetes. However, continuous glucose measurement with real-time data and alarms is a recent technology that promises to improve the efficacy of treatment in diabetic patients. GuardianRT uses a continuous telemetry display of real-time glucose values, and automatic alerts at preset hypo- and hyperglycaemic levels. Three calibrations a day are required, and the sensor must be changed every three days. The GuardControl study showed that, within three months, real-time continuous glucose monitoring with the GuardianRT led to significantly improved HbA1c values in 162 poorly controlled patients (children and adults) with type 1 diabetes despite intensive insulin therapy. The continuous availability of glucose measurements permitted the patients to adjust their own insulin doses, food intake and physical activity and, thus, improve their glycaemic control. This report summarizes the available data on this tool and details how best to use this state-of-the-art modality in diabetic patients in clinical practice.

How should postprandial glycemia be treated?

In an attempt to prevent the complications of type 2 diabetes, particular attention should be paid to controlling postprandial glycemia (PPG): on the one hand, it contributes substantially to the HbAlc level in moderately controlled patients, on the other hand, the postprandial glucose peak induces oxidative stress and endothelial dysfunction, the first step toward accelerated atherogenesis. Metformin, glitazones, and insulin secretagogues have an additive effect on fasting blood glucose (FBG), and a significant impact on PPG. Alpha-glucosidase inhibitors can reduce PPG by a mean 0.50 g/l, no matter what the insulin resistance or insulinopenia status or the other diabetes treatments already in use. After evolving for several years and the failure of oral antidiabetics to normalize fasting blood glucose, long-acting (slow-acting) insulin analogues, well titrated, can reach this goal. They will have no effect on PPG other than a simple level effect. At this stage, rather than overtreating high fasting blood glucose concentrations, systematic PPG exploration should be the rule so as to better define PPG treatment: the advantages of alpha-glucosidase inhibitors and the role of GLP-1 analogs should be defined, the use of a rapid-acting insulin analog before the meal causing the highest postprandial blood glucose excursions, even systematically at all three meals, should be considered, or inhaled insulin. As natural life expectancy is on the rise, these active strategies designed to normalize the daily glycemic profile, necessary in a strict strategy to prevent the complications of diabetes, will need to be discussed for an increasing number of patients with type 2 diabetes.