Lens shape and refractive index distribution in type 1 diabetes

Purpose: To compare lens dimensions and refractive index distributions in type 1 diabetes and age-matched control groups. Methods: There were 17 participants with type 1 diabetes, consisting of two subgroups (7 young [23 ± 4 years] and 10 older [54 ± 4 years] participants), with 23 controls (13 young, 24 ± 4 years; 10 older, 55 ± 4 years). For each participant, one eye was tested with relaxed accommodation. A 3T clinical magnetic resonance imaging scanner was used to image the eye, employing a multiple spin echo (MSE) sequence to determine lens dimensions and refractive index profiles along the equatorial and axial directions. Results: The diabetes group had significantly smaller lens equatorial diameters and larger lens axial thicknesses than the control group (diameter mean ± 95% confidence interval [CI]: diabetes group 8.65 ± 0.26 mm, control group 9.42 ± 0.18 mm; axial thickness: diabetes group 4.33 ± 0.30 mm, control group 3.80 ± 0.14 mm). These differences were also significant within each age group. The older group had significantly greater axial thickness than the young group (older group 4.35 ± 0.26 mm, young group 3.70 ± 0.25 mm). Center refractive indices of diabetes and control groups were not significantly different. There were some statistically significant differences between the refractive index fitting parameters of young and older groups, but not between diabetes and control groups of the same age. Conclusions: Smaller lens diameters occurred in the diabetes groups than in the age-matched control groups. Differences in refractive index distribution between persons with and without diabetes are too small to have important effects on instruments measuring axial thickness.

The impact of the metabolic syndrome and parental risk factors in patients with type 1 diabetes

Background: One-third of patients with type 1 diabetes develop diabetic complications, such as diabetic nephropathy. The diabetic complications are related to a high mortality from cardiovascular disease, impose a great burden on the health care system, and reduce the health-related quality of life of patients. Aims: This thesis assessed, whether parental risk factors identify subjects at a greater risk of developing diabetic complications. Another aim was to evaluate the impact of a parental history of type 2 diabetes on patients with type 1 diabetes. A third aim was to assess the role of the metabolic syndrome in patients with type 1 diabetes, both its presence and its predictive value with respect to complications. Subjects and methods: This study is part of the ongoing nationwide Finnish Diabetic Nephropathy (FinnDiane) Study. The study was initiated in 1997, and, thus far, 4,800 adult patients with type 1 diabetes have been recruited. Since 2004, follow-up data have also been collected in parallel to the recruitment of new patients. Studies I to III have a cross-sectional design, whereas Study IV has a prospective design. Information on parents was obtained from the patients with type 1 diabetes by a questionnaire. Results: Clustering of parental hypertension, cardiovascular disease, and diabetes (type 1 and type 2) was associated with diabetic nephropathy in patients with type 1 diabetes, as was paternal mortality. A parental history of type 2 diabetes was associated with a later onset of type 1 diabetes, a higher prevalence of the metabolic syndrome, and a metabolic profile related to insulin resistance, despite no difference in the distribution of human leukocyte antigen genotypes or the presence of diabetic complications. A maternal history of type 2 diabetes, seemed to contribute to a worse metabolic profile in the patients with type 1 diabetes than a paternal history. The metabolic syndrome was a frequent finding in patients with type 1 diabetes, observed in 38% of males and 40% of females. The prevalence increased with worsening of the glycemic control and more severe renal disease. The metabolic syndrome was associated with a 3.75-fold odds ratio for diabetic nephropathy, and all of the components of the syndrome were independently associated with diabetic nephropathy. The metabolic syndrome, independent of diabetic nephropathy, increased the risk of cardiovascular events and cardiovascular and diabetes-related mortality over a 5.5-year follow-up. With respect to progression of diabetic nephropathy, the role of the metabolic syndrome was less clear, playing a strong role only in the progression from macroalbuminuria to end-stage renal disease. Conclusions: Familial factors and the metabolic syndrome play an important role in patients with type 1 diabetes. Assessment of these factors is an easily applicable tool in clinical practice to identify patients at a greater risk of developing diabetic complications.

Structured Type 1 Diabetes education delivered within routine care: impact on glycemic control and diabetes-specific quality of life

OBJECTIVE:
To determine whether improvements in glycemic control and diabetes-specific quality of life (QoL) scores reported in research studies for the type 1 diabetes structured education program Dose Adjustment For Normal Eating (DAFNE) are also found when the intervention is delivered within routine U.K. health care.

RESEARCH DESIGN AND METHODS:
Before and after evaluation of DAFNE to assess impact on glycemic control and QoL among 262 adults with type 1 diabetes.

RESULTS:
There were significant improvements in HbA_1c from baseline to 6 and 12 months (from 9.1 to 8.6 and 8.8%, respectively) in a subgroup with suboptimal control. QoL was significantly improved by 3 months and maintained at both follow-up points.

CONCLUSIONS:
Longer-term improved glycemic control and QoL is achievable among adults with type 1 diabetes through delivery of structured education in routine care, albeit with smaller effect sizes than reported in trials.

Prevalence and antifungal resistance profile of Candida spp. oral isolates from patients with type 1 and 2 diabetes mellitus

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Description de l’évolution du profil socio-cognitif et clinique d’une cohorte d’adolescents diabétiques de type 1 ayant suivi un programme d’éducation thérapeutique

Thèse réalisée en cotutelle entre Aix-Marseille Université et l'Université de Montréal

Att leva med diabetes typ 1- En litteraturöversikt om barn och ungdomar samt deras föräldrars upplevelser

Bakgrund: Diabetes typ 1 ökar bland barn och ungdomar, Sverige har den näst högsta insjuknandefrekvensen i hela världen. Diabetes typ 1 är en kronisk autoimmun sjukdom vilket innebär att kroppens immunförsvar angriper de egna insulinproducerande cellerna i pankreas. Patienter med diabetes typ 1 löper stor risk att drabbas av komplikationer och följdsjukdomar. Syfte: Syftet med denna studie är att beskriva barn och ungdomar samt deras föräldrars upplevelser av att leva med diabetes typ 1. Metod: En litteraturstudie genomfördes med totalt 15 artiklar utifrån studiens syfte, sökningarna har skett i databaserna Cinahl och PubMed. Artiklarna poängsattes med hjälp av Högskolan Dalarnas modifierade version av granskningsmallar för kvantitativa och kvalitativa artiklar. Resultat: Analysen av artiklarna resulterade i fyra kategorier som beskriver barn och ungdomars upplevelser: begränsningar i vardagen, stöd från föräldrar och sjukvården var centralt, rädsla för komplikationer samt att vara annorlunda. Två kategorier beskriver föräldrarnas upplevelser: oro rädsla och frustration samt att våga släppa kontrollen. Slutsats: Barn och ungdomar med diabetes typ 1 upplevde sitt liv som begränsat. Sjukdomen påverkar dem i skolan, under fysisk aktivitet, tillsammans med vänner, och i sociala sammanhang. Föräldrar till barn och ungdomar med diabetes typ 1 upplevde rädsla och oro över sitt barns sjukdom.

Upplevelser av stöd från diabetessjuksköterskan hos personer med diabetes typ 1 : – Sekundäranalys av en kvalitativ intervjustudie

Introduction: Type 1 diabetes is a chronic disease that affects the individual in everyday life. The diabetes team sets the treatment goals together with the patient aiming for a good quality of life and to prevent complications. The diabetes nurse should include in-depth knowledge of the daily life of people with diabetes, and have respect for the individual's choices and life situation. Aim: To describe how people with type 1 diabetes experience the support from the diabetes nurse. Method: A qualitative content analysis with an inductive approach has been used. A secondary analysis including semi-structured interviews with 15 adults (> 18 years) with type 1 diabetes was conducted. Result: The result was summarized with an overall theme "At the clinic - experience of the support offered" describes how people experience the support from their diabetes nurse. The theme constituted three categories "Access to the diabetes nurse", "The diabetes nurse - a source of information and knowledge that might need to be complemented with the support from other professionals" and,"Mutual trust - the patient's experience of the district nurse as a discussion partner and support". Conclusion: The results showed that the accessibility to diabetes nurses was experienced as good. It was simple and easy to make contact. The diabetes nurses were experienced to be engaged and provide good support to the patients. A good dialogue with the diabetes nurse and commitment from the diabetes nurse were mentioned as important factors that made the visits to be experienced as good and important. There were requests for greater access and expanded opportunities for help from counselors, as well as an increased focus on how the person is feeling.

Anhörigperspektivet utifrån föräldrars erfarenheter då barnet har diabetes typ 1 : En litteraturöversikt

Bakgrund: Den största delen av behandlingen vid diabetes typ 1 är egenvård. När ett barn insjuknar i diabetes är det föräldrarna som huvudsakligen ansvarar för egenvården. Detta kan vara både psykiskt och fysiskt påfrestande. Det behövs mer kunskap om föräldrars upplevelser och deras erfarenheter av att vårda ett barn med diabetes. Syfte: Syftet med denna litteraturstudie är att belysa anhörigperspektivet utifrån föräldrars erfarenheter då barnet har diabetes typ 1 samt hur sjuksköterskan kan ge stöd till anhöriga. Metod: En litteraturöversikt. Resultat: Resultatet visar att egenvården skiljer sig mellan små barn och ungdomar, att föräldrar upplever känslor av oro och stress när deras barn fått diagnosen och att sjuksköterskan kan hjälpa och öka sin förståelse genom att stödja. Slutsats: Författarna kan dra slutsatsen att ökad kunskap och förståelse om egenvård vid diabetes typ 1 hos barn, kan bidra till en hjälp för sjuksköterskor att ge föräldrarna ett bra stöd och bemötande i vården.

Book Review: Diabetes and wellbeing: Managing psychological and emotional challenges of diabetes types 1 and 2

Book Review in peer revewed Journal of Diabetes Nursing about the psychological and emotional challenges associated with living with Diabetes. The book is recommended to both health professionals and people with Diabetes.

Differential coronary resistance microvessel remodeling between type 1 and type 2 diabetic mice: Impact of exercise training

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Adesão ao tratamento por pacientes portadores de diabetes tipo 1 e tipo 2: efeitos do treino de discriminação de dicas internas e externas

O presente trabalho pretende comparar resultados de treinos de discriminação de sintomas e de ações relativas ao tratamento do diabetes Tipo 1 e Tipo 2, avaliando a eficácia desses treinos para a estimativa do índice glicêmico e para a promoção de adesão ao tratamento. Inúmeras pesquisas realizadas na área de psicologia da saúde têm o objetivo de proporcionar a melhora no tratamento ao paciente diabético. Parte dessas pesquisas utiliza um procedimento denominado de- automonitoração, a qual consiste em habilidades de observação, aferição e registro de aspectos relevantes no tratamento do diabetes. como: (a) índice glicêmico (IG) (b) sintomas (dicas internas -DI); e (c) ações envolvidas no tratamento nas áreas da medicação, alimentação e atividade física (dicas externas -DE). Estudos têm demonstrado que com a automonitoração o paciente diabético melhora o nível de discriminação das alterações glicêmicas. Essa.literatura não é clara em definir qual o melhor tipo de dica para melhorar a discriminação dos estados glicêmicos e afirm que o desenvolvimento desta habilidade não favorece a melhora na adesão ao tratamento. Esse estudo compreendeu três fases: (a) Entrevista inicial e de linha de Base; (b ) Entrevistas de Treino e (c) Entrevista Final e Devolutiva. A fase de treino está dividida em duas etapas Dicas Internas (DI) e Dicas Externas (DE). Nas etapas de treino os participantes estimaram e atribuíram causa para taxa de glicose sangüínea medida por um reflectômetro em cada entrevista. Na etapa DE. os participantes também recebiam feedback do pesquisador acerca do relato de seguimento das orientações, com base nas orientações recebidas em consulta e compiladas do prontuário do paciente. Foi calculado o índice de adesão (IA) nas duas primeiras fases. As entrevistas da fase de treino foram realizadas na residência do participante, em intervalos de três dias, nos quais o participante registrava a ocorrência de eventos correspondentes a etapa que estava realizando. Os resultados demonstram que independente do tipo de treino realizado os participantes estimaram os seus estados glicêmicos com base em dicas externas. Os sintomas' relatados na etapa DI nem sempre estavam associados ao Ia medido. Os participantes portadores de diabetes. Tipo 1 alcançaram maior precisão nas estimativas no treino de DE. A maioria dos participantes alcançaram melhor adesão quando iniciaram o treino por DE. Os resultados sugerem que: (a) relatos de sintomas não são os melhores indicadores para avaliar o estado glicêmico e a adesão ao tratamento (b) o melhor tipo de treino para promoção da adesão ao tratamento é o que envolve as dicas externas.

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.

Age-related loss of brain volume and T2 relaxation time in youth with type 1 diabetes

OBJECTIVE: Childhood-onset type 1 diabetes is associated with neurocognitive deficits, but there is limited evidence to date regarding associated neuroanatomical brain changes and their relationship to illness variables such as age at disease onset. This report examines age-related changes in volume and T2 relaxation time (a fundamental parameter of magnetic resonance imaging that reflects tissue health) across the whole brain. RESEARCH DESIGN AND METHODS: Type 1 diabetes, N = 79 (mean age 20.32 ± 4.24 years), and healthy control participants, N = 50 (mean age 20.53 ± 3.60 years). There were no substantial group differences on socioeconomic status, sex ratio, or intelligence quotient. RESULTS: Regression analyses revealed a negative correlation between age and brain changes, with decreasing gray matter volume and T2 relaxation time with age in multiple brain regions in the type 1 diabetes group. In comparison, the age-related decline in the control group was small. Examination of the interaction of group and age confirmed a group difference (type 1 diabetes vs. control) in the relationship between age and brain volume/T2 relaxation time. CONCLUSIONS: We demonstrated an interaction between age and group in predicting brain volumes and T2 relaxation time such that there was a decline in these outcomes in type 1 diabetic participants that was much less evident in control subjects. Findings suggest the neurodevelopmental pathways of youth with type 1 diabetes have diverged from those of their healthy peers by late adolescence and early adulthood but the explanation for this phenomenon remains to be clarified.

Clinical utility of mental state screening as a predictor of intellectual outcomes 6 months after diagnosis of type 1 diabetes

Background Screening tests of basic cognitive status or ‘mental state’ have been shown to predict mortality and functional outcomes in adults. This study examined the relationship between mental state and outcomes in children with type 1 diabetes. Objective We aimed to determine whether mental state at diagnosis predicts longer term cognitive function of children with a new diagnosis of type 1 diabetes. Methods Mental state of 87 patients presenting with newly diagnosed type 1 diabetes was assessed using the School-Years Screening Test for the Evaluation of Mental Status. Cognitive abilities were assessed 1 wk and 6 months postdiagnosis using standardized tests of attention, memory, and intelligence. Results Thirty-seven children (42.5%) had reduced mental state at diagnosis. Children with impaired mental state had poorer attention and memory in the week following diagnosis, and, after controlling for possible confounding factors, significantly lower IQ at 6 months compared to those with unimpaired mental state (p < 0.05). Conclusions Cognition is impaired acutely in a significant number of children presenting with newly diagnosed type 1 diabetes. Mental state screening is an effective method of identifying children at risk of ongoing cognitive difficulties in the days and months following diagnosis. Clinicians may consider mental state screening for all newly diagnosed diabetic children to identify those at risk of cognitive sequelae.