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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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目的探究组织气氛在护士吞咽障碍知识水平与护理行为之间的中介效应。方法2019年6-7月,便利抽样法选取15个省市33所医院及医疗机构神经科、康复科具有吞咽障碍护理经验的231名护士为研究对象采用脑卒中吞咽障碍知识水平问卷、脑卒中吞咽障碍护理行为问卷及团队创新气氛量表对其进行调查。结果护士吞咽障碍知识水平总分为(56.69±13.50)分、护理行为得分为(140.65土32.02)分、组织气氛得分为(157.63±26.56)分。组织气氛与吞咽障碍知识水平(r=0.49,P<0.01)、护理行为(r=0.50,P<0.01)均呈正相关。组织气氛在知识水平和护理行为之间起中介作用,中介效应占总效应的83.18%。结论组织气氛在护士吞咽障碍知识水平与护理行为之间起中介作用,临床管理者可在提升护士吞咽障碍知识水平的基础上,通过提高组织气氛水平推进其护理行为。  相似文献   
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Gut bacteria and gut barrier plays important roles in body homeostasis. Ciprofloxacin (CPFX) is widely used to treat bacterial infections. However, whether high dosage of CPFX has side effects on gut barrier integrity is still unclear. Our results indicated that the High CPFX treatment (1 mg/ml) caused weight loss, nervousness, anorexia, and increased apoptosis cells in gut, but less influence was observed in the Low CPFX group (0.2 mg/ml). Meanwhile, the High CPFX treatment impaired tight junction molecules Ocln/ZO-1 level and down-regulated antibacterial genes expression (reg3γ, pla2g2α and defb1). Further, the High CPFX treatment increased pro-inflammatory cytokine IL-1β in intestinal tract, decreased IL-17A of duodenum but increased IL-17A of colon at day 37. In addition, the gut bacterial diversity and richness behaved significantly loss regarding CPFX treatment, especially in the High CPFX group during the experiment. Indole exhibited sharply decline in both Low and High CPFX groups at day 7, and the High CPFX mice needed longer time on restoring indole level. Meanwhile, CPFX treatment strongly decreased the concentrations of butyric acid and valeric acid at day 1. Correlation analysis indicated that the linked patterns between the key bacteria (families Bacteroidales_S247, Ruminococcaceae and Desulfovibrionaceae) and metabolites (indole and butyric acid) were disturbed via the CPFX treatment. In conclusion, the High CPFX treatment impaired the gut barrier with the evidence of reduced expression of tight junction proteins, increased apoptosis cells and inflammatory cells, decreased the bacterial diversity and composition, which suggesting a proper antibiotic-dosage use should be carefully considered in disease treatment.  相似文献   
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目的:研究糖尿病护理门诊在糖尿病健康教育中作用.方法:取78例糖尿病患者,其中39例患者进行常规护理为对照组,39例患者进行糖尿病门诊护理为观察组,对比2组患者护理后自我管理能力和血糖指标.结果:观察组自我管理能力均高于对照组(P<0.05).观察组血糖指标均低于对照组(P<0.05).结论:向糖尿病患者进行健康教育时,糖尿病门诊护理的应用,可以科学创建护理档案,明确随访策略,提升糖尿病的管理水平,使患者具有较强自我管理能力,同时降低其血糖指标.  相似文献   
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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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