Increased risk of hepatocellular carcinoma among patients with hepatitis C cirrhosis and diabetes mellitus

Recent studies suggest that diabetes mellitus increases the risk of developing hepatocellular carcinoma (HCC). The aim of this study is to quantify the risk of HCC among patients with both diabetes mellitus and hepatitis C in a large cohort of patients with chronic hepatitis C and advanced fibrosis. We included 541 patients of whom 85 (16%) had diabetes mellitus. The median age at inclusion was 50 years. The prevalence of diabetes mellitus was 10.5% for patients with Ishak fibrosis score 4, 12.5% for Ishak score 5, and 19.1% for Ishak score 6. Multiple logistic regression analysis showed an increased risk of diabetes mellitus for patients with an elevated body mass index (BMI) (odds ratio [OR], 1.05; 95% confidence interval [CI], 1.00-1.11; P = 0.060) and a decreased risk of diabetes mellitus for patients with higher serum albumin levels (OR, 0.81; 95% CI, 0.63-1.04; P = 0.095). During a median follow-up of 4.0 years (interquartile range, 2.0-6.7), 11 patients (13%) with diabetes mellitus versus 27 patients (5.9%) without diabetes mellitus developed HCC, the 5-year occurrence of HCC being 11.4% (95% CI, 3.0-19.8) and 5.0% (95% CI, 2.2-7.8), respectively (P = 0.013). Multivariate Cox regression analysis of patients with Ishak 6 cirrhosis showed that diabetes mellitus was independently associated with the development of HCC (hazard ratio, 3.28; 95% CI, 1.35-7.97; P = 0.009). CONCLUSION: For patients with chronic hepatitis C and advanced cirrhosis, diabetes mellitus increases the risk of developing HCC.

[New insights into diagnosis and management of gestational diabetes mellitus: recommendations of the Swiss Society for Endocrinology and Diabetes]

Physiology and current knowledge about gestational diabetes which led to the adoption of new diagnostic criterias and blood glucose target levels during pregnancy by the Swiss Society for Endocrinology and Diabetes are reviewed. The 6th International Workshop Conference on Gestational Diabetes mellitus in Pasedena (2008) defined new diagnostic criteria based on the results of the HAPO-Trial. These criteria were during the ADA congress in New Orleans in 2009 presented. According to the new criteria there is no need for screening, but all pregnant women have to be tested with a 75 g oral glucose tolerance test between the 24th and 28th week of pregnancy. The new diagnostic values are very similar to the ones previously adopted by the ADA with the exception that only one out of three values has to be elevated in order to make the diagnosis of gestational diabetes. Due to this important difference it is very likely that gestational diabetes will be diagnosed more frequently in the future. The diagnostic criteria are: Fasting plasma glucose > or = 5.1 mmol/l, 1-hour value > or = 10.0 mmol/l or 2-hour value > or = 8.5 mmol/l. Based on current knowledge and randomized trials it is much more difficult to define glucose target levels during pregnancy. This difficulty has led to many different recommendations issued by diabetes societies. The Swiss Society of Endocrinology and Diabetes follows the arguments of the International Diabetes Federation (IDF) that self-blood glucose monitoring itself lacks precision and that there are very few randomized trials. Therefore, the target levels have to be easy to remember and might be slightly different in mmol/l or mg/dl. The Swiss Society for Endocrinology and Diabetes adopts the tentative target values of the IDF with fasting plasma glucose values < 5.3 mM and 1- and 2-hour postprandial (after the end of the meal) values of < 8.0 and 7.0 mmol/l, respectively. The last part of these recommendations deals with the therapeutic options during pregnancy (nutrition, physical exercise and pharmaceutical treatment). If despite lifestyle changes the target values are not met, approximately 25 % of patients have to be treated pharmaceutically. Insulin therapy is still the preferred treatment option, but metformin (and as an exception glibenclamide) can be used, if there are major hurdles for the initiation of insulin therapy.

Metabolic control in children and adolescents with diabetes mellitus type I in Berne: a cross-sectional study.

AIMS/HYPOTHESIS In diabetes mellitus type I, good glycaemic control is crucial in preventing long-term diabetic complications. The aim of this study was to determine the current level of metabolic control in children and adolescents in our diabetes outpatient clinic at the University Children's Hospital, Berne. Furthermore, the impact of different factors such as age, pubertal stage, sex, duration of diabetes and insulin regimen on glycaemic control was studied. METHODS In a cross-sectional, prospective study 168 children and adolescents with type I diabetes mellitus (f:m = 87:81; prepubertal 48 [mean age 4.4 years, mean duration of diabetes 2.8 years]; pubertal 120 [mean age 9.4 years; mean duration of diabetes 5.2 years]) were studied for three months. Clinical data and HbA1c levels (latex immunoagglutination test) were recorded, statistically analysed and compared with the international literature. RESULTS In our type I diabetic children and adolescents the overall HbA1c was 8.07 +/- 1.15% (mean +/- SD; test-specific norm for healthy subjects: 4.1-6.1%). Glycaemic control was significantly worse in the pubertal group compared to the prepubertal (HbA1c 8.22 +/- 1.25% vs. 7.81 +/- 0.87%; p < 0.01). In addition, we found better metabolic control in patients with duration of diabetes below 2 years in children and adolescents (HbA1c prepubertal < 2 years: 7.45 +/- 0.67% vs. > 2 years: 8.05 +/- 0.93%, p < 0.05; pubertal < 2 years: 7.62 +/- 0.75% vs. > 2 years: 8.31 +/- 1.29%, p < 0.005). Importantly, sex and insulin regimen did not significantly influence glycaemic control. CONCLUSION/INTERPRETATION The current level of metabolic control in our children and adolescents with diabetes mellitus type I is comparable to the glycaemic control of the intensively treated adolescent group of the DCCT-study, in whom decreased risk of long-term diabetic complications was found. In contrast, our patients were intensively treated in terms of frequent contacts with the diabetes team, but were not necessarily on an intensified insulin regimen. The impact of biopsychosocial support from multidisciplinary diabetes team on good metabolic control in children and adolescents with type I diabetes mellitus and their families seems to be very important.

Insulin increases serum leptin concentrations in children and adolescents with newly diagnosed type I diabetes mellitus with and without ketoacidosis.

AIMS/HYPOTHESIS The aims of this study were to analyse the changes of serum leptin in newly diagnosed children and adolescents with Type I (insulin-dependent) diabetes mellitus after insulin treatment and to examine the possible impact of ketoacidosis on these changes. METHODS Baseline serum leptin concentrations were measured in 28 newly diagnosed Type I diabetic patients [age 8.75 +/- 4.05 years (means +/- SD); BMI 15.79 +/- 2.47 kg/m(2); HbA(1 c) 11.3 +/- 1.9 %] with (n = 18) and without (n = 10) ketoacidosis before commencement of insulin treatment, at the time of diagnosis. Thereafter, during a 4-day course of continuous intravenous insulin injection to gain and maintain euglycaemia, serum leptin concentrations were assessed. RESULTS Baseline serum leptin concentrations, adjusted to age, BMI, sex and pubertal stage, differed among these patients. There was, however, an increase of leptin in all subjects from 1.37 +/- 0.56 ng/ml (mean +/- SD) up to 2.97 +/- 1.52 ng/ml by 117 % (p < 0.0001) after insulin therapy. On average, peak serum leptin concentration was obtained after 42 h of insulin treatment. Further, there was no difference in the mean increase of serum leptin concentrations in the two groups, namely with and without ketoadicosis, of insulin-dependent diabetic children and adolescents. In addition, there was no correlation between serum leptin concentrations and correction of ketoacidosis during insulin treatment. CONCLUSIONS/INTERPRETATION Insulin increases serum leptin, within 1 day, in children and adolescents with newly diagnosed Type I diabetes. Ketoacidosis does not influence this interaction between insulin and leptin.

Prevalence of vascular disease in systemic lupus erythematosus compared with type-1 diabetes mellitus: a cross-sectional study of two cohorts.

OBJECTIVES Systemic lupus erythematosus (SLE) is associated with considerable cardiovascular morbidity that has not yet been directly compared with other diseases with known cardiovascular risk. METHODS Two hundred and forty-one patients of the multicentre Swiss SLE cohort study (SSCS) were cross-sectionally assessed for coronary heart disease (CHD), cerebrovascular disease (CVD) and peripheral artery disease (PAD). SLE patients were compared with a cohort of 193 patients with type-1 diabetes mellitus being followed at the University Hospital Basel. A subgroup analysis of 50 age- and sex-matched patients from the University Hospital Basel was performed. RESULTS Of patients within the SSCS 13.3% had one or more vascular events: 8.3% CHD, 5% CVD and 1.2% PAD. In type-1 diabetes mellitus patients, 15% had vascular events: 9.3% CHD, 3.1% CVD and 5.6% PAD. In the matched subgroup, 26% of SLE patients had vascular events (14% CHD) compared with 12% in type-1 DM patients (2% CHD). Cardiovascular risk factors were similar in both groups. Vascular events in SLE patients were associated with age, longer disease duration, dyslipidaemia, and hypertension. CONCLUSION Cardiovascular morbidity in SLE is at least as frequent as in age- and sex-matched type-1 diabetes mellitus patients. Therefore, aggressive screening and management of cardiovascular risk factors should be performed.

Estimating the prevalence of comorbid conditions and their effect on health care costs in patients with diabetes mellitus in Switzerland.

BACKGROUND Estimating the prevalence of comorbidities and their associated costs in patients with diabetes is fundamental to optimizing health care management. This study assesses the prevalence and health care costs of comorbid conditions among patients with diabetes compared with patients without diabetes. Distinguishing potentially diabetes- and nondiabetes-related comorbidities in patients with diabetes, we also determined the most frequent chronic conditions and estimated their effect on costs across different health care settings in Switzerland. METHODS Using health care claims data from 2011, we calculated the prevalence and average health care costs of comorbidities among patients with and without diabetes in inpatient and outpatient settings. Patients with diabetes and comorbid conditions were identified using pharmacy-based cost groups. Generalized linear models with negative binomial distribution were used to analyze the effect of comorbidities on health care costs. RESULTS A total of 932,612 persons, including 50,751 patients with diabetes, were enrolled. The most frequent potentially diabetes- and nondiabetes-related comorbidities in patients older than 64 years were cardiovascular diseases (91%), rheumatologic conditions (55%), and hyperlipidemia (53%). The mean total health care costs for diabetes patients varied substantially by comorbidity status (US$3,203-$14,223). Patients with diabetes and more than two comorbidities incurred US$10,584 higher total costs than patients without comorbidity. Costs were significantly higher in patients with diabetes and comorbid cardiovascular disease (US$4,788), hyperlipidemia (US$2,163), hyperacidity disorders (US$8,753), and pain (US$8,324) compared with in those without the given disease. CONCLUSION Comorbidities in patients with diabetes are highly prevalent and have substantial consequences for medical expenditures. Interestingly, hyperacidity disorders and pain were the most costly conditions. Our findings highlight the importance of developing strategies that meet the needs of patients with diabetes and comorbidities. Integrated diabetes care such as used in the Chronic Care Model may represent a useful strategy.

GoCARB: Smartphone-App zur Kohlenhydratberechnung bei Typ-1-Diabetes

Smartphone-App zur Kohlenhydratberechnung Neue Technologien wie Blutzuckersensoren und moderne Insulinpumpen prägten die Therapie des Typ-1-Diabetes (T1D) in den letzten Jahren in wesentlichem Ausmaß. Smartphones sind aufgrund ihrer rasanten technischen Entwicklung eine weitere Plattform für Applikationen zur Therapieunterstützung bei T1D. GoCARB Hierbei handelt es sich um ein zur Kohlenhydratberechnung entwickeltes System für Personen mit T1D. Die Basis für Endanwender stellt ein Smartphone mit Kamera dar. Zur Berechnung werden 2 mit dem Smartphone aus verschiedenen Winkeln aufgenommene Fotografien einer auf einem Teller angerichteten Mahlzeit benötigt. Zusätzlich ist eine neben dem Teller platzierte Referenzkarte erforderlich. Die Grundlage für die Kohlenhydratberechnung ist ein Computer-Vision-gestütztes Programm, das die Mahlzeiten aufgrund ihrer Farbe und Textur erkennt. Das Volumen der Mahlzeit wird mit Hilfe eines dreidimensional errechneten Modells bestimmt. Durch das Erkennen der Art der Mahlzeiten sowie deren Volumen kann GoCARB den Kohlenhydratanteil unter Einbeziehung von Nährwerttabellen berechnen. Für die Entwicklung des Systems wurde eine Bilddatenbank von mehr als 5000 Mahlzeiten erstellt und genutzt. Resümee Das GoCARB-System befindet sich aktuell in klinischer Evaluierung und ist noch nicht für Patienten verfügbar.

Carbohydrate Estimation by a Mobile Phone-Based System Versus Self-Estimations of Individuals With Type 1 Diabetes Mellitus: A Comparative Study

Background: Diabetes mellitus is spreading throughout the world and diabetic individuals have been shown to often assess their food intake inaccurately; therefore, it is a matter of urgency to develop automated diet assessment tools. The recent availability of mobile phones with enhanced capabilities, together with the advances in computer vision, have permitted the development of image analysis apps for the automated assessment of meals. GoCARB is a mobile phone-based system designed to support individuals with type 1 diabetes during daily carbohydrate estimation. In a typical scenario, the user places a reference card next to the dish and acquires two images using a mobile phone. A series of computer vision modules detect the plate and automatically segment and recognize the different food items, while their 3D shape is reconstructed. Finally, the carbohydrate content is calculated by combining the volume of each food item with the nutritional information provided by the USDA Nutrient Database for Standard Reference. Objective: The main objective of this study is to assess the accuracy of the GoCARB prototype when used by individuals with type 1 diabetes and to compare it to their own performance in carbohydrate counting. In addition, the user experience and usability of the system is evaluated by questionnaires. Methods: The study was conducted at the Bern University Hospital, “Inselspital” (Bern, Switzerland) and involved 19 adult volunteers with type 1 diabetes, each participating once. Each study day, a total of six meals of broad diversity were taken from the hospital’s restaurant and presented to the participants. The food items were weighed on a standard balance and the true amount of carbohydrate was calculated from the USDA nutrient database. Participants were asked to count the carbohydrate content of each meal independently and then by using GoCARB. At the end of each session, a questionnaire was completed to assess the user’s experience with GoCARB. Results: The mean absolute error was 27.89 (SD 38.20) grams of carbohydrate for the estimation of participants, whereas the corresponding value for the GoCARB system was 12.28 (SD 9.56) grams of carbohydrate, which was a significantly better performance ( P=.001). In 75.4% (86/114) of the meals, the GoCARB automatic segmentation was successful and 85.1% (291/342) of individual food items were successfully recognized. Most participants found GoCARB easy to use. Conclusions: This study indicates that the system is able to estimate, on average, the carbohydrate content of meals with higher accuracy than individuals with type 1 diabetes can. The participants thought the app was useful and easy to use. GoCARB seems to be a well-accepted supportive mHealth tool for the assessment of served-on-a-plate meals.

Does diabetes mellitus contribute to the disease burden of vascular dementia?

Background. Vascular dementia (VaD) is the second most common of dementia. Multiple risk factors are associated with VaD, but the individual contribution of each to disease onset and progression is unclear. We examined the relationship between diabetes mellitus type 2 (DM) and the clinical variables of VaD.^ Methods. Data from 593 patients evaluated between June, 2003 and June, 2008 for cognitive impairment were prospectively entered into a database. We retrospectively reviewed the charts of 63 patients who fit the NINDS-AIREN criteria of VaD. The patients were divided into those with DM (VaD-DM, n=29) and those without DM (VaD, n=34). The groups were compared with regard to multiple variables.^ Results. Patients with DM had a significantly earlier onset of VaD (71.9±6.54 vs. 77.2±6.03, p<0.001), a faster rate of decline per year on the mini mental state examination (MMSE; 3.60±1.82 vs. 2.54±1.60 points, p=0.02), and a greater prevalence of neuropsychiatric symptoms (62% vs. 21%, p=0.02) at the time of diagnosis.^ Conclusions. This study shows that a history of pre-morbid DM is associated with an early onset and faster cognitive deterioration in VaD. Moreover, the presence of DM predicts the presence of neuropsychiatric symptoms in patients with VaD. A larger study is needed to verify these associations. It will be important to investigate whether better glycemic control will mitigate the potential effects of DM on VaD.^

Macular edema in Hispanics with non-insulin dependent diabetes mellitus in Starr County, Texas: Prevalence, incidence and risk factors

This project is based on secondary analyses of data collected in Starr County, Texas from 1981 till 1991 to determine the prevalence, incidence and risk factors for macular edema in Hispanics with non-insulin-dependent diabetes in Starr County, Texas. Two studies were conducted. The first study examined the prevalence of macular edema in this population. Of the 310 diabetics that were included in the study 22 had macular edema. Of these 22 individuals 9 had clinically significant macular edema. Fasting blood glucose was found to be significantly associated with macular edema. For each 10 mg/dl increase in fasting blood glucose there was a 1.07 probability of an increase in the risk of having macular edema. Individuals with fasting blood glucose $\ge$200 mg/dl were found to be more than three times at risk of having macular edema compared to those with fasting blood glucose $<$200 mg/dl.^ In the second study the incidence and the risk factors that could cause macular edema in this Hispanic population were examined. 240 Hispanics with non-insulin-dependent diabetes mellitus and without macular edema were followed for 1223 person-years. During the follow-up period 27 individuals developed macular edema (2.21/100 person-years). High fasting blood glucose and glycosylated hemoglobin were found to be strong and independent risk factors for macular edema. Participants taking insulin were 3.9 times more at risk of developing macular edema compared to those not taking insulin. Systolic blood pressure was significantly related to macular edema, where each 10 mmHg increase in systolic blood pressure was associated with a 1.3 increase in the risk of macular edema.^ In summary, this study suggests that hyperglycemia is the main underlying factor for retinal pathological changes in this diabetic population, and that macular edema probably is not the result of sudden change in the blood glucose level. It also determined that changes in blood pressure, particularly systolic blood pressure, could trigger the development of macular edema.^ Based on the prevalence reported in this study, it is estimated that 35,500 Hispanic diabetics in the US have macular edema. This imposes a major public health challenge particularly in areas with high concentration of Mexican Americans. It also highlights the importance of public health measures directed to Mexican Americans such as health education, improved access to medical care, and periodic and careful ophthalmologic examination by ophthalmologists knowledgeable and experienced in the management of diabetic macular edema. ^

Will new diagnostic criteria for diabetes mellitus change phenotype of patients with diabetes? Reanalysis of European epidemiological data

Objective: To evaluate the impact of the revised diagnostic criteria for diabetes mellitus adopted by the American Diabetes Association on prevalence of diabetes and on classification of patients. For epidemiological purposes the American criteria use a fasting plasma glucose concentration ⩾7.0 mmol/l in contrast with the current World Health Organisation criteria of 2 hour glucose concentration ⩾11.1 mmol/l.