Hirschsprung-associated inflammatory bowel disease: A multicenter study from the APSA Hirschsprung disease interest group

Background/PurposeA small number of Hirschsprung disease (HD) patients develop inflammatory bowel disease (IBD)-like symptoms after pullthrough surgery. The etiology and pathophysiology of Hirschsprung-associated IBD (HD-IBD) remains unknown. This study aims to further characterize HD-IBD, to identify potential risk factors and to evaluate response to treatment in a large group of patients.MethodsRetrospective study of patients diagnosed with IBD after pullthrough surgery between 2000 and 2021 at 17 institutions. Data regarding clinical presentation and course of HD and IBD were reviewed. Effectiveness of medical therapy for IBD was recorded using a Likert scale.ResultsThere were 55 patients (78% male). 50% (n = 28) had long segment disease. Hirschsprung-associated enterocolitis (HAEC) was reported in 68% (n = 36). Ten patients (18%) had Trisomy 21. IBD was diagnosed after age 5 in 63% (n = 34). IBD presentation consisted of colonic or small bowel inflammation resembling IBD in 69% (n = 38), unexplained or persistent fistula in 18% (n = 10) and unexplained HAEC >5 years old or unresponsive to standard treatment in 13% (n = 7). Biological agents were the most effective (80%) medications. A third of patients required a surgical procedure for IBD.ConclusionMore than half of the patients were diagnosed with HD-IBD after 5 years old. Long segment disease, HAEC after pull through operation and trisomy 21 may represent risk factors for this condition. Investigation for possible IBD should be considered in children with unexplained fistulae, HAEC beyond the age of 5 or unresponsive to standard therapy, and symptoms suggestive of IBD. Biological agents were the most effective medical treatment.Level of EvidenceLevel 4     

穿刺技术的改进和创新是穴位埋线疗法的第三次飞跃

穴位埋线是长效针灸,是在传统针具和针法基础上建立和发展起来的,是针灸技术的发展和延伸,穴位埋线的核心技术是穿刺技术,穴位埋线的三大要素中,针具、埋藏物、穿刺技巧之间是互相影响、互相促进的。针具的改进成功实现了穴位埋线疗法的第一次飞跃,埋藏物的改进成功实现了穴位埋线疗法的第二次飞跃,穿刺技术的改进和创新是穴位埋线疗法的第三次飞跃。     

Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

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%.     

Treatment strategies for hypertension in patients with type 1 diabetes

ABSTRACT

Introduction

Type 1 diabetes mellitus (T1DM) is a chronic, autoimmune disease that is characterized by total absence of insulin production. Hypertension is a common comorbidity in T1DM with complex pathophysiology, while it is also a well-recognized risk factor for the development of cardiovascular disease (CVD), as well as other microvascular diabetic complications.