803 resultados para diabetes mellitus
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Non Alcoholic Fatty Liver Disease (NAFLD) is a condition that is frequently seen but seldom investigated. Until recently, NAFLD was considered benign, self-limiting and unworthy of further investigation. This opinion is based on retrospective studies with relatively small numbers and scant follow-up of histology data. (1) The prevalence for adults, in the USA is, 30%, and NAFLD is recognized as a common and increasing form of liver disease in the paediatric population (1). Australian data, from New South Wales, suggests the prevalence of NAFLD in “healthy” 15 year olds as being 10%.(2) Non-alcoholic fatty liver disease is a condition where fat progressively invades the liver parenchyma. The degree of infiltration ranges from simple steatosis (fat only) to steatohepatitis (fat and inflammation) steatohepatitis plus fibrosis (fat, inflammation and fibrosis) to cirrhosis (replacement of liver texture by scarred, fibrotic and non functioning tissue).Non-alcoholic fatty liver is diagnosed by exclusion rather than inclusion. None of the currently available diagnostic techniques -liver biopsy, liver function tests (LFT) or Imaging; ultrasound, Computerised tomography (CT) or Magnetic Resonance Imaging (MRI) are specific for non-alcoholic fatty liver. An association exists between NAFLD, Non Alcoholic Steatosis Hepatitis (NASH) and irreversible liver damage, cirrhosis and hepatoma. However, a more pervasive aspect of NAFLD is the association with Metabolic Syndrome. This Syndrome is categorised by increased insulin resistance (IR) and NAFLD is thought to be the hepatic representation. Those with NAFLD have an increased risk of death (3) and it is an independent predictor of atherosclerosis and cardiovascular disease (1). Liver biopsy is considered the gold standard for diagnosis, (4), and grading and staging, of non-alcoholic fatty liver disease. Fatty-liver is diagnosed when there is macrovesicular steatosis with displacement of the nucleus to the edge of the cell and at least 5% of the hepatocytes are seen to contain fat (4).Steatosis represents fat accumulation in liver tissue without inflammation. However, it is only called non-alcoholic fatty liver disease when alcohol - >20gms-30gms per day (5), has been excluded from the diet. Both non-alcoholic and alcoholic fatty liver are identical on histology. (4).LFT’s are indicative, not diagnostic. They indicate that a condition may be present but they are unable to diagnosis what the condition is. When a patient presents with raised fasting blood glucose, low HDL (high density lipoprotein), and elevated fasting triacylglycerols they are likely to have NAFLD. (6) Of the imaging techniques MRI is the least variable and the most reproducible. With CT scanning liver fat content can be semi quantitatively estimated. With increasing hepatic steatosis, liver attenuation values decrease by 1.6 Hounsfield units for every milligram of triglyceride deposited per gram of liver tissue (7). Ultrasound permits early detection of fatty liver, often in the preclinical stages before symptoms are present and serum alterations occur. Earlier, accurate reporting of this condition will allow appropriate intervention resulting in better patient health outcomes. References 1. Chalasami N. Does fat alone cause significant liver disease: It remains unclear whether simple steatosis is truly benign. American Gastroenterological Association Perspectives, February/March 2008 www.gastro.org/wmspage.cfm?parm1=5097 Viewed 20th October, 2008 2. Booth, M. George, J.Denney-Wilson, E: The population prevalence of adverse concentrations with adiposity of liver tests among Australian adolescents. Journal of Paediatrics and Child Health.2008 November 3. Catalano, D, Trovato, GM, Martines, GF, Randazzo, M, Tonzuso, A. Bright liver, body composition and insulin resistance changes with nutritional intervention: a follow-up study .Liver Int.2008; February 1280-9 4. Choudhury, J, Sanysl, A. Clinical aspects of Fatty Liver Disease. Semin in Liver Dis. 2004:24 (4):349-62 5. Dionysus Study Group. Drinking factors as cofactors of risk for alcohol induced liver change. Gut. 1997; 41 845-50 6. Preiss, D, Sattar, N. Non-alcoholic fatty liver disease: an overview of prevalence, diagnosis, pathogenesis and treatment considerations. Clin Sci.2008; 115 141-50 7. American Gastroenterological Association. Technical review on nonalcoholic fatty liver disease. Gastroenterology.2002; 123: 1705-25
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Objectives: This study examines the accuracy of Gestational Diabetes Mellitus (GDM) case-ascertainment in routinely collected data. Methods: Retrospective cohort study analysed routinely collected data from all births at Cairns Base Hospital, Australia, from 1 January 2004 to 31 December 2010 in the Cairns Base Hospital Clinical Coding system (CBHCC) and the Queensland Perinatal Data Collection (QPDC). GDM case ascertainment in the National Diabetes Services Scheme (NDSS) and Cairns Diabetes Centre (CDC) data were compared. Results: From 2004 to 2010, the specificity of GDM case-ascertainment in the QPDC was 99%. In 2010, only 2 of 225 additional cases were identified from the CDC and CBHCC, suggesting QPDC sensitivity is also over 99%. In comparison, the sensitivity of the CBHCC data was 80% during 2004–2010. The sensitivity of CDC data was 74% in 2010. During 2010, 223 births were coded as GDM in the QPDC, and the NDSS registered 247 women with GDM from the same postcodes, suggesting reasonable uptake on the NDSS register. However, the proportion of Aboriginal and Torres Strait Islander women was lower than expected. Conclusion: The accuracy of GDM case ascertainment in the QPDC appears high, with lower accuracy in routinely collected hospital and local health service data. This limits capacity of local data for planning and evaluation, and developing structured systems to improve post-pregnancy care, and may underestimate resources required. Implications: Data linkage should be considered to improve accuracy of routinely collected local health service data. The accuracy of the NDSS for Aboriginal and Torres Strait Islander women requires further evaluation.
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Background: Gestational diabetes mellitus (GDM) is increasing, along with obesity and type 2 diabetes (T2DM), with Aboriginal and Torres Strait Islander people* in Australia particularly affected. GDM causes serious complications in pregnancy, birth, and the longer term, for both women and their infants. Women diagnosed with GDM have an eightfold risk of developing T2DM after pregnancy, compared with women who have not had GDM. Indigenous women have an even higher risk, at a younger age, and progress more quickly from GDM to T2DM, compared to non-Indigenous women. If left undetected and untreated, T2DM can lead to heart disease, stroke, renal disease, kidney failure, amputations and blindness. A GDM diagnosis offers a ‘window of opportunity’ for diabetes health interventions and it is vital that acceptable and effective prevention, treatment, and post-pregnancy care are provided. Low rates of post-pregnancy screening for T2DM are reported among non-Aboriginal women in Australia and among Indigenous women in other countries, however data for Aboriginal women are scarce. Breastfeeding, a healthy diet, and exercise can also help to prevent T2DM, and together with T2DM screening are recommended elements of ‘post-pregnancy care’ for women with GDM, This paper describes methods for a data linkage study to investigate rates of post-pregnancy care among women with GDM. Methods/Design: This retrospective cohort includes all women who gave birth at Cairns Base Hospital in Far North Queensland, Australia, from 2004 to 2010, coded as having GDM in the Cairns Base Hospital Clinical Coding system. Data linkage is being conducted with the Queensland Perinatal Data Collection, and three laboratories. Hospital medical records are being reviewed to validate the accuracy of GDM case ascertainment, and gather information on breastfeeding and provision of dietary advice. Multiple logistic regression is being used to compare post-pregnancy care between Aboriginal and non-Aboriginal women, while adjusting for other factors may impact on post-pregnancy care. Survival analysis is being used to estimate the rates of progression from GDM to T2DM. Discussion: There are challenges to collecting post-pregnancy data for women with GDM. However, research is urgently needed to ensure adequate post-pregnancy care is provided for women with GDM in Australia.
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BACKGROUND: Diabetes in South Asia represents a different disease entity in terms of its onset, progression, and complications. In the present study, we systematically analyzed the medical research output on diabetes in South Asia. METHODS: The online SciVerse Scopus database was searched using the search terms "diabetes" and "diabetes mellitus" in the article Title, Abstract or Keywords fields, in conjunction with the names of each regional country in the Author Affiliation field. RESULTS: In total, 8478 research articles were identified. Most were from India (85.1%) and Pakistan (9.6%) and the contribution to the global diabetes research output was 2.1%. Publications from South Asia increased markedly after 2007, with 58.7% of papers published between 2000 and 2010 being published after 2007. Most papers were Research Articles (75.9%) and Reviews (12.9%), with only 90 (1.1%) clinical trials. Publications predominantly appeared in local national journals. Indian authors and institutions had the most number of articles and the highest h-index. There were 136 (1.6%) intraregional collaborative studies. Only 39 articles (0.46%) had >100 citations. CONCLUSIONS: Regional research output on diabetes mellitus is unsatisfactory, with only a minimal contribution to global diabetes research. Publications are not highly cited and only a few randomized controlled trials have been performed. In the coming decades, scientists in the region must collaborate and focus on practical and culturally acceptable interventional studies on diabetes mellitus.
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Despite being used since 1976, Delusions-Symptoms-States-Inventory/states of Anxiety and Depression (DSSI/sAD) has not yet been validated for use among people with diabetes. The aim of this study was to examine the validity of the personal disturbance scale (DSSI/sAD) among women with diabetes using Mater-University of Queensland Study of Pregnancy (MUSP) cohort data. The DSSI subscales were compared against DSM-IV disorders, the Mental Component Score of the Short Form 36 (SF-36 MCS), and Center for Epidemiologic Studies Depression Scale (CES-D). Factor analyses, odds ratios, receiver operating characteristic (ROC) analyses and diagnostic efficiency tests were used to report findings. Exploratory factor analysis and fit indices confirmed the hypothesized two-factor model of DSSI/sAD. We found significant variations in the DSSI/sAD domain scores that could be explained by CES-D (DSSI-Anxiety: 55%, DSSI-Depression: 46%) and SF-36 MCS (DSSI-Anxiety: 66%, DSSI-Depression: 56%). The DSSI subscales predicted DSM-IV diagnosed depression and anxiety disorders. The ROC analyses show that although the DSSI symptoms and DSM-IV disorders were measured concurrently the estimates of concordance remained only moderate. The findings demonstrate that the DSSI/sAD items have similar relationships to one another in both the diabetes and non-diabetes data sets which therefore suggest that they have similar interpretations.
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Background Symptoms of depression can be recurrent or limited to one episode. This study discusses the prospective association between psychological health, measured as change in depression symptoms, and the risk of diabetes mellitus in Australian women. Methods Data obtained from the Mater-University of Queensland Study of Pregnancy. Depression was measured using the Delusions-Symptoms: States Inventory. To examine possible transitions over time, depression was grouped into four categories and assessed at different phases over the 21-year period. Multiple logistic regression models and sensitivity analysis to assess the robustness of our analytical strategy were performed. Results Three hundred and one women reported diabetes 21 years after the index pregnancy. Almost one-third of the women who reported depression symptoms continued to report these at a subsequent follow-up (FU) phase. About 1 in 20 women who had not reported depression symptoms at the 5-year FU did so at the subsequent 14-year FU. In prospective analyses, we did not find a significant association between diabetes and negative change (not depressed to depressed, at subsequent phase); however, for women with positive history of symptoms of depression and women with persistent symptoms, there was a 1.97-fold (95% confidence interval [CI]: 1.14–3.40) to 2.23-fold (95% CI: 1.09–4.57) greater risk of diabetes. Conclusions Our study suggests that an increased risk of diabetes is significantly associated with persistent depression symptoms. It highlights the importance of recognizing depression symptoms in terms of women's psychological wellbeing and thus provides a basis for targeting those most at risk.
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Background Longitudinal studies examining the risk of depressive and anxiety disorders associated with diabetes are limited. This study examined the association between diabetes and the risk of depressive and anxiety disorders in Australian women using longitudinal data. Methods Datawere froma sample of women who were part of anAustralian pregnancy and birth cohort study. Data comprised self-reported diabetes mellitus and the subsequent reporting of depressive and anxiety disorders. Mood disorders were assessed according to the Diagnostic and Statistical Manual of Mental Disorders, fourth edition, obtained from participants using Composite International Diagnostic Interview (CIDI)-Auto (WHO WMH-CIDI CAPI, version 21.1.3). Multiple regression models with adjustment for important covariates were used. Results Women with diabetes had a higher lifetime prevalence of any depressive and/or anxiety disorder than women without diabetes. About 3 in 10 women with diabetes experienced a lifetime event of any depressive disorder, while 1 in 2 women with diabetes experienced a lifetime event of any anxiety disorder. In prospective analyses, diabetes was only significantly associated with a 30-day episode of any anxiety disorder (odds ratio [OR] 1.53, 95% confidence interval [CI] 1.09–2.15). In the case of lifetime disorders, diabetes was significantly associated with any depressive disorder (OR 1.37, 95% CI 1.03–1.84), major depressive disorder (OR 1.36, 95% CI 1.01–1.85), and posttraumatic stress disorder (OR 1.42, 95% CI 1.01–2.02). Conclusions The findings suggest that the presence of diabetes is a significant risk factor for women experiencing current anxiety disorders. However, in the case of depression, the association with diabetes only held for women who had experienced past episodes, there was no association with current depression. This suggests that the evidence is not strong enough to support a direct effect of diabetes as a cause of mood disorders.
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Introduction Behavioural interventions have been shown to improve outcomes in patients with type 1 diabetes mellitus (T1DM). There are a small number of studies that suggest text-messages (TM), native mobile applications (NMAs), and other mobile tools may be useful platforms for delivering behavioural interventions to adolescents. Aim The aim of this study was to explore, by way of a systematic review of available literature, (a) the outcomes of interventions using mobile technology for youth with T1DM and (b) what mobile technologies, functional design elements and aesthetic design elements have the best evidence to support their use. Methods A search of six online databases returned 196 unique results, of which 13 met the inclusion criteria. Results Four studies were randomised controlled trials (RCTs), and all others prospective cohort studies. TM (10) was the most common intervention technology, while NMAs were used in four studies. The most common outcome measured was HbA1c (9); however, only three studies showed a significant decrease. Similarly, the results reported for other outcome measures were mixed. The studies included in this review suggest that interventions which have data collection and clinician support functionality may be more effective in improving adherence and glycaemic control, but more evidence is needed. Further, the evidence base supporting the use of NMAs in T1DM management for adolescents is weak, with most studies adopting TM as the intervention tool. Overall, the studies lack adequate descriptions of their methodology, and better quality studies are required to inform future intervention design.