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《Pancreatology》2022,22(8):1175-1180
BackgroundHepatic steatosis has been described as a common finding in adults following total pancreatectomy with islet autotransplantation (TPIAT) but it is unknown if this occurs in children and adolescents.ObjectivesTo define the frequency of post-TPIAT hepatic steatosis in a sample of children and adolescents and to identify clinical predictors of incident steatosis post-TPIAT.MethodsIn this prospective study, consecutive participants at least 1-month post-TPIAT underwent a liver MRI with proton density fat fraction (PDFF) and blood draw at our pediatric academic medical center between April 2021 and January 2022. Comparison clinical pre-TPIAT liver MRI or ultrasound and insulin use and graft function data were extracted from the medical record. T-tests were used for the comparison of means across continuous variables between participants with and without post-TPIAT steatosis.ResultsA total of 20 participants (mean: 13 ± 4 years; 12 female) were evaluated. Mean liver PDFF at research MRI was 7.4 ± 6.2% (range: 2–25%). Seven participants (35%) had categorical hepatic steatosis (PDFF>5%) post-TPIAT, five of whom had pre-TPIAT steatosis, reflecting a 13% (2/15; 95% CI: 2–40%) incidence of post-TPIAT steatosis. Participant characteristics were not significantly different between subgroups with and without post-TPIAT steatosis. Mean PDFF at research MRI was not different between graft function subgroups (7.5% optimal/good vs. 7.3% marginal/failure; p = .96).ConclusionOur study shows a moderate prevalence but low incidence of hepatic steatosis in a small sample of children and adolescents post-TPIAT. This study raises questions about a causal relationship between TPIAT and hepatic steatosis. 相似文献
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In this article, we draw on recent scholarly work in the poststructuralist analysis of policy to consider how policy itself functions as a key site in the constitution of alcohol ‘problems’, and the political implications of these problematisations. We do this by examining Australian alcohol policy as it relates to young adults (18–24 years old). Our critical analysis focuses on three national alcohol policies (1990, 2001 and 2006) and two Victorian state alcohol policies (2008 and 2013), which together span a 25-year period. We argue that Australian alcohol policies have conspicuously ignored young adult men, despite their ongoing over-representation in the statistical ‘evidence base’ on alcohol-related harm, while increasingly problematising alcohol consumption amongst other population subgroups. We also identify the development of a new problem representation in Australian alcohol policy, that of ‘intoxication’ as the leading cause of alcohol-related harm and rising hospital admissions, and argue that changes in the classification and diagnosis of intoxication may have contributed to its prioritisation and problematisation in alcohol policy at the expense of other forms of harm. Finally, we draw attention to how preliminary and inconclusive research on the purported association between binge drinking and brain development in those under 25 years old has been mobilised prematurely to support calls to increase the legal purchasing age from 18 to 21 years. Our critical analysis of the treatment of these three issues – gender, intoxication, and brain development – is intended to highlight the ways in which policy functions as a key site in the constitution of alcohol ‘problems’. 相似文献
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《Diagnostic and interventional imaging》2020,101(9):555-564
PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%. 相似文献
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