34 research outputs found

    Characterising paediatric mortality during and after acute illness in Sub-Saharan Africa and South Asia: a secondary analysis of the CHAIN cohort using a machine learning approach

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    Background A better understanding of which children are likely to die during acute illness will help clinicians and policy makers target resources at the most vulnerable children. We used machine learning to characterise mortality in the 30-days following admission and the 180-days after discharge from nine hospitals in low and middle-income countries (LMIC). Methods A cohort of 3101 children aged 2–24 months were recruited at admission to hospital for any acute illness in Bangladesh (Dhaka and Matlab Hospitals), Pakistan (Civil Hospital Karachi), Kenya (Kilifi, Mbagathi, and Migori Hospitals), Uganda (Mulago Hospital), Malawi (Queen Elizabeth Central Hospital), and Burkina Faso (Banfora Hospital) from November 2016 to January 2019. To record mortality, children were observed during their hospitalisation and for 180 days post-discharge. Extreme gradient boosted models of death within 30 days of admission and mortality in the 180 days following discharge were built. Clusters of mortality sharing similar characteristics were identified from the models using Shapley additive values with spectral clustering. Findings Anthropometric and laboratory parameters were the most influential predictors of both 30-day and post-discharge mortality. No WHO/IMCI syndromes were among the 25 most influential mortality predictors of mortality. For 30-day mortality, two lower-risk clusters (N = 1915, 61%) included children with higher-than-average anthropometry (1% died, 95% CI: 0–2), and children without signs of severe illness (3% died, 95% CI: 2–4%). The two highest risk 30-day mortality clusters (N = 118, 4%) were characterised by high urea and creatinine (70% died, 95% CI: 62–82%); and nutritional oedema with low platelets and reduced consciousness (97% died, 95% CI: 92–100%). For post-discharge mortality risk, two low-risk clusters (N = 1753, 61%) were defined by higher-than-average anthropometry (0% died, 95% CI: 0–1%), and gastroenteritis with lower-than-average anthropometry and without major laboratory abnormalities (0% died, 95% CI: 0–1%). Two highest risk post-discharge clusters (N = 267, 9%) included children leaving against medical advice (30% died, 95% CI: 25–37%), and severely-low anthropometry with signs of illness at discharge (46% died, 95% CI: 34–62%). Interpretation WHO clinical syndromes are not sufficient at predicting risk. Integrating basic laboratory features such as urea, creatinine, red blood cell, lymphocyte and platelet counts into guidelines may strengthen efforts to identify high-risk children during paediatric hospitalisations. Funding Bill & Melinda Gates Foundation OPP1131320

    Disturbed lipid metabolism in glycogen storage disease type 1

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    Glycogen storage disease type 1 (GSD1) is an inborn error of metabolism caused by deficiency of glucose-6-phosphatase, the enzyme catalysing the conversion of glucose-6-phosphate (G6P) to glucose. GSD1 is associated with severe hyperlipidaemia and hepatic steatosis. The underlying mechanisms responsible for these abnormalities in lipid metabolism are only partly known. This review summarises data available on hyperlipidaemia and steatosis in GSD1 and postulates new hypotheses for unresolved issues. Evidence indicates that lipid clearance from the blood compartment is decreased in GSD1. Furthermore, in two GSD1a patients synthesis of palmitate, an indicator of de novo lipogenesis, and cholesterol were found to be increased 40-fold and 7-fold, respectively. Elevated hepatic G6P levels may play a regulatory role in lipid synthesis via activation of transcription of lipogenic genes. In addition, accelerated glycolysis will supply acetyl-CoA molecules required for lipogenesis. It is as yet unclear whether hepatic secretion of lipids in the form of very low density lipoprotein-triglycerides (VLDL-TG) is altered in GSD1 patients: we recently found unaffected VLDL-TG secretion rates in an acute animal model of GSD1b. Hepatic steatosis, which is invariably present in GSD1 is probably mainly caused by an increased free fatty acid flux from adipose tissue to the liver and, to a limited extent, by increased de novo lipogenesis. Conclusion: future studies, using novel stable isotope methodologies, are warranted to further clarify the disturbances in lipid and lipoprotein metabolism in glycogen storage disease type I and the role of glucose-6-phosphate herein

    Hepatic de novo synthesis of glucose 6-phosphate is not affected in peroxisome proliferator-activated receptor alpha-deficient mice but is preferentially directed toward hepatic glycogen stores after a short term fast

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    Apart from impaired beta-oxidation, Pparalpha-deficient (Pparalpha(-/-)) mice suffer from hypoglycemia during prolonged fasting, suggesting alterations in hepatic glucose metabolism. We compared hepatic glucose metabolism in vivo in wild type (WT) and Pparalpha(-/-) mice after a short term fast, applying novel isotopic methods. After a 9-h fast, mice were infused with [U-C-13] glucose, [2-C-13] glycerol, [1-H-2]galactose, and paracetamol for 6 h, and blood and urine was collected in timed intervals. Plasma glucose concentrations remained constant and were not different between the groups. Hepatic glycogen content was 69 +/- 11 and 90 +/- 31 mumol/g liver after 15 h of fasting in WT and Pparalpha(-/-) mice, respectively. The gluconeogenic flux toward glucose 6-phosphate was not different between the groups (i.e. 157 +/- 9 and 153 +/- 9 mumol/kg/min in WT and Pparalpha(-/-) mice, respectively). The gluconeogenic flux toward plasma glucose, however, was decreased in PPARalpha(-/-) mice (i.e. 142 +/- 9 versus 124 +/- 13 mumol/kg/min) (p <0.05), accounting for the observed decrease (-15%) in hepatic glucose production in Pparα(-/-) mice. Expression of the gene encoding glucose-6-phosphate hydrolase (G6ph) was lower in the PPARα(-/-) mice compared with WT mice. In conclusion, Pparα(-/-) mice were able to maintain a normal total gluconeogenic flux to glucose 6-phosphate during moderate fasting, despite their inability to up-regulate β-oxidation. However, this gluconeogenic flux was directed more toward glycogen, leading to a decreased hepatic glucose output. This was associated with a down-regulation of the expression of G6ph in PPARα-deficient mice
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