Diabetes knowledge in adolescents with type 1 diabetes and their parents and glycemic control.

OBJECTIVE: To evaluate diabetes knowledge and skills (DKS) in adolescents (>10 year) with type 1 diabetes (T1D) and their parents, and its effect on glycemic control. METHODS: A ready-to-use program and a standardized questionnaire comprising 50 true-false questions based on this program, were elaborated by a National Committee, to help dispensing education at diagnosis of T1D. The questionnaire was completed by 2933 T1D patients (49% girls, 51% boys; 14.1 ± 2.5 year), 2180 mothers and 798 fathers, in 115 pediatric centers. Associations between DKS score (number of correct answers), glycated hemoglobin (HbA1c) and sociofamilial characteristics were assessed. RESULTS: DKS score increased with age, and was higher in girls than in boys and in mothers than in fathers; it correlated strongly between adolescents and their own parents; it was higher when adolescents had previously participated in diabetes camp and when parents had higher academic levels. HbA1c decreased significantly with parents' higher DKS score and academic level, and when both parents lived together. Mean adolescent DKS score was significantly higher in patients with HbA1c below 8% or 8.5% than for patients with HbA1c above these thresholds. CONCLUSION: A large survey in T1D children and adolescents and their parents showed associations between DKS and glycemic control, and the major role of sociofamilial factors.

Insulin regimens, diabetes knowledge, quality of life, and HbA1c in children and adolescents with type 1 diabetes.

OBJECTIVES: To further describe the changes in insulin therapy regimens and hemoglobin A1c (HbA1c) in children and adolescents with type 1 diabetes, and their associations with diabetes knowledge and quality of life. RESEARCH DESIGN AND METHODS: The study included 4293 children and adolescents (12.9 ± 2.6 yr, diabetes >1 yr) attending AJD (Aide aux Jeunes Diabétiques) summer camps between 2009 and 2014. The distribution of insulin regimens and associations between HbA1c, therapeutic regimens, diabetes knowledge (AJD questionnaire), and Quality of Life (Ingersoll et Marrero, Hvidoere Study Group short version) were assessed. RESULTS: The percentage of youth treated with insulin pumps increased up to about 45%, basal bolus stabilized around 40%, and other regimens decreased majorly. HbA1c was higher with premixed insulins only regimens (9.05 ± 2.43%), but there was no difference between pump (8.12 ± 1.09%), basal bolus (8.32 ± 1.33%) and two to three injections (8.18 ± 1.28%). Mean HbA1c decreased by 0.014% per year. The percentage of HbA1c <7.5% increased by 1.5% per year, and the percentages of HbA1c >9% or >10% decreased by 4 and 5.5%, changes being greater with the pump. HbA1c was weakly associated with diabetes knowledge, and strongly with general health perception and perception about diabetes. CONCLUSION: The percentage of children and adolescents with the highest risk of complications decreased markedly. The distribution of HbA1c better depicts the glycemic control in a population than the mean or the percentage of patients reaching the target (7.5%). HbA1c was more strongly associated with general health perception than with therapeutic regimens and diabetes knowledge.

Changes in insulin therapy regimens over 10 yr in children and adolescents with type 1 diabetes attending diabetes camps.

OBJECTIVE: To describe the changes in insulin therapy regimens of children and adolescents with type 1 diabetes over 10 yr and their correlation with hemoglobin A1c (HbA1c). RESEARCH DESIGN AND METHODS: The study included 7206 children and adolescents (age 12.8 ± 2.7 yr, more than 1 yr of diabetes duration) admitted in summer camps between 1998 and 2007 (707-896/yr). Based on injection times (breakfast, lunch, afternoon, dinner, bedtime) and insulin types (short, long and premixed; human or analog), 786 different therapeutic combinations were classified in six main types of regimens. The distribution of the different regimens and their correlation with HbA1c were evaluated as a function of year and age. RESULTS: Over 10 yr, basal bolus increased from 13 to 52% and the pump from <1 to 13%, regimens with two to three injections per day decreased from 50 to 25%, those with only premixed insulins from 33 to 7%, and diverse regimens from 9 to 1%. HbA1c was significantly higher with premixed insulin only, but there were no differences between the other regimens throughout the follow-up. Mean yearly HbA1c (8.21-8.45%) did not show any significant decrease, but the percentage of patients with HbA1c > 9 and 10% decreased significantly, in those treated with two to three injections and the pump, not with basal bolus or premixed only regimens. CONCLUSION: A major trend in intensifying insulin treatment in children and adolescents with type 1 diabetes was accompanied by modest improvements in HbA1c. No insulin regimen has shown any better results, except over premixed insulins.

[Evaluation of an original tool for carbohydrate counting, aimed at facilitating the implementation of functional insulin therapy]. / Développement d'un nouvel outil d'évaluation de comptage des glucides pour faciliter la mise en oeuvre d'une insulinothérapie fonctionnelle.

OBJECTIVE: Carbohydrate counting is the most difficult component of functional insulin therapy. We thus designed a tool to facilitate carbohydrate counting of meals. RESEARCH DESIGN AND METHODS: The tool consists of an illustrated directory (16 x 10 cm, 119 pages) presenting 389 pictures of food, classified in 12 categories (breads, fruits, vegetables, etc.). For each photo, the name and mode of preparation of the foods are given, with the weight of the illustrated portion and its carbohydrate content as a multiple of 5 g. During the first phase of the study (3 days a week for 12 weeks), twelve patients with type 1 diabetes completed a precise food diary using a list and weight of all consumed foods. We were thus able to determine, for each of three meals (breakfast, lunch and dinner), the variability of their carbohydrate content. During the second phase of the study (2 weeks), the patients were given the possibility of using the illustrated food directory. We asked them first to estimate, from the photos, the global carbohydrate content of their meals, and then to weigh each food. This allowed us to calculate the true carbohydrate content of the meals from nutritional tables. RESULTS: During the first phase, the carbohydrate contents of breakfast, lunch and dinner were 67 +/- 29, 72 +/- 30 and 74 +/- 30 g, respectively (mean +/- SD, n = 12). For a given patient, the variability in the carbohydrate content of each meal was expressed by its standard deviation (SD). For the 12 patients, this variability was 18+/-+ 8, 25+/-+ 8 and 27+/-+ 11 g, respectively, for breakfast, lunch and dinner, and represented on the average about one-quarter of the total carbohydrate content. During the second phase, carbohydrate content, estimated by the patients using the illustrated food directory, correlated well with the retrospective evaluation based on nutritional tables (y = 0.95 x + 5 g, r2 = 0.8 ; n = 12, 235 meals). CONCLUSION: This new illustrated food repertory allows accurate evaluation of the highly variable carbohydrate content of meals, and could thus facilitate functional insulin therapy.

Trends in childhood type 1 diabetes incidence in France, 2010-2015.

AIMS: To estimate type 1 diabetes incidence in children in France and its evolution between 2010 and 2015, based on comprehensive medico-administrative databases. METHODS: The algorithm built to identify new cases of type 1 diabetes selected children aged between 6 months and 14 years who had at least one hospital stay for diabetes, followed by their first insulin treatment, excluding children suffering from another form of diabetes. Age and sex specific annual incidence rates were estimated and time trend was analyzed using Poisson regression. RESULTS: A total of 12 067 children were identified as newly diagnosed with type 1 diabetes and the annual incidence rates increased between 2010 and 2015 (from 15.4 [95% Confidence Interval: 14.7; 16.1] to 19.1 [18.3; 19.9] per 100 000 person-years), among boys and girls, and in each age group (4 and under, 5-9, 10-14 year olds). The annual rate of increase was 4.0% [3.4; 4.6]. This trend was not significantly different between each gender, and each age group. CONCLUSIONS: Valid database information on disease incidence is essential for healthcare planning and provides a valuable resource for health research. An increase of the incidence rate of type 1 diabetes in children was highlighted in both sexes and in all age groups.

A novel method for measuring patients' adherence to insulin dosing guidelines: introducing indicators of adherence.

BACKGROUND: Diabetic type 1 patients are often advised to use dose adjustment guidelines to calculate their doses of insulin. Conventional methods of measuring patients' adherence are not applicable to these cases, because insulin doses are not determined in advance. We propose a method and a number of indicators to measure patients' conformance to these insulin dosing guidelines. METHODS: We used a database of logbooks of type 1 diabetic patients who participated in a summer camp. Patients used a guideline to calculate the doses of insulin lispro and glargine four times a day, and registered their injected doses in the database. We implemented the guideline in a computer system to calculate recommended doses. We then compared injected and recommended doses by using five indicators that we designed for this purpose: absolute agreement (AA): the two doses are the same; relative agreement (RA): there is a slight difference between them; extreme disagreement (ED): the administered and recommended doses are merely opposite; Under-treatment (UT) and over-treatment (OT): the injected dose is not enough or too high, respectively. We used weighted linear regression model to study the evolution of these indicators over time. RESULTS: We analyzed 1656 insulin doses injected by 28 patients during a three weeks camp. Overall indicator rates were AA = 45%, RA = 30%, ED = 2%, UT = 26% and OT = 30%. The highest rate of absolute agreement is obtained for insulin glargine (AA = 70%). One patient with alarming behavior (AA = 29%, RA = 24% and ED = 8%) was detected. The monitoring of these indicators over time revealed a crescendo curve of adherence rate which fitted well in a weighted linear model (slope = 0.85, significance = 0.002). This shows an improvement in the quality of therapeutic decision-making of patients during the camp. CONCLUSION: Our method allowed the measurement of patients' adherence to their insulin adjustment guidelines. The indicators that we introduced were capable of providing quantitative data on the quality of patients' decision-making for the studied population as a whole, for each individual patient, for all injections, and for each time of injection separately. They can be implemented in monitoring systems to detect non-adherent patients.

[Obesity, immune resistance and metabolic complications: what morbid obesity can teach the doctor]. / Obésité, insulinorésistance et complications métaboliques: ce que l'obésité morbide apprend au médecin.

Abdominal -- and not peripheral -- obesity induces insulin resistance. Morbid obesity is not always accompanied by either diabetes mellitus or metabolic syndrome. Development of morbid obesity can require appropriate insulin secretion and recruitment of small insulin-sensitive adipocytes, able to store fatty acids. These fatty acids are therefore not stored in ectopic sites (muscle, liver, islets of Langerhans), and neither insulin resistance nor glucolipid toxicity develops and causes insulin deficiency. This explains the relative rarity of diabetes in morbid obesity. Patients with morbid obesity are at greater risk of developing mechanical complications (e.g. cardiac, pulmonary, or locomotor system, or sleep apnea) than metabolic complications or cardiovascular heart disease.

Prevention of hypoglycemia using risk assessment with a continuous glucose monitoring system.

Due to the lag between sugar intake and the beginning of recovery from hypoglycemia, it is necessary to intervene in an anticipatory way if one wants to prevent, not only detect, hypoglycemia. This article presents the principle of a hypoglycemia prevention system based on risk assessment. The risk situation can be defined as the moment when the system estimates that the glucose concentration is expected to reach a hypoglycemia threshold in less than a given time (e.g., 20 min). Since there are well-known discrepancies between blood and interstitial glucose concentrations, the aim of this experimental study performed in nondiabetic rats was first to validate this strategy, and second to determine whether it can work when the glucose concentration is estimated by a glucose sensor in subcutaneous tissue rather than in blood. We used a model of controlled decrease in blood glucose concentration. A glucose infusion, the profile of which mimicked the appearance of glucose from an intragastric load, was administered either when hypoglycemia was detected or on the basis of risk recognition. Despite the lag between the beginning of the load and that of the increase in blood glucose concentration, which was in all experiments 15-20 min, hypoglycemia was fully prevented without overshoot hyperglycemia in the groups of rats in which the glucose load was started when the hypoglycemia risk was detected, on the basis of either blood or interstitial glucose concentration. This was, of course, not the case when the same glucose load was infused at the detection of the hypoglycemia threshold.

Continuous glucose monitoring: physiological and technological challenges.

Over the past decade, several continuous glucose monitoring systems have been developed, representing remarkable technological achievements. Most of the systems monitor glucose invasively in the subcutaneous tissue. It is important to realize that there are discrepancies between blood and interstitial glucose concentration, which (1) may impact the quality of the system calibration and thereby the accuracy of the data, (2) may jeopardize the specificity and the sensitivity of hypoglycaemic alarms based on these systems and (3) must be considered in the design of closed-loop insulin delivery systems. The aim of this review is to make the point that the challenge of developing a continuous glucose monitoring system is not only technological, but must also take into account the physiology of glucose in alternate sites where it is sensed.

[Multidisciplinary management of gastroplasty candidates: example of Avicenne Hospital]. / Parcours multidisciplinaire du candidat à une gastroplastie: l'exemple de l'hôpital Avicenne.

The decision to perform gastroplasty must be made by a multidisciplinary team. This organization ensures compliance with good practice guidelines. Multidisciplinary management after surgery is also essential but patients' adhesion to follow-up is relatively poor.

A novel method for assessing insulin dose adjustments by patients with diabetes.

BACKGROUND: Insulin treated diabetic patients often do not adjust their insulin doses. We developed a method to provide a quantitative and qualitative assessment of this behavior. METHODS: Fourteen patients provided logbook pages of their self-monitoring of blood glucose (SMBG) data and insulin doses. We compared the actual decisions of patients in real-life to what they would decide on the same SMBG, as an a posteriori exercise. We also compared these decisions and those proposed by 6 diabetologists on the same sets of data to the recommendations made by HumaLink, an automated insulin dosage system. RESULTS: 1) Patients in real-life modified their insulin doses least often. However, given a chance to make these decisions a posteriori, they modified their insulin doses more often. HumaLink proposed changes even more often, and diabetologists were the most aggressive in changing insulin doses. 2) The decisions proposed by the patients in real-life or a posteriori and by the diabetologists were compared to the recommendations made by HumaLink, using a decisions analysis grid (DAG). For these three groups, full disagreement with HumaLink (patient or physician increases while HumaLink decreases and the opposite) was observed for less than 5% of the cases. 3) By comparison to HumaLink, patient decisions seemed guided by the desire to avoid hypoglycemia. By contrast, decisions by diabetologists seemed often to be guided by the desire to avoid hyperglycemia. CONCLUSION: These methods provide an objective evaluation of insulin dose adjustments by patients with diabetes and may be useful to assess the effectiveness of educational programs.