Hypoglycemia is a limiting factor for achieving stringent glycemic control in diabetes. This study analyzes the frequency and predictors of hypoglycemia in insulin-treated diabetes in an ambulatory setting.

A retrospective chart review was performed to study self-monitored blood glucose (SMBG) data for 3 months prior to a patient's HbA1c test.

Hypoglycemia occurred more frequently in type 1 than in type 2 diabetes; however, 19% of type 2 diabetes patients did experience at least one episode of severe hypoglycemia. For type 1 diabetes, hypoglycemia had a positive association with glycemic variability and duration of diabetes and a negative association with HbA1c and lowest blood glucose (BG). For type 2 diabetes, a positive association was noted with glycemic variability and a negative association with age and lowest BG.

Delineating factors predisposing to hypoglycemia in type 2 diabetes is difficult. Lower HbA1c is a potential predictor of hypoglycemia in type 1 but not in type 2 diabetes. Longer duration of diabetes for type 1 and younger age for type 2 are associated with more hypoglycemia. Glycemic variability portends increased risk for hypoglycemia and should be a focus of further research.

The purpose of this study was to gain a better understanding of what it means for adolescent females to live with type 1 diabetes.

Van Manen's phenomenological framework was used to guide the project of inquiry. Adolescents were recruited from a diabetes camp. A purposive sample of 10 adolescent females, aged 16 and 17 years, volunteered to participate in the study. Unstructured, one-on-one interviews were conducted and participants' accounts were transcribed and analyzed for themes.

Five themes were identified: (1) blending in with the adolescent culture, (2) standing out and being watched, (3) weighing the options and making choices, (4) being tethered to the system and to diabetes, and (5) struggling with conflicts. These adolescent females struggled with several conflicts and choices they were forced to make on a daily basis. They felt tethered to a disease that would never go away and to the healthcare system. Yet, they adopted ways to handle their disease so that it was manageable within the context of their lives. Fitting in with their peers was often more important than diabetes management.

Making visible the experience of adolescent females living with type 1 diabetes has implications for practice, education, and research in diabetes education.

Insulin pump therapy associated with continuous glucose monitoring has shown a positive clinical impact on diabetes control and reduction of hypoglycemia episodes. There are descriptions of the performance of this device in other populations, but its precision and accuracy in Colombia and Latin America are unknown, especially in the routine outpatient setting.

Data from 33 type 1 and type 2 diabetes patients with sensor-augmented pump therapy with threshold suspend automation, MiniMed Paradigm® Veo™ (Medtronic, Northridge, California), managed at Hospital Universitario San Ignacio (Bogotá, Colombia) and receiving outpatient treatment, were analyzed. Simultaneous data from continuous glucose monitoring and capillary blood glucose were compared, and their precision and accuracy were calculating with different methods, including Clarke error grid.

Analyses included 2,262 continuous glucose monitoring -reference paired glucose values. A mean absolute relative difference of 20.1% was found for all measurements, with a value higher than 23% for glucose levels ≤75mg/dL. Global compliance with the ISO criteria was 64.9%. It was higher for values >75mg/dl (68.3%, 1,308 of 1,916 readings), than for those ≤ 75mg/dl (49.4%, 171 of 346 readings). Clinical accuracy, as assessed by the Clarke error grid, showed that 91.77% of data were within the A and B zones (75.6% in hypoglycemia).

A good numerical accuracy was found for continuous glucose monitoring in normo and hyperglycemia situations, with low precision in hypoglycemia. The clinical accuracy of the device was adequate, with no significant safety concerns for patients.

Eating disorders (ED) are characterized by a persistent disturbance of eating that impairs health or psychosocial functioning. They are associated with increased rates of medical complications and mortality. Insulin omission is a unique purging behavior available to individuals with type 1 diabetes mellitus (T1DM). The standard treatment regimen for T1DM requires a major focus on food and eating patterns. Moreover, intensive insulin therapy is associated with increasing body weight. These factors, combined with the psychological burden of chronic disease management and depression, may contribute to ED. The comorbidity of ED in T1DM patients is associated with poorer glycemic control and consequently higher rates of diabetes complications. Early recognition and adequate treatment of ED in T1DM is essential.

The application of the principle of autonomy, which is considered a cornerstone of contemporary bioethics, is sometimes in obvious contradiction with the principle of beneficence. Indeed, it may happen in chronic care that the preferences of the health care provider (HCP), who is largely focused on the prevention of long term complications of diseases, differ from those, more present oriented, preferences of the patient. The aims of this narrative review are as follows: 1) to show that the exercise of autonomy by the patient is not always possible; 2) where the latter is not possible, to examine how, in the context of the autonomy principle, someone (a HCP) can decide what is good (a treatment) for someone else (a patient) without falling into paternalism. Actually this analysis leads to a paradox: not only is the principle of beneficence sometimes conflicting with the principle of autonomy, but physician's beneficence may enter into conflict with the mere respect of the patient; and 3) to propose a solution to this paradox by revisiting the very concepts of the autonomous person, patient education, and trust in the patient-physician relationship: this article provides an ethical definition of patient education.

Experience with the use of real-time continuous glucose monitoring systems (RT-CGMS) in teenagers with type 1 diabetes mellitus (T1DM) is limited. We aimed to assess the possibility of glycaemic control improvement and to characterize the group of adolescents, who may gain long-term benefits from the use of the RT-CGMS.

Forty T1DM patients, aged 14.6 ± 2.1 years, with diabetes duration 7.4 ± 3.6 years and initial HbA₁c 9.3 ± 1.5% were recruited. The analysis was based on one-month glucose sensors use, combined with the thorough family support. Patients were analysed in groups according to baseline HbA₁c: below and above 7.5%, and 10.0%. Comparison between patients with or without improvement in HbA₁c after 3-month follow-up was also performed. Patients' satisfaction based on the questionnaire was assessed.

HbA₁c level in entire study group decreased after three months, from 9.3 ± 1.0% to 8.8 ± 1.6% (P<0.001). In the group with HbA1c improvement, reduction was the highest: 9.0 ± 1.3% vs. 8.0 ± 1.2% (P<0.001). Only the group with initial HbA₁c>10% did not achieve significant improvement: 11.2 ± 0.5% vs. 10.9 ± 1.1 (P=0.06). In satisfaction questionnaire the lowest scores (negative opinion) were reported by group of patients with initial HbA₁c above 10%, while the highest scores (positive opinion) were found in the group with improvement of HbA₁c after 3 month follow-up.

Short-term use of CGMS RT, united with satisfaction questionnaire, performed in poorly controlled teenagers with T1DM, can be useful in defining the group of young patients, who can benefit from long-term CGMS RT use in metabolic control improvement.

Self-monitoring of blood glucose (SMBG) is the most accessible way to assess glycemic patterns, and interpretation of these patterns can provide reasons for poor glycemic control and suggest management strategies. Furthermore, diabetes management based on blood glucose (BG) patterns is associated with improved patient outcomes. The aim of this review is therefore to evaluate the impact of pattern management in clinical practice.

We included a review of available literature, a discussion of obstacles to implementation of SMBG and pattern management, and suggestions on how clinicians and patients might work together to optimize this management feature.

The literature review revealed eight publications specifically describing structured approaches to SMBG and pattern management. Specific information on how SMBG might be structured to detect BG patterns, however, remains limited. Barriers to pattern management include not just practical reasons, but emotional and psychological reasons as well.

Patterns are not always easy to detect or interpret, but on-meter and web-based tools can support both patients and clinicians. Ultimately, successful pattern management requires education and mutual commitment from the clinician and patient--ongoing collaboration is needed to obtain, review, and interpret SMBG values and to make changes based on the patterns.

To determine the influence of number and type of antidiabetes medications on adherence and glycemia of ambulatory type 2 diabetes patients in southwestern Nigeria.

A cross-sectional study using pre-tested structured questionnaire among 176 consented patients recruited from the endocrinology clinics of two teaching hospitals between November, 2010 and January, 2011; and a retrospective review of case notes of the cohort for details of prescribed medications and blood glucose values. Descriptive statistics were used to summarize the data. Tests of proportions were evaluated using Chi-square or Fisher's exact test as appropriate. The differences in mean fasting blood glucose (FBG) between and among categorical variables were compared using student t-test and ANOVA respectively, with p<0.05 considered significant.

Mean number of prescribed medications was 4.6 ±1.4. Almost two thirds 103 (60.6%) were placed on >4 medications. Adherence was better among patients on >4 medications compared to those on ≤4 medications (p=0.05). However, patients on >4 medications were mostly older adults (>60 years of age), and they were in the majority (66.7%) who had tertiary education compared to 33.3% of those on ≤4 medications who had tertiary education (p=0.02). Adherence rates to antidiabetes medications were in the ranking of oral antidiabetes medications (OAM) alone (50.0%) > insulin plus OAM (44.0%) > insulin alone (41.7%) with no significant difference (p=0.77). There was a significant difference in mean FBG among patients on >4 medications (172.1 ±61.1mg/dL) versus (198.8 ±83.8mg/dL) among those on ≤4 medications (p=0.02).

Prescribing more than four medications is linked to improved adherence and glycemic outcome. However, age and educational background of patients are important factors that need to be considered when prescribing multiple medications for type 2 diabetes.

To report the population burden of hypoglycemia necessitating emergency medical services (EMS) and the long-term outcomes in patients with type 1 diabetes mellitus (T1DM) receiving different insulin treatments.

We retrieved all EMS calls because of hypoglycemia in patients with T1DM in Olmsted County, Minnesota, between January 1, 2003, and December 31, 2009, and reviewed the related medical records.

During the 7-year study period, 531 EMS calls were made involving 208 patients with T1DM (112 men, 96 women; mean age 47 ± 13 years). Of the 208 patients, 137 (66%) were receiving multiple daily insulin (MDI) injections, 50 (24%) were receiving continuous subcutaneous insulin infusion, 15 (7%) were receiving simple insulin (SI), 4 (2%) were treated with metformin + MDI, and 2 (1%) were not receiving treatment for diabetes (after pancreas transplantation). The last 2 groups were excluded from further analysis because of small sample size. The remaining 3 treatment groups differed by age (P<.02), with the oldest patients receiving SI. Repeated calls, emergency department transportation (EDT), and hospitalization had a 33%, 49%, and 18% frequency, respectively, and did not differ among the treatment groups. In a multivariate model, mortality was significantly associated with treatment type (the SI group had a higher risk for mortality than did the MDI group [P = .03] after exclusion of 27 patients who changed treatment during follow-up), age (P<.0001), and EDT (P = .04).

The population burden of EMS-requiring hypoglycemia in patients with T1DM is high. Medical resource utilization was similar among the 3 treatment groups. Mortality was higher in the SI group (limited by small sample size) and among patients requiring EDT and increased with advancing age. Further research could be directed toward understanding the effect of expert evaluation of high-risk patients on long-term outcomes.

Diabetes is associated with increased risk for eating disorders; with different types of eating disorders associating with different types of diabetes. Binge eating disorders show increased prevalence among individuals with type 2 diabetes (T2DM). Intentional omission of insulin for the purpose of inducing weight loss presents among individuals with type 1 (T1DM). Similarly, some individuals with T2DM intentionally omit oral hypoglycemic drugs, resulting in poor glycemic control, and weight loss. Common dominators for the development of eating disorders in T1DM and T2DM are female gender, increased body weight, body dissatisfaction, a history of dieting, and a history of depression. Patients tend to deny the existence of the problem. Clinical signs that should raise suspicion are: poor glycemic control, missed clinical appointments, recurrent episodes of diabetes ketoacidosis, recurrent hypoglycemia secondary to intentional overdose, poor self-esteem, and dietary manipulation. Eating disorders are associated with poorer glycemic control, and therefore increased risk of diabetes associated comorbidities.

Diabetic patients often do not adjust their insulin doses using the algorithms that they have been taught. While this behavior may intuitively have a number of causes, such as the complexity of the decision or the fear of hypoglycaemia, we propose in this article a more general, "psychophysical", explanation based on behavioral economics concepts used to describe decisions made under uncertainty and risk. The concepts discussed herein may not be familiar to clinicians, who will find here an introduction to theories that may be helpful in understanding some aspects of non-adherence to medical prescriptions.

1) The Prospect Theory of Kahneman and Tversky proposes that choices made in the context of risk are subject to loss aversion. 2) Decisions under uncertainty use mental short cuts called "heuristics", which can lead to biases; for instance, overestimating the probability of the risk. 3) To understand the very concept of risk, emotions must be considered with a special focus on anticipated regret. 4) Finally, selection difficulty is an important determinant of the preference for the status quo.

These concepts may be relevant for understanding a preference for the status quo in decisions made in a context of uncertainty and risk, such as insulin dose adjustment. We suggest that these mental mechanisms may also be involved in other aspects of patients' non-adherence. As other common human behaviors, non-adherence may actually often be a consequence of biases resulting from our ways of thinking, being both cognitive and emotional, and, according to Kahneman, more often "fast" than "slow". Empirical studies are needed to support this hypothesis.

Severe hypoglycemic events are a major consequence of tight diabetes control. Continuous glucose monitoring systems (CGMSs) were recently introduced in order to minimize the risk of hypoglycemia. However, the present CGMSs are invasive and costly and have been recently demonstrated to be intolerant for most children and adolescents. Hence there is a need for a simple, noninvasive, convenient, and inexpensive device to detect hypoglycemic events. The Gili Medical Hypoglycemia Non Invasive Monitoring System (GMHNIMS) (Gili Medical Ltd., Migdal HaEmek, Israel) has been currently developed for these purposes.

Ten patients 14-18 years old with type 1 diabetes for at least 1 year participated in a pilot study that was held at the Meyer Children's Hospital, Rambam Medical Center, Haifa, Israel. All patients were either treated by insulin pump or by multiple daily injections. The GMHNIMS was connected to the study subjects during three consecutive nights in an inpatient setting while they received their usual insulin regimen. The system is composed of four sensors (heart rate, perspiration, skin temperature, and tremor) that detect physiologic changes during hypoglycemia. In addition, each patient was connected to a real-time CGMS for 3 nights. When a hypoglycemic event was suspected clinically by the patient, a bedside capillary glucose was checked by a glucometer.

The system was found to be convenient without any disturbances to sleep quality. The sensitivity of the GMHNIMS for detection of true hypoglycemic events was 100% with specificity of 85.7%.

The new device showed high detection rates of nocturnal hypoglycemic events with an acceptable degree of false-positive readings. Being inexpensive and noninvasive, this device has the potential for routine use in insulin-treated patients.

The benefits of real-time continuous glucose monitoring (CGM) have been demonstrated in patients with type 1 diabetes. Our aim was to compare the effect of two modes of use of CGM, patient led or physician driven, for 1 year in subjects with poorly controlled type 1 diabetes.

Patients with type 1 diabetes aged 8-60 years with HbA(1c) ≥ 8% were randomly assigned to three groups (1:1:1). Outcomes for glucose control were assessed at 1 year for two modes of CGM (group 1: patient led; group 2: physician driven) versus conventional self-monitoring of blood glucose (group 3: control).

A total of 257 subjects with type 1 diabetes underwent screening. Of these, 197 were randomized, with 178 patients completing the study (age: 36 ± 14 years; HbA(1c): 8.9 ± 0.9%). HbA(1c) improved similarly in both CGM groups and was reduced compared with the control group (group 1 vs. group 3: -0.52%, P = 0.0006; group 2 vs. group 3: -0.47%, P = 0.0008; groups 1 + 2 vs. group 3: -0.50%, P < 0.0001). The incidence of hypoglycemia was similar in the three groups. Patient SF-36 questionnaire physical health score improved in both experimental CGM groups (P = 0.004). Sensor consumption was 34% lower in group 2 than in group 1 (median [Q1-Q3] consumption: group 1: 3.42/month [2.20-3.91] vs. group 2: 2.25/month [1.27-2.99], P = 0.001).

Both patient-led and physician-driven CGM provide similar long-term improvement in glucose control in patients with poorly controlled type 1 diabetes, but the physician-driven CGM mode used fewer sensors.

Glycemic control is an important goal of treatment to delay the progression of and complications associated with diabetes, but controversies exist regarding individual HbA1c control targets for different patients. With the aim of optimizing outcomes and minimizing adverse events, a preliminary consensus on HbA1c control targets for adults with Type 2 diabetes has been proposed by the Chinese Society of Endocrinology (CSE). Instead of recommending a general standard value for all patients, the CSE suggests that a relatively reasonable stratified and tailored target for individual patients should take into consideration both clinical status and social factors. Principles governing the establishment of a glycemic control target include safety, feasibility, scientific evidence, and customized care, of which the most important factor is safety. In addition to controlling plasma glucose, equal consideration should be given to other vascular disease risk factors.

Therapeutic nonadherence is defined as the lack of equivalence between the behavior of the patients and their prescribed medical treatment. Consequences of nonadherence include not only health outcomes, but also cost saving. Thus, this issue gets paramount importance in contemporary medicine.

The aim of this article is to discuss the relationships between technology and adherence by asking the following three questions. (1) How can technology be used to monitor patient adherence? (2) Considering the mechanisms of nonadherence in chronic diseases, is there room for technology in interventions aimed to improve patient adherence? (3) What about adherence to technology in diabetes care?

Technology may help improve adherence to long-term therapies by (1) giving a concrete representation of adherence rewards, (2) overcoming immediate obstacles to adherence, such as the fear of hypoglycemia, and (3) providing an opportunity for patient-doctor conversations. This assumes, however, that both the patient and the doctor are convinced that technologies are useful.

Girls and women with type 1 diabetes have increased rates of disturbed eating behaviors and clinically significant eating disorders than their nondiabetic peers. Type 1 diabetes is strongly associated with several empirically supported eating disorder risk factors (eg, higher body mass index, increased body weight and shape dissatisfaction, low self-esteem and depression, and dietary restraint). It may be that specific aspects of diabetes treatment increase the risk for developing disordered eating. Disturbed eating behaviors and clinical eating disorders predispose women with diabetes to many complex medical risks and increase risk of morbidity and mortality. For this reason, it is critical that diabetes clinicians understand more about eating disorders to improve the likelihood of early risk detection and access to appropriate treatment. This article presents a review of the current scientific literature on eating disturbances in type 1 diabetes and synthesizes the existent findings into recommendations for screening and treatment.

The value of continuous glucose monitoring in the management of type 1 diabetes mellitus has not been determined.

In a multicenter clinical trial, we randomly assigned 322 adults and children who were already receiving intensive therapy for type 1 diabetes to a group with continuous glucose monitoring or to a control group performing home monitoring with a blood glucose meter. All the patients were stratified into three groups according to age and had a glycated hemoglobin level of 7.0 to 10.0%. The primary outcome was the change in the glycated hemoglobin level at 26 weeks.

The changes in glycated hemoglobin levels in the two study groups varied markedly according to age group (P=0.003), with a significant difference among patients 25 years of age or older that favored the continuous-monitoring group (mean difference in change, -0.53%; 95% confidence interval [CI], -0.71 to -0.35; P<0.001). The between-group difference was not significant among those who were 15 to 24 years of age (mean difference, 0.08; 95% CI, -0.17 to 0.33; P=0.52) or among those who were 8 to 14 years of age (mean difference, -0.13; 95% CI, -0.38 to 0.11; P=0.29). Secondary glycated hemoglobin outcomes were better in the continuous-monitoring group than in the control group among the oldest and youngest patients but not among those who were 15 to 24 years of age. The use of continuous glucose monitoring averaged 6.0 or more days per week for 83% of patients 25 years of age or older, 30% of those 15 to 24 years of age, and 50% of those 8 to 14 years of age. The rate of severe hypoglycemia was low and did not differ between the two study groups; however, the trial was not powered to detect such a difference.

Continuous glucose monitoring can be associated with improved glycemic control in adults with type 1 diabetes. Further work is needed to identify barriers to effectiveness of continuous monitoring in children and adolescents. (ClinicalTrials.gov number, NCT00406133.)

Results of both the Diabetes Control and Complications Trial and the United Kingdom Prospective Diabetes Studies supported the role of tight glucose control in reducing long-term complications of diabetes. There is further evidence that glycemic variability may be better correlated with the risk for complications than sustained hyperglycemia. These studies reinforce the need to work toward improved glucose control with minimal variability in patients with diabetes. Continuous glucose monitoring technology offers a means of obtaining a more complete picture of glucose patterns and can be used to aid in identifying trends in glycemic variability, especially overnight and after meals when blood glucose testing is not usually performed. Increased access to retrospective trends, the addition of real-time glucose alarms, and prospective trend data can be advantageous in motivating and evaluating behavior change.

This paper presents a critical review of continuous glucose monitoring studies that address accuracy, utility in assessing glucose variability, detection of hypoglycemia for improved metabolic control or reduced glucose variability, impact on quality of life, reduced fear of hypoglycemia, and applicability in helping patients to overcome their reluctance to intensify insulin therapy. This analysis can be used to delineate the evidence that is still missing when considering continuous glucose monitoring as an established tool in clinical practice and for reimbursement of the system and services.

To ascertain the frequency and identify predictors of self-reported hypoglycaemia in Type 1 and insulin-treated Type 2 diabetes.

A random sample of 267 people with insulin-treated diabetes were recruited from a population-based diabetes register in Tayside, Scotland. Each subject prospectively recorded the number of mild and severe hypoglycaemic episodes experienced over a 1-month period. Ordinal logistic regression was performed to identify potential predictors of hypoglycaemia.

Five hundred and seventy-two hypoglycaemic events were reported by 155 patients. The participants with Type 1 diabetes had a total of 336 hypoglycaemic events with a rate of 42.89 events per patient per year. Of these, nine were severe hypoglycaemic events, with a rate of 1.15 events per patient per year. Participants with insulin-treated Type 2 diabetes experienced a total of 236 hypoglycaemic events with a rate of 16.37 events per patient per year. Of these, five were severe hypoglycaemic events, which would be equivalent to 0.35 events per patient per year. Predictors of hypoglycaemia in Type 1 diabetes were a history of previous hypoglycaemia (P = 0.006) and co-prescribing of any oral drug (P = 0.048). In patients with insulin-treated Type 2 diabetes, a history of previous hypoglycaemia (P < 0.0001) and duration of insulin treatment (P = 0.014) were significant predictors.

The incidence of self-reported severe hypoglycaemia in insulin-treated Type 2 diabetes is lower than in Type 1 diabetes but does occur more often than previously reported and with sufficient frequency to cause significant morbidity. Duration of insulin treatment is a key predictor of hypoglycaemia in insulin-treated Type 2 diabetes.

A series of case reports in the early 1980s and prevalence studies in the 1990s highlighted the serious medical consequences of coexisting eating disorders and diabetes mellitus. Diabetes-specific treatment issues, such as the need to carefully monitor diet, exercise, and blood glucose, may contribute to the development of eating disorder symptoms among women with diabetes mellitus. The attention to food portions and bodyweight that is part of routine diabetes mellitus management parallels the rigid thinking about food and body image found in women with eating disorders who do not have diabetes mellitus. Additionally, intensive insulin management of diabetes mellitus, the current standard of care, has been shown to be associated with bodyweight gain. Following from this, it may be that the very goals of state-of-the-art diabetes mellitus care increase the risk for developing an eating disorder. Once an eating disorder and recurrent insulin omission becomes entrenched, a pattern develops which is hard to break - one of chronic hyperglycemia, depressed mood, fear of bodyweight gain, and frustration with diabetes management. Eating disorders predispose women with diabetes mellitus to many complex medical risks. For example, insulin omission and reduction, eating disorder symptoms unique to diabetes mellitus, are strongly associated with an increased risk of diabetic ketoacidosis and with microvascular complications of diabetes mellitus such as retinopathy. For this reason, it is critical that diabetes mellitus clinicians understand more about eating disorders so as to improve the likelihood of early detection, appropriate treatment, and prevention of acute and long-term medical complications within this high-risk group of women.

The purpose of this study was to examine patient attitudes toward weight gain with medications under 4 conditions-medical vs psychiatric and life-threatening vs non-life-threatening.

In a suburban primary care practice, 241 patients completed surveys that explored the 4 study conditions and the amount of weight, from 0 to 20 or more pounds, willing to be gained on medication.

Participants were willing to gain an average of 5.51 lb for a non-life-threatening medical condition, 5.37 lb for a non-life-threatening psychiatric condition, 13.30 lb for a life-threatening medical condition, and 12.70 lb for a life-threatening psychiatric condition. Participants were willing to gain significantly more weight with a medical vs psychiatric condition and with a life-threatening vs non-life-threatening condition. There were no significant gender differences in responses.

There appear to be distinct patterns of acceptability of weight gain with medications. This information may enhance prescribers' ability to strategize medication compliance among patients.

To compare blood glucose control and incidence of nocturnal hypoglycemia in adolescents with type 1 diabetes on multiple injection regimens managed with either an insulin analog combination or NPH insulin plus regular human insulin.

In a randomized cross-over study, 28 adolescents with type 1 diabetes on multiple injection therapy received either insulin glargine prebedtime plus lispro preprandially (LIS/GLAR) or NPH insulin prebedtime plus regular human insulin preprandially (R/NPH). During each 16-week treatment arm, subjects completed home blood glucose profiles, and at the end of each treatment arm, they were admitted for an overnight metabolic profile. A total of 25 subjects completed the study.

Compared with R/NPH therapy, LIS/GLAR was associated with lower mean blood glucose levels (LIS/GLAR versus R/NPH): fasting (8.0 vs. 9.2 mmol/l, P < 0.0001), 2 h postbreakfast (8.1 vs. 10.7 mmol/l, P < 0.0005), prelunch (8.9 vs. 10.1 mmol/l, P < 0.01), and 2 h postlunch (8.0 vs. 9.5 mmol/l, P < 0.002). However, there was no difference in mean blood glucose levels before or after the evening meal. Incidence of nocturnal hypoglycemia on overnight profiles was 43% lower on LIS/GLAR compared with R/NPH therapy; however, there was no difference in rates of self-reported symptomatic hypoglycemia. Total insulin dose required to achieve target blood glucose control was lower on LIS/GLAR (1.16 IU/kg) compared with R/NPH therapy (1.26 IU/kg, P < 0.005), but there was no significant difference in HbA(1c) levels (LIS/GLAR versus R/NPH: 8.7 vs. 9.1%, P = 0.13).

Combination therapy with insulin glargine plus lispro reduced the incidence of nocturnal hypoglycemia and was at least as effective as R/NPH insulin therapy in maintaining glycemic control in adolescents on multiple injection regimens.

The goal of this study was to evaluate the effectiveness of two monitoring schemes(blood and urine) in the metabolic control of type 1 diabetic patients, in biweekly therapeutic adjustments, along 6 months of participation in the educational groups. A sample of 34 patients was divided in two groups. The interventions proposed to group A were daily blood glucose monitoring, during three consecutive days for each period (before breakfast, before lunch, before dinner and before bed) and biweekly in the dawn. For the other group B was proposed daily urine glucose monitoring, during three consecutive days for each period (before breakfast, before lunch, before dinner and before bed). These schemes were used to construct glycemic profile and to determine the therapeutic adjustments. The results evidenced that there was no significant statistical difference in the metabolic control after proposed intervention in each group. In spite of this, the monitoring facilitated the educational process and the considerations about the use of more intensive monitoring schemes.

To audit glycaemic control and incidence of severe hypoglycaemia in children and adolescents with type 1 diabetes in New South Wales (NSW) and the Australian Capital Territory (ACT).

A multicentre, population-based, cross-sectional study from 1 September to 31 December, 1999.

1190 children and adolescents aged 1.2-15.8 years with type 1 diabetes, identified from three hospital-based paediatric diabetes units, four private city-based paediatric practices and 18 regional outreach clinics in NSW and the ACT.

HbA(1c) level and incidence of severe hypoglycaemia (defined by unconsciousness or seizures).

The response rate was 67% (1190 of a target group of 1765). The median HbA(1c) level was 8.2% (interquartile range, 7.6%-9.1%). Significant predictors of HbA1c level in a multiple regression model were duration (b = 0.05; 95% CI, 0.02-0.07) and insulin dose/kg (b = 0.46; 95% CI, 0.27-0.66). At least one episode of severe hypoglycaemia in the previous three months was reported in 6.7%, and the rate of severe hypoglycaemia was 36/100 patient-years. Significant predictors of hypoglycaemia in a Poisson regression model were younger age (P = 0.03), male sex (P = 0.04), longer diabetes duration (P = 0.02), and > 3 daily insulin injections (P = 0.02), but not HbA(1c) level. Children with diabetes had higher BMI standard deviation scores compared with population standards, and those in the highest quartile of BMI standard deviation score were younger, had shorter diabetes duration and had higher HbA(1c) level.

Many children and adolescents with type 1 diabetes have suboptimal glycaemic control, placing them at high risk of developing microvascular complications. Those with longer diabetes duration are at increased risk of suboptimal glycaemic control and severe hypoglycaemia and should be targeted for interventional strategies.

Glycemic control is associated with microvascular events, but its effect on the risk of heart failure is not well understood. We examined the association between hemoglobin (Hb) A(Ic) and the risk of heart failure hospitalization and/or death in a population-based sample of adult patients with diabetes and assessed whether this association differed by patient sex, heart failure pathogenesis, and hypertension status.

A cohort design was used with baseline between January 1, 1995, and June 30, 1996, and follow-up through December 31, 1997 (median 2.2 years). Participants were 25 958 men and 22 900 women with (predominantly type 2) diabetes, >/=19 years old, with no known history of heart failure. There were a total of 935 events (516 among men; 419 among women). After adjustment for age, sex, race/ethnicity, education level, cigarette smoking, alcohol consumption, hypertension, obesity, use of beta-blockers and ACE inhibitors, type and duration of diabetes, and incidence of interim myocardial infarction, each 1% increase in Hb A(Ic) was associated with an 8% increased risk of heart failure (95% CI 5% to 12%). An Hb A(Ic) >/=10, relative to Hb A(Ic) <7, was associated with 1.56-fold (95% CI 1.26 to 1.93) greater risk of heart failure. Although the association was stronger in men than in women, no differences existed by heart failure pathogenesis or hypertension status.

These results confirm previous evidence that poor glycemic control may be associated with an increased risk of heart failure among adult patients with diabetes.

Symptomatic hypoglycemia is an unavoidable problem in the treatment of type I diabetes. Celiac disease is associated with malabsorption and may therefore represent an important risk factor.

The frequency of symptomatic hypoglycemia in patients with type I diabetes and celiac disease (cases) was compared with those of patients who had diabetes without celiac disease (controls). For this purpose, each case was matched for age, sex, and duration of disease with one to two control patients. Indices of metabolic control (hemoglobin [Hb]A1c, frequency of hypoglycemia, and total insulin requirement) were retrieved for the 18 months before and after diagnosis of celiac disease.

Eighteen patients (6 males and 12 females) had diagnosed celiac disease and were matched with 26 control patients (10 males and 16 females). There was no difference in age (11.0 years; range, 1.8-21.9 vs. 13.1 years; range, 2.3-22; P = 0.3) and duration of disease (8.4 years; range, 1.2-19.3 vs. 8.3 years; range, 1.1-18.7; P = 0.3) between the two groups. During the 6 months before and after diagnosis of celiac disease the cases had significantly more hypoglycemic episodes than the controls (means +/- SD; 4.5+/-4 vs. 2.0+/-2.2 episodes/months, P = 0.01). This was reflected by a progressive reduction in insulin requirement over the 12 months before diagnosis reaching a nadir at time 0 (0.6+/-0.2 vs. 0.9+/-0.3, P = 0.05).

These data suggest that underlying celiac disease is associated with an increased risk of symptomatic hypoglycemia and that the introduction of a gluten-free diet with normalization of the intestinal mucosa may reduce its frequency.

The transition from childhood through adolescence to adulthood is a difficult stage, particularly for patients with type 1 diabetes. The yearning for autonomy and independence, as well as the hormonal changes around the time of puberty, can manifest in poor glycaemic control. The focus on diet and weight increases the prevalence of eating disorders, compounding the difficulties in supervising diabetes patients. This can be exacerbated by the realisation that hyperglycaemia induces weight loss and the use of this knowledge to further manipulate diabetes control to gain a desired body image. The management of adolescents with type 1 diabetes is therefore challenging and requires close collaboration between psychological medicine and diabetes teams. This review describes the difficulties frequently encountered, with a description of four cases illustrating these points. Case 1 demonstrates the problem of needle phobia in a newly diagnosed patient with type 1 diabetes leading to persistent hyperglycaemia, the recognition of weight loss associated with this and the development of bulimia. The patient's overall management was further complicated by risk-taking behaviour. By the age of 24 years, she has developed diabetic retinopathy and autonomic neuropathy and continues to partake in risk-taking behaviour. Case 2 illustrates how the lack of parental support shortly after the development of type 1 diabetes led to poor glycaemic control and how teenagers often omit insulin to accommodate lifestyle and risk-taking behaviour. Case 3 further exemplifies the difficulty in managing patients with needle phobia and the fear of hypoglycaemia. Case 4 adds further weight to the need for parental support and the impact of deleterious life events on glycaemic control by manipulation of insulin dosage.

Hypoglycemia is the most common acute complication in insulin-treated type 1 diabetic patients. Most surveys have demonstrated that the tighter the glycemic control, and the younger the patient, the greater the frequency of both mild and severe hypoglycemia. However, people in poor metabolic control, with high glycosylated hemoglobin levels, are not protected from experiencing severe hypoglycemia. Focusing on the pediatric population, we review new or controversial issues surrounding the prevalence of hypoglycemia, its causes, its consequences and preventive strategies, and discuss possible mechanisms underlying the variability of responses to hypoglycemia.

Patients with Type 1 diabetes mellitus (DM) appear to have remarkably stable HbA1c levels, regardless of the need for improvement. The purpose of the present study was therefore to study predictors of intra-individual variability of the HbA1c level together with changes in HbA1c over time.

Hospital records of patients with Type 1 DM seen at our diabetes clinic from February 1992 to May 1997 were reviewed for HbA1c measurements and clinical data. In the main study, 214 patients who had been on insulin for more than 1 year, and in a sub-study, 14 patients newly started on insulin, were included.

The coefficient of variation (CV) of the intra-individual HbA1c measurements, after at least 1 year of insulin, was 8.8 +/- 3.7% (mean +/- SD). There was a positive association between the CV and the HbA1c measurement at inclusion in the study (P < 0.05), and also a negative association between the CV and age (P < 0.05). Fifty per cent of the patients had a difference between first and last HbA1c below 1%, and 83.6% had a difference below 2%. In the sub-study, there was a positive association between the mean HbA1c value the first year on insulin (excluding the first 3 months) and the last HbA1c measurement (P < 0.01).

The HbA1c levels in individual patients remain remarkably stable over time. Furthermore, the HbA1c level shortly after starting insulin is a predictor of future glycaemic control.