An Integrated Catheter Dressing for Early Detection of Catheter-related Bloodstream Infections

项目总结/摘要 导管相关血流感染（CRBSI），也称为导管相关败血症，是最常见的， 致命的，昂贵的并发症的中心静脉导管。CRBSI影响数亿人 仅在美国，每年就有超过250，000名患者受到影响。这些感染大多是由 通过在导管插入部位的患者皮肤植物群上发现的微生物的迁移。巨大 已经做出努力来减少导管相关的脓毒症，包括改进导管插入 指导方针和开发浸有抗生素的敷料。这些方法有助于减少 患者皮肤上的细菌数量，但不能消除它们。没有可用的导管敷料， 自动和早期检测导管插入部位的细菌生长。这种导管敷料是一种 迫切需要早期检测CRBSI，允许移除/更换导管，并且根据需要， 为患者提供量身定制的抗生素治疗。此外，它仍然是一个临床挑战，以检测 由于人体皮肤的高度柔韧性， 和地形自然。提供与皮肤的适形和无缝粘附的柔性生物传感器可以 帮助，但以前的研究对可穿戴和灵活的传感器的优点，以检测细菌感染已经 限于通过间接参数测量的伤口感染（例如，pH值）随饮食变化而变化 限制，而不是特定的细菌感染。因此，在使用 可穿戴和灵活的传感器与电子集成，用于实时监测 导管插入部位，以便早期检测CRBSI相关感染风险。本报告的总体目标 应用程序是通过开发一个完全集成的，无线操作的， 导管敷料能够实时监测导管插入部位的细菌生长， 从而能够自动早期检测源自皮肤的感染。核心假设是 可以直接测量导管插入部位活细菌的电化学活性，以及 可以使用机器学习对采集的数据进行分类，从而允许精确监测腔外 实时污染。为实现总体目标，将追求以下两个具体目标：目标1： 开发能够实时监测导管处细菌生长的集成导管敷料（ICD） 插入位点。目的2：改进和优化ICD，以早期检测皮肤上导管相关脓毒症 体模和动物模型。这些目标将由一个熟练的专家和优秀的团队来实现。 资源拟议的研究是重要的，因为ICD可以改变目前的床旁护理 实践，最终有可能降低感染风险，卫生保健成本，发病率和死亡率 与CRBSI相关的感染率，并实时、非侵入性和在护理点监测感染状态。

PROJECT SUMMARY/ABSTRACT Catheter-related bloodstream infection (CRBSI), also called catheter-related sepsis, is one of the most frequent, lethal, and costly complications of central venous catheterization. CRBSI affects hundreds of millions of people worldwide; in the U.S. alone, it affects more than 250,000 patients yearly. These infections are mostly caused by the migration of microorganisms found on the patient's skin flora at the catheter insertion site. Tremendous efforts have been undertaken to reduce catheter-related sepsis, including improvements to the catheter insertion guidelines and the development of dressings impregnated with antibiotics. These methods help reduce the number of bacteria on the patient's skin but do not eliminate them. No available catheter dressing enables automated and early detection of bacterial growth at the catheter insertion site. Such catheter dressing is a critical need for early detection of CRBSI, allowing for the removal/replacement of the catheter, and, as needed, for early treatment of patients with tailored antibiotic therapy. In addition, it remains a clinical challenge to detect bacterial colonization on the skin at early stages without catheter removal due to the human skin's highly flexible and topographical nature. Flexible biosensors that provide conformal and seamless adherence to the skin can help, but previous studies on the merits of wearable and flexible sensors to detect bacterial infection have been limited to wound infections measured by indirect parameters (e.g., pH) that are subject to change with dietary restrictions and not specific to bacterial infection. Therefore, a significant knowledge gap exists in the use of wearable and flexible sensors integrated with electronics for real-time monitoring of direct bacterial growth at the catheter insertion site for the early detection of CRBSI-related infection risks. The overall objective of this application is to address this need and knowledge gap by developing a fully integrated, wirelessly operated catheter dressing that is capable of monitoring bacterial growth at the catheter insertion site in real-time and non- invasively to enable automated early detection of infection originating from the skin. The central hypothesis is that the electrochemical activity of live bacteria at the catheter insertion site can be directly measured, and acquired data can be classified using machine learning, thereby allowing precise monitoring of extraluminal contamination in real-time. To attain the overall objective, the following two specific aims will be pursued: Aim 1: Develop an integrated catheter dressing (ICD) capable of real-time monitoring of bacterial growth at the catheter insertion site. Aim 2: Validate and optimize the ICD for early detection of catheter-related sepsis on a skin phantom and an animal model. These aims will be accomplished by a team of skilled experts and excellent resources. The proposed research is significant because the ICD can transform the current point-of-care practices, ultimately has the potential to reduce infection risks, health care costs, and morbidity and mortality rates related to CRBSI, and monitor the infection status in real-time, non-invasively, and at the point of care.