Physician's adherence to the standard protocol for diabetes treatment in Brooke Army Medical Center (BAMC)

The level of compliance with clinical practice guidelines for patients with Type II Diabetes Mellitus was evaluated in 157 patients treated at BAMC from 1 January 2006 to 1 January 2007. This retrospective analysis was conducted reviewing data from medical records and following the VA/DOD protocols that health care providers are expected to follow at this facility. Data collected included patient’s age and gender, presence or absence of complications of diabetes, physical examination findings, glycemic and lipid control, eye care, foot care, kidney function, and self-management and education. Subjects were selected performing systematic random sampling, and included both male and female patients, from a variety of ages and ethnic groups. The Diabetes complications screened for included glycemic and lipid complications, retinopathy, cardiovascular complications, peripheral circulation complications, and nephropathy. The results revealed that 19.10% had no complications and that the most common complications were: cardiovascular (49.68%), glycemic and lipid control (10.82%), retinopathy and peripheral circulation (8.28% each), and nephropathy (2.54%). Only 2.54% of the records reviewed did not include information on complications. Strictly following the Department of Defense guidelines, six treatment modules were evaluated independently and together to get a final percentage of adherence to the clinical practice guidelines. It was established that the level of adherence was going to be graded as follows: Extremely deficient: 0-15%; very poor: 16-30%; Poor and in need of improvement: 31-45%. Acceptable: 46-60%; Good: 61-80%, and Excellent: 81-100%. The results indicated that the percentage of physicians' adherence to each protocol was as follows: 88.31%, 89.93%, 90.63%, 89.42%, 89.42% and 89.64%. When the results were pooled, the level of adherence to the clinical practice guidelines was 89.55%, proving my hypothesis that Brooke Army Medical Center physicians have excellent adherence to the standard protocols for Diabetes Type II to treat their patients. ^

Factors associated with diabetes in tuberculosis patients in Harris County, Texas 1995--2004

Objective. To determine the prevalence and factors associated with diabetes in tuberculosis patients in Harris County, Texas. ^ Background. Tuberculosis and diabetes mellitus are two diseases of immense public health significance. Various epidemiologic studies have established an association between the two conditions. While many studies have identified factors associated with the conditions individually, few have looked at factors associated with their co-occurrence particularly in the United States. Furthermore, most of those studies are hospital-based and may not be representative of the population. The aim of this study was to determine the prevalence and distribution of diabetes among tuberculosis patients in Harris County, Texas and to identify the factors associated with diabetes in tuberculosis. ^ Methods. A population-based case control study was performed using secondary data from the Houston Tuberculosis Initiative (HTI) collected from October 1995 to September 2004. Socio-demographic characteristics and clinical variables were compared between tuberculosis patients with diabetes and non-diabetic tuberculosis patients. Logistic regression analysis was performed to identify associations. Survival at 180 days post tuberculosis diagnosis was assessed by Cox regression. ^ Results. The prevalence of diabetes among the tuberculosis (TB) population was 14.4%. The diabetics (cases) with a mean age 53 ± 13.3 years were older than the non-diabetics (controls) with a mean age of 39 ± 18.5 years (p<0.001). Socio-demographic variables that were independently associated with the risk of diabetes were age (OR 1.04, p<0.001) and Hispanic ethnicity (OR 2.04, p<0.001). Diabetes was associated with an increased risk of pulmonary tuberculosis disease (OR 1.33, p<0.028). Among individuals with pulmonary TB, diabetes was associated with positive sputum acid-fast bacilli (AFB) smear (OR 1.47, p<0.005) and culture (OR 1.83, p<0.018). Diabetics were more likely to have cavitary lung disease than non-diabetics (OR 1.50, p<0.002). After adjustment for age and HIV status, the risk of dying within 180 days of TB diagnosis was significantly increased in the diabetics (HR 1.51, p<0.002). ^ Conclusion. Diabetes mellitus was more prevalent in our tuberculosis patients than in the general population. The tuberculous diabetic may be more infectious and has a higher risk of death. It is therefore imperative to screen diabetics for TB and TB patients for diabetes. ^

The association between diabetes and hepatitis C: A systematic review of epidemiological evidence

Background. Several studies have proposed a link between type 2 Diabetes mellitus (DM2) and Hepatitis C infection (HCV) with conflicting results. Since DM2 and HCV have high prevalence, establishing a link between the two may guide further studies aimed at DM2 prevention. A systematic review was conducted to estimate the magnitude and direction of association between DM2 and HCV. Temporality was assessed from cohort studies and case-control studies where such information was available. ^ Methods. MEDLINE searches were conducted for studies that provided risk estimates and fulfill criteria regarding the definition of exposure (HCV) and outcomes (DM2). HCV was defined in terms of method of diagnosis, laboratory technique and method of data collection; DM2 was defined in terms of the classification [World Health Organization (WHO) and American Diabetes Association (ADA)] 1-3 used for diagnosis, laboratory technique and method of data collection. Standardized searches and data abstraction for construction of tables was performed. Unadjusted or adjusted measures of association for individual studies were obtained or calculated from the full text of the studies. Template designed by Dr. David Ramsey. ^ Results. Forty-six studies out of one hundred and nine potentially eligible articles finally met the inclusion and exclusion criteria and were classified separately based on the study design as cross-sectional (twenty four), case-control (fifteen) or cohort studies (seven). The cohort studies showed a three-fold high (confidence interval 1.66–6.29) occurrence of DM2 in individuals with HCV compared to those who were unexposed to HCV and cross sectional studies had a summary odds ratio of 2.53 (1.96, 3.25). In case control studies, the summary odds ratio for studies done in subjects with DM2 was 3.61 (1.93, 6.74); in HCV, it was 2.30 (1.56, 3.38); and all fifteen studies, together, yielded an odds ratio of 2.60 (1.82, 3.73). ^ Conclusion. The above results support the hypothesis that there is an association between DM and HCV. The temporal relationship evident from cohort studies and proposed pathogenic mechanisms also suggest that HCV predisposes patients to development of DM2. Further cohort or prospective studies are needed, however, to determine whether treatment of HCV infections prevents development of DM2.^

Burden of diabetes in cancer inpatients

Inpatient hyperglycemia has been shown to be associated with higher morbidity and mortality. Treatment of inpatient hyperglycemia reduces morbidity and mortality at least in the intensive care unit. Burden and severity of hyperglycemia in an inpatient population of a cancer center is not known. The study is a secondary analysis of the primary study 'Prevalence of Diabetes in cancer inpatient'. Finger-stick glucose concentration and pharmacy data were collected prospectively for all hospitalizations to a large cancer center. Demographic, clinical and laboratory data were collected in a retrospective fashion. Between May 1 and July 31, 2006; 3,940 patients were admitted 5,489 times. Prior to their first admissions, 920(23.4%) of the 3940 patients had unrecognized or recognized hyperglycemia. Glucose was never tested during 1714 (31.8%) hospitalizations, including 170 (12%) of the 1414 admissions of the 920 patients with previous hyperglycemia, and, 109 (58%) of 188 patients who were not tested for glucose prior to their index admissions. Overall, sustained significant hyperglycemia (>= 200 mg/dL on two separate days) was present in 765 (13.9%). Antidiabetic treatment was dispensed in 1168 (21.3%), though 627 (53.7%) of these received only short/rapid acting insulin, and, 951 (17.3%)diabetes code before and in another 80 (1.5%) during stay in hospital, out of total 5489 admissions. Therefore diabetes mellitus or hyperglycemia affected 1525 (27.8%) out of all admissions and coding alone as a criterion for diagnosis of hyperglycemia would have underreported it by 32%. Hyperglycemia occurred more commonly during hospitalization of patients with older age, males, ethnic minorities, advanced malignancies, and those receiving glucocorticoids, parenteral nutrition, and those who had a past history of coding for diabetes or past hyperglycemia, but not in those with the cancers reported to be associated with diabetes mellitus. Of the recognized diabetics half had sustained significant hyperglycemia and 10% had three quarters glucoses tested above 180 mg/dL. To conclude, diabetes affects at least 27.8% of inpatients at our cancer center. Coding for diabetes significantly underreports the burden of the disease. Significant sustained hyperglycemia of >=200 mg/dL among inpatients at a cancer center is common, under-recognized, and either untreated or inadequately treated with suboptimal glycemic control. The implications of hyperglycemia in cancer inpatient populations need further investigations. Fasting serum or plasma glucose should be checked routinely for every patient admitted to a cancer hospital, to recognize and treat hyperglycemia as clinically appropriate.^

Concordance between medical records and personal interview in ascertaining breast cancer and diabetes status: Analysis of the south Texas women's health project

Accurate ascertainment of risk factors and disease status is vital in public health research for proper classification of research subjects. The two most common ways of obtaining this data is by self-report and review of medical records (MRs). South Texas Women’s Health Project was a case-control study looking at interrelationships between hormones, diet, and body size and breast cancer among Hispanic women 30-79 years of age. History of breast cancer, diabetes mellitus (DM) and use of DM medications was ascertained from a personal interview. At the time of interview, the subject identified her major health care providers and signed the medical records release form, which was sent to the designated providers. The MRs were reviewed to confirm information obtained from the interview.^ Aim of this study was to determine the sensitivity and specificity between MRs and personal interview in diagnosis of breast cancer, DM and DM treatment. We also wanted to assess how successful our low-cost approach was in obtaining pertinent MRs and what factors influenced the quality of MR or interview data. Study sample was 721 women with both self-report and MR data available by June 2007. Overall response rate for MR requests was 74.5%. MRs were 80.9% sensitive and 100% specific in confirming breast cancer status. Prevalence of DM was 22.7% from the interviews and 16% from MRs. MRs did not provide definite information about DM status of 53.6% subjects. Sensitivity and specificity of MRs for DM status was 88.9% and 90.4% respectively. Disagreement on DM status from the two sources was seen in 15.9% subjects. This discordance was more common among older subjects, those who were married and were predominantly Spanish speaking. Income and level of education did not have a statistically significantly association with this disagreement.^ Both self-report and MRs underestimate the prevalence of DM. Relying solely on MRs leads to greater misclassification than relying on self-report data. MRs have good to excellent specificity and thus serve as a good tool to confirm information obtained from self-report. Self-report and MRs should be used in a complementary manner for accurate assessment of DM and breast cancer status.^

A case-control study of the risk factors for eclampsia

Objective. To study the risk factors for eclampsia, a rare but significant complication of pregnancy.^ Target population. All deliveries at or after the 20th week of gestation that took place between January 1, 1977 and March 1992, and between January 1990 and April 1992 at two hospitals in Houston, Texas, respectively.^ Study population. Sixty-six confirmed cases of eclampsia, and 2 groups of randomly selected controls: Non-preeclamptic and preeclamptic deliveries matched to cases on hospital and month of delivery on a 1:4 ratio.^ Exclusions. Women with chronic hypertension, gestational epilepsy, a previous history of epilepsy, and convulsions attributed to encephalitis, meningitis, cerebral tumor, and intracerebral bleeding, and women without a definite diagnosis of preeclampsia/eclampsia.^ Results. Eclampsia developed in 0.52-0.93/1000 deliveries. Fifty-six percent of seizures occurred in the antepartum period, 2% as early as 20 weeks of gestation and 39% between 37 and 42 weeks. Twenty-nine percent and 15% occurred in the postpartum and late postpartum periods, respectively, 8% as late as one week postpartum. A different set of risk factors was involved in the development of eclampsia in non-preeclamptic women than in the progression from preeclampsia to eclampsia. Factors involved in the development of eclampsia included, in addition to twin pregnancy and family history of pregnancy-induced hypertension, fewer than 3 prenatal care visits, urinary tract infections, primigravidity, obesity, black ethnicity, diabetes mellitus, and age $\le$20 years. Risk factors involved in the progression from preeclampsia to eclampsia included fewer than 3 of prenatal care visits, and age $\le$20 years. Protective factors were magnesium sulfate administration prior to seizure, history of abortions and longer gestational age. Having less than 3 prenatal care visits and being less than or equal to 20 years of age were predictors of eclampsia, whether of its development or progression from preeclampsia. Once preeclampsia is diagnosed, primigravid, diabetic, black, or obese women and those with urinary tract infections did not appear to exhibit any increased risk for the progression to eclampsia. The administration of magnesium sulfate was especially protective, followed by a positive history of abortions, 3 or more prenatal care visits, and longer gestational age. The protective effect of MgSO$\sb4$ was only slightly diminished when cases were restricted to the 65% who had a diagnosis of preeclampsia. The progression from preeclampsia to eclampsia may be largely preventable through adequate prenatal care and presumably the administration of magnesium sulfate. (Abstract shortened by UMI.) ^

Artificial pancreas using a personalized rule-based controller achieves overnight normoglycemia in patients with type 1 diabetes

Objective: This study assessed the efficacy of a closed-loop (CL) system consisting of a predictive rule-based algorithm (pRBA) on achieving nocturnal and postprandial normoglycemia in patients with type 1 diabetes mellitus (T1DM). The algorithm is personalized for each patient’s data using two different strategies to control nocturnal and postprandial periods. Research Design and Methods: We performed a randomized crossover clinical study in which 10 T1DM patients treated with continuous subcutaneous insulin infusion (CSII) spent two nonconsecutive nights in the research facility: one with their usual CSII pattern (open-loop [OL]) and one controlled by the pRBA (CL). The CL period lasted from 10 p.m. to 10 a.m., including overnight control, and control of breakfast. Venous samples for blood glucose (BG) measurement were collected every 20 min. Results: Time spent in normoglycemia (BG, 3.9–8.0 mmol/L) during the nocturnal period (12 a.m.–8 a.m.), expressed as median (interquartile range), increased from 66.6% (8.3–75%) with OL to 95.8% (73–100%) using the CL algorithm (P<0.05). Median time in hypoglycemia (BG, <3.9 mmol/L) was reduced from 4.2% (0–21%) in the OL night to 0.0% (0.0–0.0%) in the CL night (P<0.05). Nine hypoglycemic events (<3.9 mmol/L) were recorded with OL compared with one using CL. The postprandial glycemic excursion was not lower when the CL system was used in comparison with conventional preprandial bolus: time in target (3.9–10.0 mmol/L) 58.3% (29.1–87.5%) versus 50.0% (50–100%). Conclusions: A highly precise personalized pRBA obtains nocturnal normoglycemia, without significant hypoglycemia, in T1DM patients. There appears to be no clear benefit of CL over prandial bolus on the postprandial glycemia

Glucose-Insulin regulator for type 1 diabetes using high order neural networks

In this paper a Glucose-Insulin regulator for Type 1 Diabetes using artificial neural networks (ANN) is proposed. This is done using a discrete recurrent high order neural network in order to identify and control a nonlinear dynamical system which represents the pancreas? beta-cells behavior of a virtual patient. The ANN which reproduces and identifies the dynamical behavior system, is configured as series parallel and trained on line using the extended Kalman filter algorithm to achieve a quickly convergence identification in silico. The control objective is to regulate the glucose-insulin level under different glucose inputs and is based on a nonlinear neural block control law. A safety block is included between the control output signal and the virtual patient with type 1 diabetes mellitus. Simulations include a period of three days. Simulation results are compared during the overnight fasting period in Open-Loop (OL) versus Closed- Loop (CL). Tests in Semi-Closed-Loop (SCL) are made feedforward in order to give information to the control algorithm. We conclude the controller is able to drive the glucose to target in overnight periods and the feedforward is necessary to control the postprandial period.

Extracción de conocimientos de la diabetes tipo 1 utilizando la metodología de "Data Mining"

La diabetes mellitus es un trastorno en la metabolización de los carbohidratos, caracterizado por la nula o insuficiente segregación de insulina (hormona producida por el páncreas), como resultado del mal funcionamiento de la parte endocrina del páncreas, o de una creciente resistencia del organismo a esta hormona. Esto implica, que tras el proceso digestivo, los alimentos que ingerimos se transforman en otros compuestos químicos más pequeños mediante los tejidos exocrinos. La ausencia o poca efectividad de esta hormona polipéptida, no permite metabolizar los carbohidratos ingeridos provocando dos consecuencias: Aumento de la concentración de glucosa en sangre, ya que las células no pueden metabolizarla; consumo de ácidos grasos mediante el hígado, liberando cuerpos cetónicos para aportar la energía a las células. Esta situación expone al enfermo crónico, a una concentración de glucosa en sangre muy elevada, denominado hiperglucemia, la cual puede producir a medio o largo múltiples problemas médicos: oftalmológicos, renales, cardiovasculares, cerebrovasculares, neurológicos… La diabetes representa un gran problema de salud pública y es la enfermedad más común en los países desarrollados por varios factores como la obesidad, la vida sedentaria, que facilitan la aparición de esta enfermedad. Mediante el presente proyecto trabajaremos con los datos de experimentación clínica de pacientes con diabetes de tipo 1, enfermedad autoinmune en la que son destruidas las células beta del páncreas (productoras de insulina) resultando necesaria la administración de insulina exógena. Dicho esto, el paciente con diabetes tipo 1 deberá seguir un tratamiento con insulina administrada por la vía subcutánea, adaptado a sus necesidades metabólicas y a sus hábitos de vida. Para abordar esta situación de regulación del control metabólico del enfermo, mediante una terapia de insulina, no serviremos del proyecto “Páncreas Endocrino Artificial” (PEA), el cual consta de una bomba de infusión de insulina, un sensor continuo de glucosa, y un algoritmo de control en lazo cerrado. El objetivo principal del PEA es aportar al paciente precisión, eficacia y seguridad en cuanto a la normalización del control glucémico y reducción del riesgo de hipoglucemias. El PEA se instala mediante vía subcutánea, por lo que, el retardo introducido por la acción de la insulina, el retardo de la medida de glucosa, así como los errores introducidos por los sensores continuos de glucosa cuando, se descalibran dificultando el empleo de un algoritmo de control. Llegados a este punto debemos modelar la glucosa del paciente mediante sistemas predictivos. Un modelo, es todo aquel elemento que nos permita predecir el comportamiento de un sistema mediante la introducción de variables de entrada. De este modo lo que conseguimos, es una predicción de los estados futuros en los que se puede encontrar la glucosa del paciente, sirviéndonos de variables de entrada de insulina, ingesta y glucosa ya conocidas, por ser las sucedidas con anterioridad en el tiempo. Cuando empleamos el predictor de glucosa, utilizando parámetros obtenidos en tiempo real, el controlador es capaz de indicar el nivel futuro de la glucosa para la toma de decisones del controlador CL. Los predictores que se están empleando actualmente en el PEA no están funcionando correctamente por la cantidad de información y variables que debe de manejar. Data Mining, también referenciado como Descubrimiento del Conocimiento en Bases de Datos (Knowledge Discovery in Databases o KDD), ha sido definida como el proceso de extracción no trivial de información implícita, previamente desconocida y potencialmente útil. Todo ello, sirviéndonos las siguientes fases del proceso de extracción del conocimiento: selección de datos, pre-procesado, transformación, minería de datos, interpretación de los resultados, evaluación y obtención del conocimiento. Con todo este proceso buscamos generar un único modelo insulina glucosa que se ajuste de forma individual a cada paciente y sea capaz, al mismo tiempo, de predecir los estados futuros glucosa con cálculos en tiempo real, a través de unos parámetros introducidos. Este trabajo busca extraer la información contenida en una base de datos de pacientes diabéticos tipo 1 obtenidos a partir de la experimentación clínica. Para ello emplearemos técnicas de Data Mining. Para la consecución del objetivo implícito a este proyecto hemos procedido a implementar una interfaz gráfica que nos guía a través del proceso del KDD (con información gráfica y estadística) de cada punto del proceso. En lo que respecta a la parte de la minería de datos, nos hemos servido de la denominada herramienta de WEKA, en la que a través de Java controlamos todas sus funciones, para implementarlas por medio del programa creado. Otorgando finalmente, una mayor potencialidad al proyecto con la posibilidad de implementar el servicio de los dispositivos Android por la potencial capacidad de portar el código. Mediante estos dispositivos y lo expuesto en el proyecto se podrían implementar o incluso crear nuevas aplicaciones novedosas y muy útiles para este campo. Como conclusión del proyecto, y tras un exhaustivo análisis de los resultados obtenidos, podemos apreciar como logramos obtener el modelo insulina-glucosa de cada paciente. ABSTRACT. The diabetes mellitus is a metabolic disorder, characterized by the low or none insulin production (a hormone produced by the pancreas), as a result of the malfunctioning of the endocrine pancreas part or by an increasing resistance of the organism to this hormone. This implies that, after the digestive process, the food we consume is transformed into smaller chemical compounds, through the exocrine tissues. The absence or limited effectiveness of this polypeptide hormone, does not allow to metabolize the ingested carbohydrates provoking two consequences: Increase of the glucose concentration in blood, as the cells are unable to metabolize it; fatty acid intake through the liver, releasing ketone bodies to provide energy to the cells. This situation exposes the chronic patient to high blood glucose levels, named hyperglycemia, which may cause in the medium or long term multiple medical problems: ophthalmological, renal, cardiovascular, cerebrum-vascular, neurological … The diabetes represents a great public health problem and is the most common disease in the developed countries, by several factors such as the obesity or sedentary life, which facilitate the appearance of this disease. Through this project we will work with clinical experimentation data of patients with diabetes of type 1, autoimmune disease in which beta cells of the pancreas (producers of insulin) are destroyed resulting necessary the exogenous insulin administration. That said, the patient with diabetes type 1 will have to follow a treatment with insulin, administered by the subcutaneous route, adapted to his metabolic needs and to his life habits. To deal with this situation of metabolic control regulation of the patient, through an insulin therapy, we shall be using the “Endocrine Artificial Pancreas " (PEA), which consists of a bomb of insulin infusion, a constant glucose sensor, and a control algorithm in closed bow. The principal aim of the PEA is providing the patient precision, efficiency and safety regarding the normalization of the glycemic control and hypoglycemia risk reduction". The PEA establishes through subcutaneous route, consequently, the delay introduced by the insulin action, the delay of the glucose measure, as well as the mistakes introduced by the constant glucose sensors when, decalibrate, impede the employment of an algorithm of control. At this stage we must shape the patient glucose levels through predictive systems. A model is all that element or set of elements which will allow us to predict the behavior of a system by introducing input variables. Thus what we obtain, is a prediction of the future stages in which it is possible to find the patient glucose level, being served of input insulin, ingestion and glucose variables already known, for being the ones happened previously in the time. When we use the glucose predictor, using obtained real time parameters, the controller is capable of indicating the future level of the glucose for the decision capture CL controller. The predictors that are being used nowadays in the PEA are not working correctly for the amount of information and variables that it need to handle. Data Mining, also indexed as Knowledge Discovery in Databases or KDD, has been defined as the not trivial extraction process of implicit information, previously unknown and potentially useful. All this, using the following phases of the knowledge extraction process: selection of information, pre- processing, transformation, data mining, results interpretation, evaluation and knowledge acquisition. With all this process we seek to generate the unique insulin glucose model that adjusts individually and in a personalized way for each patient form and being capable, at the same time, of predicting the future conditions with real time calculations, across few input parameters. This project of end of grade seeks to extract the information contained in a database of type 1 diabetics patients, obtained from clinical experimentation. For it, we will use technologies of Data Mining. For the attainment of the aim implicit to this project we have proceeded to implement a graphical interface that will guide us across the process of the KDD (with graphical and statistical information) of every point of the process. Regarding the data mining part, we have been served by a tool called WEKA's tool called, in which across Java, we control all of its functions to implement them by means of the created program. Finally granting a higher potential to the project with the possibility of implementing the service for Android devices, porting the code. Through these devices and what has been exposed in the project they might help or even create new and very useful applications for this field. As a conclusion of the project, and after an exhaustive analysis of the obtained results, we can show how we achieve to obtain the insulin–glucose model for each patient.

Mechanisms of β cell death in diabetes: A minor role for CD95

Insulin-dependent diabetes mellitus is an autoimmune disease, under polygenic control, manifested only when >90% of the insulin-producing β cells are destroyed. Although the disease is T cell mediated, the demise of the β cell results from a number of different insults from the immune system. It has been proposed that foremost amongst these effector mechanisms is CD95 ligand-induced β cell death. Using the nonobese diabetic lpr mouse as a model system, we have found, to the contrary, that CD95 plays only a minor role in the death of β cells. Islet grafts from nonobese diabetic mice that carry the lpr mutation and therefore lack CD95 were protected only marginally from immune attack when grafted into diabetic mice. An explanation to reconcile these differing results is provided.

Correction of obesity and diabetes in genetically obese mice by leptin gene therapy

The ob/ob mouse is genetically deficient in leptin and exhibits both an obese and a mild non-insulin-dependent diabetic phenotype. To test the hypothesis that correction of the obese phenotype by leptin gene therapy will lead to the spontaneous correction of the diabetic phenotype, the ob/ob mouse was treated with a recombinant adenovirus expressing the mouse leptin cDNA. Treatment resulted in dramatic reductions in both food intake and body weight, as well as the normalization of serum insulin levels and glucose tolerance. The subsequent diminishment in serum leptin levels resulted in the rapid resumption of food intake and a gradual gain of body weight, which correlated with the gradual return of hyperinsulinemia and insulin resistance. These results not only demonstrated that the obese and diabetic phenotypes in the adult ob/ob mice are corrected by leptin gene treatment but also provide confirming evidence that body weight control may be critical in the long-term management of non-insulin-dependent diabetes mellitus in obese patients.

The outcome in Australian children with hyperinsulinism of infancy: early extensive surgery in severe cases lowers risk of diabetes

AIMS Hyperinsulinism of infancy (HI) is characterized by unregulated insulin secretion in the presence of hypoglycaemia, often resulting in brain damage. Pancreatic resection for control of hypoglycaemia is frequently resisted because of the risk of diabetes mellitus (DM). We investigated retrospectively 62 children with HI from nine Australian treatment centres born between 1972 and 1998, comparing endocrine and neurological outcome in 28 patients receiving medical therapy alone with 34 who required pancreatic resection to control their hypoglycaemia. METHODS History, treatment and clinical course were ascertained from file audit and interview. Risk of DM (hazard ratio) attributable to age at surgery (< vs. greater than or equal to 100 days at last pancreatectomy) and extent of resection (< vs. greater than or equal to 95%) were calculated using Cox proportional hazards regression and categorical variables compared by the chi(2) -test. Neurological outcome (normal, mild deficit or severe deficit) was derived from the most authoritative source. RESULTS Surgically treated patients had a greater birthweight, earlier presentation and higher plasma insulin levels. Of 18 infants < 100 days and 16 greater than or equal to 100 days of age at surgery, four (all greater than or equal to 100 days) became diabetic as an immediate consequence of surgery and five (two < 100 days and three greater than or equal to 100 days) became diabetic 7-18 years later. Surgery greater than or equal to 100 days and pancreatectomy greater than or equal to 95% were associated with development of diabetes (HR = 12.61, CI 1.53-104.07 and HR = 7.03, CI 1.43-34.58, respectively). Neurodevelopmental outcome was no different between the surgical and medical groups with 44% overall with neurological deficits. Patients euglycaemic within 35 days of the first symptom of hypoglycaemia (Group A) had a better neurodevelopmental outcome than those still hypoglycaemic > 35 days from first presentation (Group B) (P = 0.007). Prolonged hypoglycaemia in Group B was due either to delayed diagnosis or to need for repeat surgery because of continued hypoglycaemia. Within Group A, medically treated patients (who presented later with apparently milder disease) had a higher incidence of neurodevelopmental deficit (n = 15, four mild, three severe deficit) compared with surgically treated patients (n = 18, two mild, none severe deficit) (P < 0.025). CONCLUSIONS Poor neurodevelopmental outcome remains a major problem in hyperinsulinism of infancy. Risk of diabetes mellitus with pancreatectomy varies according to age at surgery and extent of resection. Patients presenting early with severe disease have a better neurodevelopmental outcome and lower risk of diabetes if they are treated with early extensive surgery.

Left ventricular mass in patients with type 2 diabetes is independently associated with central but not peripheral pulse pressure

An increase in left ventricular mass (LVM) occurs in the presence of type 2 diabetes, apparently independent of hypertension (1), but the determinants of this process are unknown. Brachial blood pressure is not representative of that at the ascending aorta (2) because the pressure wave is amplified from central to peripheral arteries. Central blood pressure is probably more clinically important since local pulsatile pressure determines adverse arterial and myocardial remodeling (3,4). Thus, an inaccurate assessment of the contribution of arterial blood pressure to LVM may occur if only brachial blood pressure is taken into consideration. In this study we sought the contribution of central blood pressure (and other interactive factors known to affect wave reflection, e.g., glycemic control and total arterial compliance) to LVM in patients with type 2 diabetes.

Increased C282Y heterozygosity in gestational diabetes

Background. Hereditary hemochromatosis is an autosomal recessive disorder of iron metabolism that is characterized by excess accumulation of iron in various organs and often leads to diabetes mellitus (DM). To study whether mutations in the hemochromatosis gene (HFE) could be a risk factor for the development of gestational diabetes mellitus (GDM), the prevalence of HFE mutations in patients with GDM was compared to that of healthy pregnant controls. Methods: GDM was diagnosed in 208 of 2,421 pregnant woman screened between the 24th and 28th week of gestation over a period of 18 months. Patients and 170 matched control subjects were screened for the HFE gene mutations C282Y and H63D. Results: In North and Central European GDM patients, the allele frequency of the C282Y mutation (7.7%) was higher than in pregnant controls (2.9%; p = 0.04), while the frequency of the H63D mutation was not different (p = 0.45). Three patients with GDM were homozygous for H63D (3.1%), 1 patient was homozygous for C282Y (1.0%), 2 patients were compound heterozygous (2.0%) and 26 were heterozygous [11 C282Y (11.2%) and 15 H63D (15.3%)]. C282Y and H63D allele frequencies were not different between controls and GDIVI patients of Southern European or non-European origin. Irrespective of the HIFE-mutation status, serum ferritin levels were increased in patients with GDM compared to healthy pregnant controls (p = 0.01), while transferrin saturation was similar in both groups. Conclusions: In North and Central European patients with GDM, the C282Y allele frequency is higherthan in healthy pregnant women, suggesting a genetic susceptibility to the development of GDM. Copyright (c) 2005 S. Karger AG, Basel.

Sensing and control of adipocyte function

Obesity has become a global epidemic. Approximately 15% of the world population is either overweight or obese. This figure rises to 75% in many westernised countries including the United Kingdom. Health costs in the UK to treat obesity and associated disease are conservatively estimated at 6% of the National Health Service (NHS) budget equating to 3.33 billion Euros. Excess adiposity, especially in visceral depots, increases the risk of type 2 diabetes, cardiovascular disease, gall stones, hypertension and cancer. Type 2 diabetes mellitus accounts for >90% of all cases of diabetes of which the majority can be attributed to increased adiposity, and approximately 70% of cardiovascular disease has been attributed to obesity in the US. Weight loss reduces risk of these complications and in some cases can eliminate the condition. However, weight loss by conventional non-medicated methods is often unsuccessful or promptly followed by weight regain. This thesis has investigated adipocytes development and adipokine signalling with a view to enhance the understanding of tissue functionality and to identify possible targets or pathways for therapeutic intervention. Adipocyte isolation from human tissue samples was undertaken for these investigative studies, and the methodology was optimised. The resulting isolates of pre-adipocytes and mature adipocytes were characterised and evaluated. Major findings from these studies indicate that mature adipocytes undergo cell division post terminal differentiation. Gene studies indicated that subcutaneous adipose tissue exuded greater concentrations and fluctuations of adipokine levels than visceral adipose tissue, indicating an important adiposensing role of subcutaneous adipose tissue. It was subsequently postulated that the subcutaneous depot may provide the major focus for control of overall energy balance and by extension weight control. One potential therapeutic target, 11ß-hydrosteroid dehydrogenase (11ß-HSD1) was investigated, and prospective inhibitors of its action were considered (BVT1, BVT2 and AZ121). Selective reduction of adiposity of the visceral depot was desired due to its correlation with the detrimental effects of obesity. However, studies indicated that although the visceral depot tissue was not unaffected, the subcutaneous depot was more susceptible to therapeutic inhibition by these compounds. This was determined to be a potentially valuable therapeutic intervention in light of previous postulations regarding long-term energy control via the subcutaneous tissue depot.