6 research outputs found
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Which growth standards should be used to identify large- and small-for-gestational age infants of mothers with type 1 diabetes? A pre-specified analysis of the CONCEPTT trial
Abstract: Background: Offspring of women with type 1 diabetes are at increased risk of fetal growth patterns which are associated with perinatal morbidity. Our aim was to compare rates of large- and small-for-gestational age (LGA; SGA) defined according to different criteria, using data from the Continuous Glucose Monitoring in Type 1 Diabetes Pregnancy Trial (CONCEPTT). Methods: This was a pre-specified analysis of CONCEPTT involving 225 pregnant women and liveborn infants from 31 international centres (ClinicalTrials.gov NCT01788527; registered 11/2/2013). Infants were weighed immediately at birth and GROW, INTERGROWTH and WHO centiles were calculated. Relative risk ratios, sensitivity and specificity were used to assess the different growth standards with respect to perinatal outcomes, including neonatal hypoglycaemia, hyperbilirubinaemia, respiratory distress, neonatal intensive care unit (NICU) admission and a composite neonatal outcome. Results: Accelerated fetal growth was common, with mean birthweight percentiles of 82.1, 85.7 and 63.9 and LGA rates of 62, 67 and 30% using GROW, INTERGROWTH and WHO standards respectively. Corresponding rates of SGA were 2.2, 1.3 and 8.9% respectively. LGA defined according to GROW centiles showed stronger associations with preterm delivery, neonatal hypoglycaemia, hyperbilirubinaemia and NICU admission. Infants born > 97.7th centile were at highest risk of complications. SGA defined according to INTERGROWTH centiles showed slightly stronger associations with perinatal outcomes. Conclusions: GROW and INTERGROWTH standards performed similarly and identified similar numbers of neonates with LGA and SGA. GROW-defined LGA and INTERGROWTH-defined SGA had slightly stronger associations with neonatal complications. WHO standards underestimated size in preterm infants and are less applicable for use in type 1 diabetes. Trial registration: This trial is registered with ClinicalTrials.gov. number NCT01788527. Trial registered 11/2/2013
Metabolic syndrome: a major risk factor for atherosclerosis in HIV-infected patients (SHIVA study).
International audienceOBJECTIVE: Metabolic syndrome (MetS) is directly related to a high incidence of cardiovascular disease in the general population. The association is more doubtful among HIV-infected patients, although MetS has an elevated prevalence in this population. We explored the impact of MetS on early atherosclerosis markers. RESEARCH DESIGN AND METHODS: All HIV-infected outpatients followed at the Brest University Hospital were included in this cross-sectional hospital-based study (SHIVA study, France) (n=154). The MetS status (NCEP ATPIII definition, at least three of these five criteria: fasting glucose, triglycerides, HDL-C, waist circumference and hypertension.) of each patient was analyzed (Mann-Whitney test) according to carotid intima-media thickness, number of plaques, and a combined cardiovascular score. RESULTS: After exclusion of 6 patients treated with statins or insulin or both, MetS status was available for 140 (90.9%) patients and positive for 10 (7.1%). MetS status was due predominantly to blood glucose and triglyceride levels and was strongly correlated with all atherosclerosis markers (p < or = 0.01). CONCLUSION: The MetS prevalence in this population is low for a group with HIV infection, even after inclusion of the statin-treated patients (11.4%), but remains higher than among the general population. MetS in this population is probably a heterogeneous cluster of side effects of antiretroviral therapy (high triglycerides, lower HDL-C, and hypertension) and direct effects of HIV (glucose disturbances). Because it is strongly linked to the presence of plaque and intimal thickness, it is a pertinent criterion for deciding about cardiovascular prevention
Prog Retin Eye Res
There is an urgency to find new treatment strategies that could prevent or delay the onset or progression of AMD. Different classes of lipids and lipoproteins metabolism genes have been associated with AMD in a multiple ways, but despite the ever-increasing knowledge base, we still do not understand fully how circulating lipids or local lipid metabolism contribute to AMD. It is essential to clarify whether dietary lipids, systemic or local lipoprotein metabolismtrafficking of lipids in the retina should be targeted in the disease. In this article, we critically evaluate what has been reported in the literature and identify new directions needed to bring about a significant advance in our understanding of the role for lipids in AMD. This may help to develop potential new treatment strategies through targeting the lipid homeostasis
Disruption prediction with artificial intelligence techniques in tokamak plasmas
In nuclear fusion reactors, plasmas are heated to very high temperatures of more than 100 million kelvin and, in so-called tokamaks, they are confined by magnetic fields in the shape of a torus. Light nuclei, such as deuterium and tritium, undergo a fusion reaction that releases energy, making fusion a promising option for a sustainable and clean energy source. Tokamak plasmas, however, are prone to disruptions as a result of a sudden collapse of the system terminating the fusion reactions. As disruptions lead to an abrupt loss of confinement, they can cause irreversible damage to present-day fusion devices and are expected to have a more devastating effect in future devices. Disruptions expected in the next-generation tokamak, ITER, for example, could cause electromagnetic forces larger than the weight of an Airbus A380. Furthermore, the thermal loads in such an event could exceed the melting threshold of the most resistant state-of-the-art materials by more than an order of magnitude. To prevent disruptions or at least mitigate their detrimental effects, empirical models obtained with artificial intelligence methods, of which an overview is given here, are commonly employed to predict their occurrence—and ideally give enough time to introduce counteracting measures