A technological framework based on automatic messaging for improving adherence of diabetic patients

En todo el mundo se ha observado un crecimiento exponencial en la incidencia de enfermedades crónicas como la hipertensión y enfermedades cardiovasculares y respiratorias, así como la diabetes mellitus, que causa un número de muertes cada vez mayor en todo el mundo (Beaglehole et al., 2008). En concreto, la prevalencia de diabetes mellitus (DM) está aumentando de manera considerable en todas las edades y representa un serio problema de salud mundial. La diabetes fue la responsable directa de 1,5 millones de muertes en 2012 y 89 millones de años de vida ajustados por discapacidad (AVAD) (OMS, 2014). Uno de los principales dilemas que suelen asociarse a la gestión de EC es la adherencia de los pacientes a los tratamientos, que representa un aspecto multifactorial que necesita asistencia en lo relativo a: educación, autogestión, interacción entre los pacientes y cuidadores y compromiso de los pacientes. Medir la adherencia del tratamiento es complicado y, aunque se ha hablado ampliamente de ello, aún no hay soluciones “de oro” (Reviews, 2002). El compromiso de los pacientes, a través de la participación, colaboración, negociación y a veces del compromiso firme, aumentan las oportunidades para una terapia óptima en la que los pacientes se responsabilizan de su parte en la ecuación de adherencia. Comprometer e involucrar a los pacientes diabéticos en las decisiones de su tratamiento, junto con expertos profesionales, puede ayudar a favorecer un enfoque centrado en el paciente hacia la atención a la diabetes (Martin et al., 2005). La motivación y atribución de poder de los pacientes son quizás los dos factores interventores más relevantes que afectan directamente a la autogestión de la atención a la diabetes. Se ha demostrado que estos dos factores desempeñan un papel fundamental en la adherencia a la prescripción, así como en el fomento exitoso de un estilo de vida sana y otros cambios de conducta (Heneghan et al., 2013). Un plan de educación personalizada es indispensable para proporcionarle al paciente las herramientas adecuadas que necesita para la autogestión efectiva de la enfermedad (El-Gayar et al. 2013). La comunicación efectiva es fundamental para proporcionar una atención centrada en el paciente puesto que influye en las conductas y actitudes hacia un problema de salud ((Frampton et al. 2008). En este sentido, la interactividad, la frecuencia, la temporalización y la adaptación de los mensajes de texto pueden promover la adherencia a un régimen de medicación. Como consecuencia, adaptar los mensajes de texto a los pacientes puede resultar ser una manera de hacer que las sugerencias y la información sean más relevantes y efectivas (Nundy et al. 2013). En este contexto, las tecnologías móviles en el ámbito de la salud (mHealth) están desempeñando un papel importante al conectar con pacientes para mejorar la adherencia a medicamentos recetados (Krishna et al., 2009). La adaptación de los mensajes de texto específicos de diabetes sigue siendo un área de oportunidad para mejorar la adherencia a la medicación y ofrecer motivación a adultos con diabetes. Sin embargo, se necesita más investigación para entender totalmente su eficacia. Los consejos de texto personalizados han demostrado causar un impacto positivo en la atribución de poder a los pacientes, su autogestión y su adherencia a la prescripción (Gatwood et al., 2014). mHealth se puede utilizar para ofrecer programas de asistencia de autogestión a los pacientes con diabetes y, al mismo tiempo, superar las dificultades técnicas y financieras que supone el tratamiento de la diabetes (Free at al., 2013). El objetivo principal de este trabajo de investigación es demostrar que un marco tecnológico basado en las teorías de cambios de conducta, aplicado al campo de la mHealth, permite una mejora de la adherencia al tratamiento en pacientes diabéticos. Como método de definición de una solución tecnológica, se han adoptado un conjunto de diferentes técnicas de conducta validadas denominado marco de compromiso de retroacción conductual (EBF, por sus siglas en inglés) para formular los mensajes, guiar el contenido y evaluar los resultados. Los estudios incorporan elementos del modelo transteórico (TTM, por sus siglas en inglés), la teoría de la fijación de objetivos (GST, por sus siglas en inglés) y los principios de comunicación sanitaria persuasiva y eficaz. Como concepto general, el modelo TTM ayuda a los pacientes a progresar a su próxima fase de conducta a través de mensajes de texto motivados específicos y permite que el médico identifique la fase actual y adapte sus estrategias individualmente. Además, se adoptan las directrices del TTM para fijar objetivos personalizados a un nivel apropiado a la fase de cambio del paciente. La GST encierra normas que van a ponerse en práctica para promover la intervención educativa y objetivos de pérdida de peso. Finalmente, los principios de comunicación sanitaria persuasiva y eficaz aplicados a la aparición de los mensajes se han puesto en marcha para aumentar la efectividad. El EBF tiene como objetivo ayudar a los pacientes a mejorar su adherencia a la prescripción y encaminarlos a una mejora general en la autogestión de la diabetes mediante mensajes de texto personalizados denominados mensajes de retroacción automáticos (AFM, por sus siglas en inglés). Después de una primera revisión del perfil, consistente en identificar características significativas del paciente basadas en las necesidades de tratamiento, actitudes y conductas de atención sanitaria, el sistema elige los AFM personalizados, los aprueba el médico y al final se transfieren a la interfaz del paciente. Durante el tratamiento, el usuario recopila los datos en dispositivos de monitorización de pacientes (PMD, por sus siglas en inglés) de una serie de dispositivos médicos y registros manuales. Los registros consisten en la toma de medicación, dieta y actividad física y tareas de aprendizaje y control de la medida del metabolismo. El compromiso general del paciente se comprueba al estimar el uso del sistema y la adherencia del tratamiento y el estado de los objetivos del paciente a corto y largo plazo. El módulo de análisis conductual, que consiste en una serie de reglas y ecuaciones, calcula la conducta del paciente. Tras lograr el análisis conductual, el módulo de gestión de AFM actualiza la lista de AFM y la configuración de los envíos. Las actualizaciones incluyen el número, el tipo y la frecuencia de mensajes. Los AFM los revisa periódicamente el médico que también participa en el perfeccionamiento del tratamiento, adaptado a la fase transteórica actual. Los AFM se segmentan en distintas categorías y niveles y los pacientes pueden ajustar la entrega del mensaje de acuerdo con sus necesidades personales. El EBF se ha puesto en marcha integrado dentro del sistema METABO, diseñado para facilitar al paciente diabético que controle sus condiciones relevantes de una manera menos intrusiva. El dispositivo del paciente se vincula en una plataforma móvil, mientras que una interfaz de panel médico permite que los profesionales controlen la evolución del tratamiento. Herramientas específicas posibilitan que los profesionales comprueben la adherencia del paciente y actualicen la gestión de envíos de AFM. El EBF fue probado en un proyecto piloto controlado de manera aleatoria. El principal objetivo era examinar la viabilidad y aceptación del sistema. Los objetivos secundarios eran también la evaluación de la eficacia del sistema en lo referente a la mejora de la adherencia, el control glucémico y la calidad de vida. Se reclutaron participantes de cuatro centros clínicos distintos en Europa. La evaluación del punto de referencia incluía datos demográficos, estado de la diabetes, información del perfil, conocimiento de la diabetes en general, uso de las plataformas TIC, opinión y experiencia con dispositivos electrónicos y adopción de buenas prácticas con la diabetes. La aceptación y eficacia de los criterios de evaluación se aplicaron para valorar el funcionamiento del marco tecnológico. El principal objetivo era la valoración de la eficacia del sistema en lo referente a la mejora de la adherencia. En las pruebas participaron 54 pacientes. 26 fueron asignados al grupo de intervención y equipados con tecnología móvil donde estaba instalado el EBF: 14 pacientes tenían T1DM y 12 tenían T2DM. El grupo de control estaba compuesto por 25 pa cientes que fueron tratados con atención estándar, sin el empleo del EBF. La intervención profesional tanto de los grupos de control como de intervención corrió a cargo de 24 cuidadores, entre los que incluían diabetólogos, nutricionistas y enfermeras. Para evaluar la aceptabilidad del sistema y analizar la satisfacción de los usuarios, a través de LimeSurvey, se creó una encuesta multilingüe tanto para los pacientes como para los profesionales. Los resultados también se recopilaron de los archivos de registro generados en los PMD, el panel médico profesional y las entradas de la base de datos. Los mensajes enviados hacia y desde el EBF y los archivos de registro del sistema y los servicios de comunicación se grabaron durante las cinco semanas del estudio. Se entregaron un total de 2795 mensajes, lo que supuso una media de 107,50 mensajes por paciente. Como se muestra, los mensajes disminuyen con el tiempo, indicando una mejora global de la adherencia al plan de tratamiento. Como se esperaba, los pacientes con T1DM recibieron más consejos a corto plazo, en relación a su estado. Del mismo modo, al ser el centro de T2DM en cambios de estilo de vida sostenible a largo plazo, los pacientes con T2DM recibieron más consejos de recomendación, en cuanto a dietas y actividad física. También se ha llevado a cabo una comparación de la adherencia e índices de uso para pacientes con T1DM y T2DM, entre la primera y la segunda mitad de la prueba. Se han observado resultados favorables para el uso. En lo relativo a la adherencia, los resultados denotaron una mejora general en cada dimensión del plan de tratamiento, como la nutrición y las mediciones de inserción de glucosa en la sangre. Se han llevado a cabo más estudios acerca del cambio a nivel educativo antes y después de la prueba, medidos tanto para grupos de control como de intervención. Los resultados indicaron que el grupo de intervención había mejorado su nivel de conocimientos mientras que el grupo de control mostró una leve disminución. El análisis de correlación entre el nivel de adherencia y las AFM ha mostrado una mejora en la adherencia de uso para los pacientes que recibieron los mensajes de tipo alertas, y unos resultados no significativos aunque positivos relacionados con la adherencia tanto al tratamiento que al uso correlacionado con los recordatorios. Por otra parte, los AFM parecían ayudar a los pacientes que no tomaban suficientemente en serio su tratamiento en el principio y que sí estaban dispuestos a responder a los mensajes recibidos. Aun así, los pacientes que recibieron demasiadas advertencias, comenzaron a considerar el envío de mensajes un poco estresante. El trabajo de investigación llevado a cabo al desarrollar este proyecto ofrece respuestas a las cuatro hipótesis de investigación que fueron la motivación para el trabajo. • Hipótesis 1 : es posible definir una serie de criterios para medir la adherencia en pacientes diabéticos. • Hipótesis 2: es posible diseñar un marco tecnológico basado en los criterios y teorías de cambio de conducta mencionados con anterioridad para hacer que los pacientes diabéticos se comprometan a controlar su enfermedad y adherirse a planes de atención. • Hipótesis 3: es posible poner en marcha el marco tecnológico en el sector de la salud móvil. • Hipótesis 4: es posible utilizar el marco tecnológico como solución de salud móvil en un contexto real y tener efectos positivos en lo referente a indicadores de control de diabetes. La verificación de cada hipótesis permite ofrecer respuesta a la hipótesis principal: La hipótesis principal es: es posible mejorar la adherencia diabética a través de un marco tecnológico mHealth basado en teorías de cambio de conducta. El trabajo llevado a cabo para responder estas preguntas se explica en este trabajo de investigación. El marco fue desarrollado y puesto en práctica en el Proyecto METABO. METABO es un Proyecto I+D, cofinanciado por la Comisión Europea (METABO 2008) que integra infraestructura móvil para ayudar al control, gestión y tratamiento de los pacientes con diabetes mellitus de tipo 1 (T1DM) y los que padecen diabetes mellitus de tipo 2 (T2DM). ABSTRACT Worldwide there is an exponential growth in the incidence of Chronic Diseases (CDs), such as: hypertension, cardiovascular and respiratory diseases, as well as diabetes mellitus, leading to rising numbers of deaths worldwide (Beaglehole et al. 2008). In particular, the prevalence of diabetes mellitus (DM) is largely increasing among all ages and constitutes a major worldwide health problem. Diabetes was directly responsible for 1,5 million deaths in 2012 and 89 million Disability-adjusted life year (DALYs) (WHO 2014). One of the key dilemmas often associated to CD management is the patients’ adherence to treatments, representing a multi-factorial aspect that requires support in terms of: education, self-management, interaction between patients and caregivers, and patients’ engagement. Measuring adherence is complex and, even if widely discussed, there are still no “gold” standards ((Giardini et al. 2015), (Costa et al. 2015). Patient’s engagement, through participation, collaboration, negotiation, and sometimes compromise, enhance opportunities for optimal therapy in which patients take responsibility for their part of the adherence equation. Engaging and involving diabetic patients in treatment decisions, along with professional expertise, can help foster a patient-centered approach to diabetes care (Martin et al. 2005). Patients’ motivation and empowerment are perhaps the two most relevant intervening factors that directly affect self-management of diabetes care. It has been demonstrated that these two factors play an essential role in prescription adherence, as well as for the successful encouragement of a healthy life-style and other behavioural changes (Heneghan et al. 2013). A personalised education plan is indispensable in order to provide the patient with the appropriate tools needed for the effective self-management of the disease (El-Gayar et al. 2013). Effective communication is at the core of providing patient-centred care since it influences behaviours and attitudes towards a health problem (Frampton et al. 2008). In this regard, interactivity, frequency, timing, and tailoring of text messages may promote adherence to a medication regimen. As a consequence, tailoring text messages to patients can constitute a way of making suggestions and information more relevant and effective (Nundy et al. 2013). In this context, mobile health technologies (mHealth) are playing significant roles in improving adherence to prescribed medications (Krishna et al. 2009). The tailoring of diabetes-specific text messages remains an area of opportunity to improve medication adherence and provide motivation to adults with diabetes but further research is needed to fully understand their effectiveness. Personalized text advices have proven to produce a positive impact on patients’ empowerment, self-management, and adherence to prescriptions (Gatwood et al. 2014). mHealth can be used for offering self-management support programs to diabetes patients and at the same time surmounting the technical and financial difficulties involved in diabetes treatment (Free et al. 2013). The main objective of this research work is to demonstrate that a technological framework, based on behavioural change theories, applied to mHealth domain, allows improving adherence treatment in diabetic patients. The framework, named Engagement Behavioural Feedback Framework (EBF), is built on top of validated behavioural techniques to frame messages, guide the definition of contents and assess outcomes: elements from the Transtheoretical Model (TTM), the Goal-Setting Theory (GST), Effective Health Communication (EHC) guidelines and Principles of Persuasive Technology (PPT) were incorporated. The TTM helps patients to progress to a next behavioural stage, through specific motivated text messages, and allow clinician’s identifying the current stage and tailor its strategies individually. Moreover, TTM guidelines are adopted to set customised goals at a level appropriate to the patient’s stage of change. The GST was used to build rules to be applied for enhancing educational intervention and weight loss objectives. Finally, the EHC guidelines and the PPT were applied to increase the effectiveness of messages. The EBF aims to support patients on improving their prescription adherence and persuade them towards a general improvement in diabetes self-management, by means of personalised text messages, named Automatic Feedback Messages (AFM). After a first profile screening, consisting in identifying meaningful patient characteristics based on treatment needs, attitudes and health care behaviours, customised AFMs are selected by the system, approved by the professional, and finally transferred into the patient interface. During the treatment, the user collects the data into a Patient Monitoring Device (PMD) from a set of medical devices and from manual inputs. Inputs consist in medication intake, diet and physical activity, metabolic measurement monitoring and learning tasks. Patient general engagement is checked by estimating the usage of the system and the adherence of treatment and patient goals status in the short and the long term period. The Behavioural Analysis Module, consisting in a set of rules and equations, calculates the patient’s behaviour. After behavioural analysis is accomplished, the AFM library and the dispatch setting are updated by the AFM Manager module. Updates include the number, the type and the frequency of messages. The AFMs are periodically supervised by the professional who also participates to the refinement of the treatment, adapted to the current transtheoretical stage. The AFMs are segmented in different categories and levels and patients can adjust message delivery in accordance with their personal needs. The EBF was integrated to the METABO system, designed to facilitate diabetic patients in managing their disease in a less intrusive approach. Patient device corresponds in a mobile platform, while a medical panel interface allows professionals to monitoring the treatment evolution. Specific tools allow professional to check patient adherence and to update the AFMs dispatch management. The EBF was tested in a randomised controlled pilot. The main objective was to examine the feasibility and acceptance of the system. Secondary objectives were also the assessment of the effectiveness of system in terms of adherence improvement, glycaemic control, and quality of life. Participants were recruited from four different clinical centres in Europe. The baseline assessment included demographics, diabetes status, profile information, knowledge about diabetes in general, usage of ICT platforms, opinion and experience about electronic devices and adoption of good practices with diabetes. Acceptance and the effectiveness evaluation criteria were applied to evaluate the performance of the technological framework. The main objective was the assessment of the effectiveness of system in terms of adherence improvement. Fifty-four patients participated on the trials. Twenty-six patients were assigned in the intervention group and equipped with mobile where the EBF was installed: 14 patients were T1DM and 12 were T2DM. The control group was composed of 25 patients that were treated through a standard care, without the usage of the EBF. Professional’s intervention for both intervention and control groups was carried out by 24 care providers, including endocrinologists, nutritionists, and nurses. In order to evaluate the system acceptability and analyse the users’ satisfaction, an online multi-language survey, using LimeSurvey, was produced for both patients and professionals. Results were also collected from the log-files generated in the PMDs, the professional medical panel and the entries of the data base. The messages sent to and from the EBF and the log-files of the system and communication services were recorded over 5 weeks of the study. A total of 2795 messages were submitted, representing an average of 107,50 messages per patient. As demonstrated, messages decrease over time indicating an overall improvement of the care plan’s adherence. As expected, T1DM patients were more loaded with short-term advices, in accordance with their condition. Similarly, being the focus of T2DM on long-term sustainable lifestyle changes, T2DM received more reminders advices, as for diet and physical activity. Favourable outcomes were observed for treatment and usage adherences of the intervention group: for both the adherence indices, results denoted a general improvement on each care plan’s dimension, such as on nutrition and blood glucose input measurements. Further studies were conducted on the change on educational level before and after the trial, measured for both control and intervention groups. The outcomes indicated the intervention group has improved its level of knowledge, while the control group denoted a low decrease. The correlation analysis between the level of adherences and the AFMs showed an improvement in usage adherence for patients who received warnings message, while non-significantly yet even positive indicators related to both treatment and usage adherence correlated with the Reminders. Moreover, the AFMs seemed to help those patients who did not take their treatment seriously enough in the beginning and who were willing to respond to the messages they received. Even though, patients who received too many Warnings, started to consider the message dispatch to be a bit stressful. The research work carried out in developing this research work provides responses to the four research hypothesis that were the motivation for the work: •Hypothesis 1: It is possible to define a set of criteria to measure adherence in diabetic patients. •Hypothesis 2: It is possible to design a technological framework, based on the aforementioned criteria and behavioural change theories, to engage diabetic patients in managing their disease and adhere to care plans. •Hypothesis 3: It is possible to implement the technological framework in the mobile health domain. •Hypothesis 4: It is possible to use the technological framework as a mobile health solution in a real context and have positive effects in terms of diabetes management indicators. The verification of each hypothesis allowed us to provide a response to the main hypothesis: The Main Hypothesis is: It is possible to improve diabetic adherence through a mHealth technological framework based on behavioural change theories. The work carried out to answer these questions is explained in this research work. The framework was developed and applied in the METABO project. METABO is an R&D project, co-funded by the European Commission (METABO 2008) that integrates mobile infrastructure for supporting the monitoring, management, and treatment of type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) patients.

Leptin, troglitazone, and the expression of sterol regulatory element binding proteins in liver and pancreatic islets

Overaccumulation of lipids in nonadipose tissues of obese rodents may lead to lipotoxic complications such as diabetes. To assess the pathogenic role of the lipogenic transcription factor, sterol regulatory element binding protein 1 (SREBP-1), we measured its mRNA in liver and islets of obese, leptin-unresponsive fa/fa Zucker diabetic fatty rats. Hepatic SREBP-1 mRNA was 2.4 times higher than in lean +/+ controls, primarily because of increased SREBP-1c expression. mRNA of lipogenic enzymes ranged from 2.4- to 4.6-fold higher than lean controls, and triacylglycerol (TG) content was 5.4 times higher. In pancreatic islets of fa/fa rats, SREBP-1c was 3.4 times higher than in lean +/+ Zucker diabetic fatty rats. The increase of SREBP-1 in liver and islets of untreated fa/fa rats was blocked by 6 weeks of troglitazone therapy, and the diabetic phenotype was prevented. Up-regulation of SREBP-1 also occurred in livers of Sprague–Dawley rats with diet-induced obesity. Hyperleptinemia, induced in lean +/+ rats by adenovirus gene transfer, lowered hepatic SREBP-1c by 74% and the lipogenic enzymes from 35 to 59%. In conclusion, overnutrition increases and adenovirus-induced hyperleptinemia decreases SREBP-1c expression in liver and islets. SREBP-1 overexpression, which is prevented by troglitazone, may play a role in the ectopic lipogenesis and lipotoxicity complicating obesity in Zucker diabetic fatty rats.

Overexpression of lecithin:cholesterol acyltransferase in transgenic rabbits prevents diet-induced atherosclerosis.

Lecithin:cholesterol acyltransferase (LCAT) is a key plasma enzyme in cholesterol and high density lipoprotein (HDL) metabolism. Transgenic rabbits overexpressing human LCAT had 15-fold greater plasma LCAT activity that nontransgenic control rabbits. This degree of overexpression was associated with a 6.7-fold increase in the plasma HDL cholesterol concentration in LCAT transgenic rabbits. On a 0.3% cholesterol diet, the HDL cholesterol concentrations increased from 24 +/- 1 to 39 +/- 3 mg/dl in nontransgenic control rabbits (n = 10; P < 0.05) and increased from 161 +/- 5 to 200 +/- 21 mg/dl (P < 0.001) in the LCAT transgenic rabbits (n = 9). Although the baseline non-HDL concentrations of control (4 +/- 3 mg/dl) and transgenic rabbits (18 +/- 4 mg/dl) were similar, the cholesterol-rich diet raised the non-HDL cholesterol concentrations, reflecting the atherogenic very low density, intermediate density, and low density lipoprotein particles observed by gel filtration chromatography. The non-HDL cholesterol rose to 509 +/- 57 mg/dl in controls compared with only 196 +/- 14 mg/dl in the LCAT transgenic rabbits (P < 0.005). The differences in the plasma lipoprotein response to a cholesterol-rich diet observed in the transgenic rabbits paralleled the susceptibility to developing aortic atherosclerosis. Compared with nontransgenic controls, LCAT transgenic rabbits were protected from diet-induced atherosclerosis with significant reductions determined by both quantitative planimetry (-86%; P < 0.003) and quantitative immunohistochemistry (-93%; P < 0.009). Our results establish the importance of LCAT in the metabolism of both HDL and apolipoprotein B-containing lipoprotein particles with cholesterol feeding and the response to diet-induced atherosclerosis. In addition, these findings identify LCAT as a new target for therapy to prevent atherosclerosis.

High fat diet-induced hyperglycemia: prevention by low level expression of a glucose transporter (GLUT4) minigene in transgenic mice.

High-fat intake leading to obesity contributes to the development of non-insulin-dependent diabetes mellitus (NIDDM, type 2). Similarly, mice fed a high-fat (safflower oil) diet develop defective glycemic control, hyperglycemia, and obesity. To assess the effect of a modest increase in the expression of GLUT4 (the insulin-responsive glucose transporter) on impaired glycemic control caused by fat feeding, transgenic mice harboring a GLUT4 minigene were fed a high-fat diet. Low-level tissue-specific (heart, skeletal muscle, and adipose tissue) expression of the GLUT4 minigene in transgenic mice prevented the impairment of glycemic control and accompanying hyperglycemia, but not obesity, caused by fat feeding. Thus, a small increase (< or = 2-fold) in the tissue level of GLUT4 prevents a primary symptom of the diabetic state in a mouse model, suggesting a possible target for intervention in the treatment of NIDDM.

Estatinas e risco de diabetes : revisão sistemática

Trabalho Final do Curso de Mestrado Integrado em Medicina, Faculdade de Medicina, Universidade de Lisboa, 2014

Determinantes de efetividade de intervenção clínica na obesidade : perspetiva de um painel de peritos

Tese de mestrado, Nutrição Clínica, Faculdade de Medicina, Universidade de Lisboa, 2014

Perda auditiva na diabetes Mellitus

Trabalho Final do Curso de Mestrado Integrado em Medicina, Faculdade de Medicina, Universidade de Lisboa, 2014

The place of DPP-4 inhibitors in the treatment algorithm of diabetes type 2 : a systematic review of cost-effectiveness studies

Tese de mestrado, Epidemiologia, Universidade de Lisboa, Faculdade de Medicina, 2015

Vitamin and mineral therapy

Data contained in Dr. R. J. Fraser's "Vitamin chart": p. 27-94.

Hypertension and diabetes treatments and risk of adverse outcomes among breast cancer patients

Thesis (Ph.D.)--University of Washington, 2016-06

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.

Secondary prevention of cardiovascular events with long-term pravastatin in patients with diabetes or impaired fasting glucose - Results from the LIPID trial

OBJECTIVE- Diabetes, a major health problem worldwide, increases the risk of cardiovascular disease and its associated mortality. Evidence of the overall benefits of lipid modification in this area is needed. RESEARCH DESIGN AND METHODS- The Long-Term Intervention with Pravastatin in Ischemic Disease (LIPID) trial showed that cholesterol-lowering treatment with pravastatin reduced mortality and coronary heart disease (CHD) events in 9,014 patients aged 31-75 years with CHD and total cholesterol 4.0-7.0 mmol/l. We measured the effects of pravastatin therapy, 40 mg/day over 6.0 years, on the risk of CHD death or nonfatal myocardial infarction and other cardiovascular outcomes in 1,077 LIPID patients with diabetes and 940 patients with impaired fasting glucose (IFG). RESULTS- in patients allocated to placebo, the risk of a major CHD event was 61% higher in patients with diabetes and 23% higher in the IFG group than in patients with normal fasting glucose, and the risk of any cardiovascular event was 37% higher in the diabetic group and 19% higher in the IFG group. Pravastatin therapy reduced the risk of a major CHD event overall from 15.9 to 12.3% (relative risk reduction [RRR] 24%, P < 0.001) and from 23.4 to 19.6% in the diabetic group (19%, P = 0.11); in the diabetic group, the reduction was not significantly different from the reductions in the other groups. Pravastatin reduced the risk of any cardiovascular event from 52.7 to 45.2% (21%, P < 0.008) in patients With diabetes and from 45.7 to 37.1% (26%, P = 0.003) in the IFG group. Pravastatin reduced the risk of stroke from 9.9 to 6.3% in the diabetic group (RRR 39%, Cl 7-61%, P = 0.02) and from 5.4 to 3.4% in the IFG group (RRR 42%, Cl -9 to 69%, P = 0.09). Pravastatin did not reduce the incidence of diabetes. Over 6 years, pravastatin therapy prevented one major,CHD event (CHD death or nonfatal myocardial infarction) in 23 patients with IFG and 18 patients with diabetes. A meta-analysis of other major trials confirmed the high absolute risks of diabetes and IFG and the absolute benefits of statin therapy in these patients. CONCLUSIONS- Cholesterol-lowering treatment with pravastatin therapy prevents cardiovascular events, including stroke, in patients with diabetes or IFG and established CHD.

Tissue Doppler imaging for evaluation of myocardial function in patients with diabetes mellitus

Purpose of review Heart failure and diabetes mellitus are frequently associated, and diabetes appears to potentiate the clinical presentation of heart failure related to other causes. The purpose of this review is to examine recent advances in the application of tissue Doppler imaging for the assessment of diabetic heart disease. Recent findings Recent studies have documented that both myocardial systolic and diastolic abnormalities can be identified in apparently healthy patients with diabetes and no overt cardiac dysfunction. Interestingly, these are disturbances of longitudinal function, with compensatory increases of radial function-suggesting primary involvement of the subendocardium, which is a hallmark of myocardial ischemia. Despite this, there is limited evidence that diabetic microangiopathy is responsible-with reduced myocardial blood volume rather than reduced resting flow, and at least some evidence suggesting a normal increment of tissue velocity with stress. Finally, a few correlative studies have shown association of diabetic myocardial disease with poor glycemic control, while angiotensin converting enzyme inhibition may be protective. Summary Tissue Doppler imaging (and the related technique of strain rate imaging) appears to be extremely effective for the identification of subclinical LV dysfunction in diabetic patients It is hoped that the recognition of this condition will prompt specific therapy to prevent the development of overt LV dysfunction.

Metformin and serious adverse effects

Metformin, a biguanide derivative, has been used in the treatment of type 2 diabetes for nearly 50 years. It acts as an insulin-sensitising agent, lowering fasting plasma insulin concentrations by inducing greater peripheral uptake of glucose, as well as decreasing hepatic glucose output. In 1998, the United Kingdom Prospective Diabetes Study reported that, in overweight patients with type 2 diabetes, treatment with metformin compared with diet alone resulted in statistically significant absolute risk reductions (ARRs) in all-cause mortality (ARR, 7%), diabetes-related deaths (ARR, 5%), any diabetes-related endpoint (ARR, 10%), and macrovascular disease (myocardial infarction, sudden death, angina, stroke, peripheral vascular disease).1 This was achieved without hypoglycaemia or weight gain. As a result, metformin is now regarded as the oral hypoglycaemic agent of choice in the treatment of overweight people with type 2 diabetes.

Two new tools for assessing patients' knowledge and beliefs about obstructive sleep apnea and continuous positive airway pressure therapy

Background and purpose: Patients' knowledge and beliefs about their illnesses are known to influence a range of health related variables, including treatment compliance. It may, therefore, be important to quantify these variables to assess their impact on compliance, particularly in chronic illnesses such as Obstructive Sleep Apnea (OSA) that rely on self-administered treatments. The aim of this study was to develop two new tools, the Apnea Knowledge Test (AKT) and the Apnea Beliefs Scale (ABS), to assess illness knowledge and beliefs in OSA patients. Patients and methods: The systematic test construction process followed to develop the AKT and the ABS included consultation with sleep experts and OSA patients. The psychometric properties of the AKT and ABS were then investigated in a clinical sample of 81 OSA patients and 33 healthy, non-sleep disordered adults. Results: Results suggest both measures are easily understood by OSA patients, have adequate internal consistency, and are readily accepted by patients. A preliminary investigation of the validity of these tools, conducted by comparing patient data to that of the 33 healthy adults, revealed that apnea patients knew more about OSA, had more positive attitudes towards continuous positive airway pressure (CPAP) treatment, and attributed more importance to treating sleep disturbances than non-clinical groups. Conclusions: Overall, the results of psychometric analyses of these tests suggest these measures will be useful clinical tools with numerous beneficial applications, particularly in CPAP compliance studies and apnea education program evaluations. (C) 2004 Elsevier B.V. All rights reserved.