1,543 research outputs found

    Diabetic ketoacidosis complicated by the use of ecstasy: a case report

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    <p>Abstract</p> <p>Introduction</p> <p>Ecstasy (3,4-methylenedioxymethamphetamin), a hallucinogenic amphetamine, is often used by young people, especially at 'raves'. This illicit drug can cause many metabolic changes and its use, when associated with prolonged exercise, may exacerbate ketoacidosis in type 1 diabetic patients.</p> <p>Case presentation</p> <p>This is a case of ketoacidosis complicated by the use of ecstasy in a 19-year-old insulin-dependent diabetic Caucasian woman.</p> <p>Conclusion</p> <p>The use of ecstasy may trigger diabetic ketoacidosis in patients with a preexisting metabolic disorder</p

    Classification of patients with knee osteoarthritis in clinical phenotypes: data from the osteoarthritis initiative

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    <div><p>Objectives</p><p>The existence of phenotypes has been hypothesized to explain the large heterogeneity characterizing the knee osteoarthritis. In a previous systematic review of the literature, six main phenotypes were identified: Minimal Joint Disease (MJD), Malaligned Biomechanical (MB), Chronic Pain (CP), Inflammatory (I), Metabolic Syndrome (MS) and Bone and Cartilage Metabolism (BCM). The purpose of this study was to classify a sample of individuals with knee osteoarthritis (KOA) into pre-defined groups characterized by specific variables that can be linked to different disease mechanisms, and compare these phenotypes for demographic and health outcomes.</p><p>Methods</p><p>599 patients were selected from the OAI database FNIH at 24 months’ time to conduct the study. For each phenotype, cut offs of key variables were identified matching the results from previous studies in the field and the data available for the sample. The selection process consisted of 3 steps. At the end of each step, the subjects classified were excluded from the further classification stages. Patients meeting the criteria for more than one phenotype were classified separately into a ‘complex KOA’ group.</p><p>Results</p><p>Phenotype allocation (including complex KOA) was successful for 84% of cases with an overlap of 20%. Disease duration was shorter in the MJD while the CP phenotype included a larger number of Women (81%). A significant effect of phenotypes on WOMAC pain (F = 16.736 p <0.001) and WOMAC physical function (F = 14.676, p < 0.001) was identified after controlling for disease duration.</p><p>Conclusion</p><p>This study signifies the feasibility of a classification of KOA subjects in distinct phenotypes based on subgroup-specific characteristics.</p></div

    Gender, sex hormones and pulmonary hypertension

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    Most subtypes of pulmonary arterial hypertension (PAH) are characterized by a greater susceptibility to disease among females, although females with PAH appear to live longer after diagnosis. While this “estrogen paradoxȍ of enhanced female survival despite increased female susceptibility remains a mystery, recent progress has begun to shed light upon the interplay of sex hormones, the pathogenesis of pulmonary hypertension, and the right ventricular response to stress. For example, emerging data in humans and experimental models suggest that estrogens or differential sex hormone metabolism may modify disease risk among susceptible subjects, and that estrogens may interact with additional local factors such as serotonin to enhance the potentially damaging chronic effects of estrogens on the pulmonary vasculature. Regardless, it remains unclear why not all estrogenic compounds behave equally, nor why estrogens appear to be protective in certain settings but detrimental in others. The contribution of androgens and other compounds, such as dehydroepiandrosterone, to pathogenesis and possibly treatment must be considered as well. In this review, we will discuss the recent understandings on how estrogens, estrogen metabolism, dehydroepiandrosterone, and additional susceptibility factors may all contribute to the pathogenesis or potentially to the treatment of pulmonary hypertension, by evaluating current human, cell-based, and experimental model data
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