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Algorithm for the multidisciplinary management of hemorrhage in EUS-guided drainage for pancreatic fluid collections

机译:EUS引导的胰液收集引流中出血的多学科管理算法

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摘要

Pancreatic fluid collections (PFCs), common sequelae of acute or chronic pancreatitis, are broadly classified as pancreatic pseudocysts or walled-off necrosis according to the revised Atlanta classification. Endoscopic ultrasound (EUS)-guided drainage is often considered a standard first-line therapy preferable to surgical or interventional radiology approaches for patients with symptomatic PFC. EUS-guided drainage is effective and successful; it has a technical success rate of 90%-100% and a clinical success rate of 85%-98%. Recent studies have shown a 5%-30% adverse events (AEs) rate for the procedure. The most common AEs include infection, hemorrhage, perforation and stent migration. Hemorrhage, a severe and sometimes deadly outcome, requires a well-organized and appropriate treatment strategy. However, few studies have reported the integrated management of hemorrhage during EUS-guided drainage of PFC. Establishing a practical therapeutic strategy is an essential and significant step in standardized management. The aim of this review is to describe the current situation of EUS-guided drainage of PFCs, including the etiology and treatment of procedure-related bleeding as well as current problems and future perspectives. We propose a novel and meaningful algorithm for systematically managing hemorrhage events. To our limited knowledge, a multidisciplinary algorithm for managing EUS-guided drainage for PFC-related bleeding has not been previously reported.
机译:胰腺液集合(PFC)是急性或慢性胰腺炎的常见后遗症,根据经修订的亚特兰大分类,大致分为胰腺假性囊肿或壁坏死。对于有症状的PFC患者,内镜超声(EUS)引导引流通常被认为是优于手术或介入放射学方法的标准一线疗法。 EUS引导的引流是有效和成功的;它的技术成功率为90%-100%,临床成功率为85%-98%。最近的研究表明该手术的不良事件(AEs)发生率为5%-30%。最常见的不良事件包括感染,出血,穿孔和支架迁移。出血是一种严重的,有时甚至是致命的后果,需要有条理,适当的治疗策略。但是,很少有研究报道在EUS指导下的PFC引流期间对出血的综合处理。建立切实可行的治疗策略是标准化管理中必不可少的重要步骤。这篇综述的目的是描述EUS指导的PFC引流的现状,包括与手术相关的出血的病因和治疗以及当前的问题和未来的前景。我们提出了一种新颖而有意义的算法来系统地管理出血事件。据我们所知,以前还没有针对EUS引导的引流治疗PFC相关出血的多学科算法。

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