933 resultados para Glycemic control
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Background: This pilot study aimed to verify if glycemic control can be achieved in type 2 diabetes patients after acute myocardial infarction (AMI), using insulin glargine (iGlar) associated with regular insulin (iReg), compared with the standard intensive care unit protocol, which uses continuous insulin intravenous delivery followed by NPH insulin and iReg (St. Care). Patients and Methods: Patients (n = 20) within 24 h of AMI were randomized to iGlar or St. Care. Therapy was guided exclusively by capillary blood glucose (CBG), but glucometric parameters were also analyzed by blinded continuous glucose monitoring system (CGMS). Results: Mean glycemia was 141 +/- 39 mg/dL for St. Care and 132 +/- 42 mg/dL for iGlar by CBG or 138 +/- 35 mg/dL for St. Care and 129 +/- 34 mg/dL for iGlar by CGMS. Percentage of time in range (80-180 mg/dL) by CGMS was 73 +/- 18% for iGlar and 77 +/- 11% for St. Care. No severe hypoglycemia (<= 40 mg/dL) was detected by CBG, but CGMS indicated 11 (St. Care) and seven (iGlar) excursions in four subjects from each group, mostly in sulfonylurea users (six of eight patients). Conclusions: This pilot study suggests that equivalent glycemic control without increase in severe hyperglycemia may be achieved using iGlar with background iReg. Data outputs were controlled by both CBG and CGMS measurements in a real-life setting to ensure reliability. Based on CGMS measurements, there were significant numbers of glycemic excursions outside of the target range. However, this was not detected by CBG. In addition, the data indicate that previous use of sulfonylurea may be a potential major risk factor for severe hypoglycemia irrespective of the type of insulin treatment.
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This cross-sectional and quantitative study aimed to analyze the relationship among social support, adherence to non-pharmacological (diet and physical exercise) and pharmacological treatments (insulin and/or oral anti-diabetic medication) and clinical and metabolic control of 162 type 2 diabetes mellitus patients. Data were collected through instruments validated for Brazil. Social support was directly correlated with treatment adherence. Adherence to non-pharmacological treatment was inversely correlated with body mass index, and medication adherence was inversely correlated with diastolic blood pressure. There were no associations between social support and clinical and metabolic control variables. Findings indicate that social support can be useful to achieve treatment adherence. Studies with other designs should be developed to broaden the analysis of relations between social support and other variables.
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BACKGROUND Morbidity and mortality in T1DM depend on metabolic control, which is assessed by HbA1c measurements every 3-4 months. Patients' self-perception of glycemic control depends on daily blood glucose monitoring. Little is known about the congruence of patients' and professionals' perception of metabolic control in T1DM. OBJECTIVE To assess the actual patients' self-perception and objective assessment (HbA1c) of metabolic control in T1DM children and adolescents and to investigate the possible factors involved in any difference. METHODS Patients with T1DM aged 8 - 18 years were recruited in a cross-sectional, retrospective and prospective cohort study. Data collection consisted of clinical details, measured HbA1c, self-monitored blood glucose values and questionnaires assessing self and professionals' judgment of metabolic control. RESULTS 91 patients participated. Mean HbA1c was 8.03%. HbA1c was higher in patients with a diabetes duration > 2 years (p = 0.025) and in patients of lower socioeconomic level (p = 0.032). No significant correlation was found for self-perception of metabolic control in well and poorly controlled patients. We found a trend towards false-positive memory of the last HbA1c in patients with a HbA1c > 8.5% (p = 0.069) but no difference in patients' knowledge on target HbA1c between well and poorly controlled patients. CONCLUSIONS T1DM patients are aware of a target HbA1c representing good metabolic control. Ill controlled patients appear to have a poorer recollection of their HbA1c. Self-perception of actual metabolic control is similar in well and poorly controlled T1DM children and adolescents. Therefore, professionals should pay special attention that ill controlled T1DM patients perceive their HbA1c correctly.
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ntroduction: The ProAct study has shown that a pump switch to the Accu-Chek® Combo system (Roche Diagnostics Deutschland GmbH, Mannheim, Germany) in type 1 diabetes patients results in stable glycemic control with significant improvements in glycated hemoglobin (HbA1c) in patients with unsatisfactory baseline HbA1c and shorter pump usage time. Patients and Methods: In this post hoc analysis of the ProAct database, we investigated the glycemic control and glycemic variability at baseline by determination of several established parameters and scores (HbA1c, hypoglycemia frequency, J-score, Hypoglycemia and Hyperglycemia Indexes, and Index of Glycemic Control) in participants with different daily bolus and blood glucose measurement frequencies (less than four day, four or five per day, and more than five per day, in both cases). The data were derived from up to 299 patients (172 females, 127 males; age [mean±SD], 39.4±15.2 years; pump treatment duration, 7.0±5.2 years). Results: Participants with frequent glucose readings had better glycemic control than those with few readings (more than five readings per day vs. less than four readings per day: HbA1c, 7.2±1.1% vs. 8.0±0.9%; mean daily blood glucose, 151±22 mg/dL vs. 176±30 mg/dL; percentage of readings per month >300 mg/dL, 10±4% vs. 14±5%; percentage of readings in target range [80-180 mg/dL], 59% vs. 48% [P<0.05 in all cases]) and had a lower glycemic variability (J-score, 49±13 vs. 71±25 [P<0.05]; Hyperglycemia Index, 0.9±0.5 vs. 1.9±1.2 [P<0.05]; Index of Glycemic Control, 1.9±0.8 vs. 3.1±1.6 [P<0.05]; Hypoglycemia Index, 0.9±0.8 vs. 1.2±1.3 [not significant]). Frequent self-monitoring of blood glucose was associated with a higher number of bolus applications (6.1±2.2 boluses/day vs. 4.5±2.0 boluses/day [P<0.05]). Therefore, a similar but less pronounced effect on glycemic variability in favor of more daily bolus applications was observed (more than five vs. less than four bolues per day: J-score, 57±17 vs. 63±25 [not significant]; Hypoglycemia Index, 1.0±1.0 vs. 1.5±1.4 [P<0.05]; Hyperglycemia Index, 1.3±0.6 vs. 1.6±1.1 [not significant]; Index of Glycemic Control, 2.3±1.1 vs. 3.1±1.7 [P<0.05]). Conclusions: Pump users who perform frequent daily glucose readings have a better glycemic control with lower glycemic variability.
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La diabetes mellitus es un trastorno del metabolismo de los carbohidratos producido por la insuficiente o nula producción de insulina o la reducida sensibilidad a esta hormona. Es una enfermedad crónica con una mayor prevalencia en los países desarrollados debido principalmente a la obesidad, la vida sedentaria y disfunciones en el sistema endocrino relacionado con el páncreas. La diabetes Tipo 1 es una enfermedad autoinmune en la que son destruidas las células beta del páncreas, que producen la insulina, y es necesaria la administración de insulina exógena. Un enfermo de diabetes Tipo 1 debe seguir una terapia con insulina administrada por la vía subcutánea que debe estar adaptada a sus necesidades metabólicas y a sus hábitos de vida, esta terapia intenta imitar el perfil insulínico de un páncreas no patológico. La tecnología actual permite abordar el desarrollo del denominado “páncreas endocrino artificial”, que aportaría precisión, eficacia y seguridad para los pacientes, en cuanto a la normalización del control glucémico y reducción del riesgo de hipoglucemias. Permitiría que el paciente no estuviera tan pendiente de su enfermedad. El páncreas artificial consta de un sensor continuo de glucosa, una bomba de infusión de insulina y un algoritmo de control, que calcula la insulina a infusionar usando la glucosa como información principal. Este trabajo presenta un método de control en lazo semi-cerrado mediante un sistema borroso experto basado en reglas. La regulación borrosa se fundamenta en la ambigüedad del lenguaje del ser humano. Esta incertidumbre sirve para la formación de una serie de reglas que representan el pensamiento humano, pero a la vez es el sistema que controla un proceso, en este caso el sistema glucorregulatorio. Este proyecto está enfocado en el diseño de un controlador borroso que haciendo uso de variables como la glucosa, insulina y dieta, sea capaz de restaurar la función endocrina del páncreas de forma tecnológica. La validación del algoritmo se ha realizado principalmente mediante experimentos en simulación utilizando una población de pacientes sintéticos, evaluando los resultados con estadísticos de primer orden y algunos más específicos como el índice de riesgo de Kovatchev, para después comparar estos resultados con los obtenidos por otros métodos de control anteriores. Los resultados demuestran que el control borroso (FBPC) mejora el control glucémico con respecto a un sistema predictivo experto basado en reglas booleanas (pBRES). El FBPC consigue reducir siempre la glucosa máxima y aumentar la mínima respecto del pBRES pero es en terapias desajustadas, donde el FBPC es especialmente robusto, hace descender la glucosa máxima 8,64 mg/dl, el uso de insulina es 3,92 UI menor, aumenta la glucosa mínima 3,32 mg/dl y lleva al rango de glucosa 80 – 110 mg/dl 15,33 muestras más. Por lo tanto se puede concluir que el FBPC realiza un mejor control glucémico que el controlador pBRES haciéndole especialmente efectivo, robusto y seguro en condiciones de desajustes de terapia basal y con gran capacidad de mejora futura. SUMMARY The diabetes mellitus is a metabolic disorder caused by a poor or null insulin secretion or a reduced sensibility to insulin. Diabetes is a chronic disease with a higher prevalence in the industrialized countries, mainly due to obesity, the sedentary life and endocrine disfunctions connected with the pancreas. Type 1 diabetes is a self-immune disease where the beta cells of the pancreas, which are the responsible of secreting insulin, are damaged. Hence, it is necessary an exogenous delivery of insulin. The Type 1 diabetic patient has to follow a therapy with subcutaneous insulin administration which should be adjusted to his/her metabolic needs and life style. This therapy tries to mimic the insulin profile of a non-pathological pancreas. Current technology lets the development of the so-called endocrine artificial pancreas that would provide accuracy, efficiency and safety to patients, in regards to the glycemic control normalization and reduction of the risk of hypoglycemic. In addition, it would help the patient not to be so concerned about his disease. The artificial pancreas has a continuous glucose sensor, an insulin infusion pump and a control algorithm, that calculates the insulin infusion using the glucose as main information. This project presents a method of control in semi-closed-loop, through an expert fuzzy system based on rules. The fuzzy regulation is based on the human language ambiguity. This uncertainty serves for construction of some rules that represent the human language besides it is the system that controls a process, in this case the glucoregulatory system. This project is focus on the design of a fuzzy controller that, using variables like glucose insulin and diet, will be able to restore the pancreas endocrine function with technology. The algorithm assessment has mainly been done through experiments in simulation using a population of synthetic patients, evaluating the results with first order statistical parameters and some other more specific such as the Kovatchev risk index, to compare later these results with the ones obtained in others previous methods of control. The results demonstrate that the fuzzy control (FBPC) improves the glycemic control connected with a predictive expert system based on Booleans rules (pBRES). The FBPC is always able to reduce the maximum level of glucose and increase the minimum level as compared with pBRES but it is in unadjusted therapies where FBPC is especially strong, it manages to decrease the maximum level of glucose and insulin used by 8,64 mg/dl and 3,92 UI respectively, also increases the value of minimum glucose by 3,32 mg/dl, getting 15,33 samples more inside the 80-110 mg/dl glucose rank. Therefore we can conclude that FBPC achieves a better glycemic control than the controller pBRES doing it especially effective, robust and safe in conditions of mismatch basal therapy and with a great capacity for future improvements.
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Introducción: En España, cerca del 14% de la población es diabética y el 95% corresponde a DM2. Un pobre control glucémico provoca un aumento de la morbilidad y mortalidad. Tres son los pilares en el tratamiento de la DM2: la dieta, la medicación y el ejercicio físico, sin embargo, el potencial de la prescripción de entrenamiento físico no ha sido totalmente explotado. Objetivo: Analizar el efecto de las distintas modalidades de ejercicio físico (AE, RT, Combo, INT) en el control glucémico en pacientes con diabetes mellitus tipo 2. Métodos: La búsqueda bibliográfica se realizó en 3 bases de datos electrónicas (Pubmed, Scopus y Proquest), incluyendo publicaciones desde enero de 2011 hasta mayo de 2014, que realizaran la intervención con AE, RT, Combo o INT, y que midieran la glucemia a través de la glucosa capilar, CGMS o HbA1c. Resultados: Del total de 386 artículos encontrados, 14 cumplieron los criterios de inclusión. Estos artículos fueron clasificados atendiendo a la modalidad de ejercicio físico de la intervención (AE, RT, Combo, INT), y en función de si analizaban el control glucémico como consecuencia del entrenamiento a largo plazo o tras una sesión de entrenamiento. Conclusiones: El AE, RT, Combo e INT muestran eficacia en el control glucémico tanto en el entrenamiento prolongado como en las 24-48h post-entrenamiento. Es necesaria la prescripción de un entrenamiento estructurado con una frecuencia, volumen e intensidad determinados para lograr beneficios en el control glucémico. El combo es la modalidad que obtiene mejores resultados a través del entrenamiento a largo plazo.
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OBJECTIVE Cannabidiol (CBD) and D9-tetrahydrocannabivarin (THCV) are nonpsychoactive phytocannabinoids affecting lipid and glucose metabolism in animal models. This study set out to examine the effects of these compounds in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS In this randomized, double-blind, placebo-controlled study, 62 subjects with noninsulin-treated type 2 diabetes were randomized to five treatment arms: CBD (100 mg twice daily), THCV (5 mg twice daily), 1:1 ratio of CBD and THCV (5 mg/5 mg, twice daily), 20:1 ratio of CBD and THCV (100 mg/5 mg, twice daily), or matched placebo for 13 weeks. The primary end point was a change in HDL-cholesterol concentrations from baseline. Secondary/tertiary end points included changes in glycemic control, lipid profile, insulin sensitivity, body weight, liver triglyceride content, adipose tissue distribution, appetite, markers of inflammation, markers of vascular function, gut hormones, circulating endocannabinoids, and adipokine concentrations. Safety and tolerability end points were also evaluated. RESULTS Compared with placebo, THCV significantly decreased fasting plasma glucose (estimated treatment difference [ETD] = 21.2 mmol/L; P < 0.05) and improved pancreatic b-cell function (HOMA2 b-cell function [ETD = 244.51 points; P < 0.01]), adiponectin (ETD = 25.9 3 106 pg/mL; P < 0.01), and apolipoprotein A (ETD = 26.02 mmol/L; P < 0.05), although plasma HDL was unaffected. Compared with baseline (but not placebo), CBD decreased resistin (2898 pg/ml; P < 0.05) and increased glucose-dependent insulinotropic peptide (21.9 pg/ml; P < 0.05). None of the combination treatments had a significant impact on end points. CBD and THCV were well tolerated. CONCLUSIONS THCV could represent a newtherapeutic agent in glycemic control in subjects with type 2 diabetes.
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Abstract Objectives: To assess the adherence to therapeutic regimen; to determine the Hemoglobin Glycation Index (HbA1c); to analyse the relationship that exists between the adherence to therapeutic regimen and metabolic control. Design: correlational analytical study, carried out according to a cross-sectional perspective. Participants: A non-probabilistic sample of 266 people with type 1 diabetes aged between 18 and 78 years old (mean M = 51.02 ± SD = 18.710), attending follow-up diabetes consultations. Mostly male individuals (51.88%), with low schooling level (50.75% had only inished elementar school). Measuring Instruments: We used the following data collection tools: a questionnaire on clinical and socio-demographic data, blood analysis of venous blood to determine the glycated hemoglobin level (HbA1c).Three self-report scales were used: Accession to Diabetes Treatment (Matos, 1999), Self-perception Scale (Vaz Serra, 1986) and Social Support Scale (Matos & Rodrigues, 2000). Results: In a sample in which the mean disease duration is 12.75 years, 69.17% of the sample run glycemic control tests between once a day and four times a year and 42.86% of them undergo insulin treatment. In the last 3 weeks, 26.32% of these people have experienced an average of 4.22 to 44.36%, hypoglycemic crises and experienced an average of 6.18 hyperglycemic crises. 57% of the individuals have showed a poor metabolic control (mean HbA1c higher than 7.5% (HbA1c mean M ≥ 7.50%). The mean psychosocial proile revealed individuals who show a decent self-esteem (M = 70.81) and acceptable social support (M = 58.89). Conclusions: The results suggest we should develop a kind of investigation that could be used to monitor the strenght of the mediation effect effect of the psychosocial predictive dimension of the adherence, since it has become essential to support a multidisciplinary approach which center lays in the promotion of a co-responsible self-management from the person who suffers from diabetes. This will enable a better quality of life; fewer years of people’s lives lost prematurely and a better health with less economical costs for citizens and healthcare systems.
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Improved glycemic control is the only treatment that has been shown to be effective for diabetic peripheral neuropathy in patients with type 1 diabetes (1). Continuous subcutaneous insulin infusion (CSII) is superior to multiple daily insulin injection (MDI) for reducing HbA1c and hypoglycemic events (2). Here, we have compared the benefits of CSII compared withMDI for neuropathy over 24months....
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Background: The prevalence of type 2 diabetes is rising with the majority of patients practicing inadequate disease self-management. Depression, anxiety, and diabetes-specific distress present motivational challenges to adequate self-care. Health systems globally struggle to deliver routine services that are accessible to the entire population, in particular in rural areas. Web-based diabetes self-management interventions can provide frequent, accessible support regardless of time and location Objective: This paper describes the protocol of an Australian national randomized controlled trial (RCT) of the OnTrack Diabetes program, an automated, interactive, self-guided Web program aimed to improve glycemic control, diabetes self-care, and dysphoria symptoms in type 2 diabetes patients. Methods: A small pilot trial is conducted that primarily tests program functionality, efficacy, and user acceptability and satisfaction. This is followed by the main RCT, which compares 3 treatments: (1) delayed program access: usual diabetes care for 3 months postbaseline followed by access to the full OnTrack Diabetes program; (2) immediate program: full access to the self-guided program from baseline onward; and (3) immediate program plus therapist support via Functional Imagery Training (FIT). Measures are administered at baseline and at 3, 6, and 12 months postbaseline. Primary outcomes are diabetes self-care behaviors (physical activity participation, diet, medication adherence, and blood glucose monitoring), glycated hemoglobin A1c (HbA1c) level, and diabetes-specific distress. Secondary outcomes are depression, anxiety, self-efficacy and adherence, and quality of life. Exposure data in terms of program uptake, use, time on each page, and program completion, as well as implementation feasibility will be conducted. Results: This trial is currently underway with funding support from the Wesley Research Institute in Brisbane, Australia. Conclusions: This is the first known trial of an automated, self-guided, Web-based support program that uses a holistic approach in targeting both type 2 diabetes self-management and dysphoria. Findings will inform the feasibility of implementing such a program on an ongoing basis, including in rural and regional locations.
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Insulin is used in all subjects with Type 1 diabetes, and when Type 2 diabetes is not controlled by oral anti-diabetic medicines, insulin is also used in Type 2 diabetes. However, despite this use, there is still increased mortality and morbidity in subjects with diabetes, compared to subjects without diabetes. One of the factors, which may be involved in this increased mortality and morbidity in subjects with diabetes, is nonadherence to insulin. Nonadherence rates to insulin are in the range20-38%, and many factors contribute to the nonadherence. The major aim of the review was to determine whether interventions to improve adherence to insulin do actually improve adherence to insulin. Most studies have shown that adherence to insulin was improved by changing from the vial-and-syringe approach to prefilled insulin pens, but not all studies have shown that this translated into better glycemic control and clinical outcomes. The results of studies using automatic telephone messages to improve adherence to insulin to date are inconclusive. There is limited and variable evidence that an intervention by a nurse/educator, which discusses adherence to medicines, does improve adherence to insulin. In contrast, there is little or no evidence that an extra intervention by a doctor or an intervention by a pharmacist, which discusses adherence to insulin, does actually improve the measured adherence to insulin. In conclusion, rather than assuming that an intervention by a health professional discussing adherence to insulin actually improves adherence to insulin, long-term studies investigating this are required.
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Purpose The aim of this study was to determine alterations to the corneal subbasal nerve plexus (SNP) over four years using in vivo corneal confocal microscopy (IVCM) in participants with type 1 diabetes and to identify significant risk factors associated with these alterations. Methods A cohort of 108 individuals with type 1 diabetes and no evidence of peripheral neuropathy at enrollment underwent laser-scanning IVCM, ocular screening, and health and metabolic assessment at baseline and the examinations continued for four subsequent annual visits. At each annual visit, eight central corneal images of the SNP were selected and analyzed to quantify corneal nerve fiber density (CNFD), branch density (CNBD) and fiber length (CNFL). Linear mixed model approaches were fitted to examine the relationship between risk factors and corneal nerve parameters. Results A total of 96 participants completed the final visit and 91 participants completed all visits. No significant relationships were found between corneal nerve parameters and time, sex, duration of diabetes, smoking, alcohol consumption, blood pressure or BMI. However, CNFD was negatively associated with HbA1c (β=-0.76, P<0.01) and age (β=-0.13, P<0.01) and positively related to high density lipids (HDL) (β=2.01, P=0.03). Higher HbA1c (β=-1.58, P=0.04) and age (β=-0.23, P<0.01) also negatively impacted CNBD. CNFL was only affected by higher age (β=-0.06, P<0.01). Conclusions Glycemic control, HDL and age have significant effects on SNP structure. These findings highlight the importance of diabetic management to prevent corneal nerve damage as well as the capability of IVCM for monitoring subclinical alterations in the corneal SNP in diabetes.
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The prevalence of latent autoimmune diabetes in adults (LADA) in patients diagnosed with type 2 diabetes mellitus (T2DM) ranges from 7 to 10% (1). They present at a younger age and have a lower BMI but poorer glycemic control, which may increase the risk of complications (2). However, a recent analysis of the Collaborative Atorvastatin Diabetes Study (CARDS) has demonstrated no difference in macrovascular or microvascular events between patients with LADA and T2DM, but neuropathy was not assessed (3). Previous studies quantifying neuropathy in patients with LADA are limited. In this study, we aimed to accurately quantify neuropathy in subjects with LADA compared with matched patients with T2DM.
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Introduction: The epidemic of obesity has been accompanied by an increase in the prevalence of the metabolic syndrome, type 2 diabetes, and non-alcoholic fatty liver disease (NAFLD). However, not all obese subjects develop these metabolic abnormalities. Hepatic fat accumulation is related to hepatic insulin resistance, which in turn leads to hyperglycemia, hypertriglyceridemia, and a low HDL cholesterol con-centration. The present studies aimed to investigate 1) how intrahepatic as compared to intramyocellular fat is related to insulin resistance in these tissues and to the metabolic syndrome (Study I); 2) the amount of liver fat in subjects with and without the metabolic syndrome, and which clinically available markers best reflect liver fat content (Study II); 3) the effect of liver fat on insulin clearance (Study III); 4) whether type 2 diabetic patients have more liver fat than age-, gender-, and BMI-matched non-diabetic subjects (Study IV); 5) how type 2 diabetic patients using exceptionally high doses of insulin respond to addition of a PPARγ agonist (Study V). Subjects and methods: The study groups consisted of 45 (Study I), 271 (Study II), and 80 (Study III) non-diabetic subjects, and of 70 type 2 diabetic patients and 70 matched control subjects (Study IV). In Study V, a total of 14 poorly controlled type 2 diabetic patients treated with high doses of insulin were studied before and after rosiglitazone treatment (8 mg/day) for 8 months. In all studies, liver fat content was measured by proton magnetic resonance spectroscopy, and sub-cutaneous and intra-abdominal fat content by MRI. In addition, circulating markers of insulin resistance and serum liver enzyme concentrations were determined. Hepatic (i.v. insulin infusion rate 0.3 mU/kg∙min combined with [3-3H]glucose, Studies I, III, and V) and muscle (1.0 mU/kg min, Study I) insulin sensitivities were measured by the euglycemic hyperinsulinemic clamp technique. Results: Fat accumulation in the liver rather than in skeletal muscle was associated with features of insulin resistance, i.e. increased fasting serum (fS) triglycerides and decreased fS-HDL cholesterol, and with hyperinsulinemia and low adiponectin concentrations (Study I). Liver fat content was 4-fold higher in subjects with as compared to those without the metabolic syndrome, independent of age, gender, and BMI. FS-C-peptide was the best correlate of liver fat (Study II). Increased liver fat was associated with both impaired insulin clearance and hepatic insulin resistance independent of age, gender, and BMI (Study III). Type 2 diabetic patients had 80% more liver fat than age-, weight-, and gender-matched non-diabetic subjects. At any given liver fat content, S-ALT underestimated liver fat in the type 2 diabetic patients as compared to the non-diabetic subjects (Study IV). In Study V, hepatic insulin sensitivity increased and glycemic control improved significantly during rosiglitazone treatment. This was associated with lowering of liver fat (on the average by 46%) and insulin requirements (40%). Conclusions: Liver fat is increased both in the metabolic syndrome and type 2 diabetes independent of age, gender, and BMI. A fatty liver is associated with both hepatic insulin resistance and impaired insulin clearance. Rosi-glitazone may be particularly effective in type 2 diabetic patients who are poorly controlled despite using high insulin doses.
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Introduction: The pathogenesis of diabetic nephropathy remains a matter of debate, although strong evidence suggests that it results from the interaction between susceptibility genes and the diabetic milieu. The true pathogenetic mechanism remains unknown, but a common denominator of micro- and macrovascular complications may exist. Some have suggested that low-grade inflammation and activation of the innate immune system might play a synergistic role in the pathogenesis of diabetic nephropathy. Aims of the study: The present studies were undertaken to investigate whether low-grade inflammation, mannan-binding lectin (MBL) and α-defensin play a role, together with adiponectin, in patients with type 1 diabetes and diabetic nephropathy. Subjects and methods: This study is part of the ongoing Finnish Diabetic Nephropathy Study (FinnDiane). The first four cross-sectional substudies of this thesis comprised 194 patients with type 1 diabetes divided into three groups (normo-, micro-, and macroalbuminuria) according to their albumin excretion rate (AER). The fifth substudy aimed to determine whether baseline serum adiponectin plays a role in the development and progression of diabetic nephropathy. This follow-up study included 1330 patients with type 1 diabetes and a mean follow-up period of five years. The patients were divided into three groups depending on their AER at baseline. As a measure of low-grade inflammation, highly sensitive CRP (hsCRP) and α-defensin were measured with radio-immunoassay, and interleukin-6 (IL-6) with high- sensitivity enzyme immuno-assay. Mannan-binding lectin and adiponectin were determined with time-resolved immunofluorometric assays. The progression of albuminuria from one stage to the other served as a measure of the progression of diabetic nephropathy. Results: Low-grade inflammatory markers, MBL, adiponectin, and α-defensin were all associated with diabetic nephropathy, whereas MBL, adiponectin, and α-defensin per se were unassociated with low-grade inflammatory markers. AER was the only clinical variable independently associated with hsCRP. AER, HDL-cholesterol and the duration of diabetes were independently associated with IL-6. HbA1c was the only variable independently associated with MBL. The estimated glomerular filtration rate (eGFR), AER, and waist-to-hip ratio were independently associated with adiponectin. Systolic blood pressure, HDL-cholesterol, total cholesterol, age, and eGFR were all independently associated with α-defensin. In patients with macroalbuminuria, progression to end-stage renal disease (ESRD) was associated with higher baseline adiponectin concentrations. Discussion and conclusions: Low-grade inflammation, MBL, adiponectin, and defensin were all associated with diabetic nephropathy in these cross-sectional studies. In contrast however, MBL, adiponectin, and defensin were not associated with low-grade inflammatory markers per se. Nor was defensin associated with MBL, which may suggest that these different players function in a coordinated fashion during the deleterious process of diabetic nephropathy. The question of what causes low-grade inflammation in patients with type 1 diabetes and diabetic nephropathy, however, remains unanswered. We could observe in our study that glycemic control, an atherosclerotic lipid profile, and waist-to-hip ratio (WHR) were associated with low-grade inflammation in the univariate analysis, although in the multivariate analysis, only AER, HDL-cholesterol, and the duration of diabetes, as a measure of glycemic load, proved to be independently associated with inflammation. Notably, all these factors are modifiable with changes in lifestyle and/or with a targeted medication. In the follow-up study, elevated serum adiponectin levels at baseline predicted the progression from macroalbuminuria to ESRD independently of renal function at baseline. This observation does not preclude adiponectin as a favorable factor during the process of diabetic nephropathy, since the rise in serum adiponectin concentrations may remain a mechanism by which the body compensates for the demands created by the diabetic milieu.