Improving Chronic Wound healing with Intelligent Dressings

使用智能敷料改善慢性伤口愈合

• 批准号: EP/D505437/1
• 负责人: David Riley
• 金额: $ 68.16万
• 依托单位: University of Bristol
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2006
• 资助国家: 英国
• 起止时间: 2006 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FD505437%2F1
• 关键词: Improving; Chronic; Wound; healing; Intelligent

One hundred and fifty years ago, Koch designed methods to look at bacteria in specimens. The methods remain unchanged to this day. Identifying bacteria in clinical samples is very labour intensive and takes a long time - up to ten days. This time delay in receiving any information on a clinical specimen means that the doctor has to best guess which bacteria are causing the infection. For this reason, the prescription of antibiotics to treat the infection is often by guess work and may be wrong.Incorrect prescribing has contributed to the emergence of bacteria which resist conventional therapy. This is now a major world health problem. Our research plans to make assessment of bacterial infections rapid, on site in the clinic and, in the future by home-testing similar to diabetes monitoring. Knowing which and how many bacteria are present within a wound will allow the doctor to prescribe effective antibiotics quickly and to each person's needs for the best treatment.Our research programme will develop two new test systems to measure the number and type of bacteria in a leg wound. As a model, we will study bacteria in chronic skin wounds for two reasons. Firstly, these wounds represent a huge clinical problem, affecting three in every hundred people over 60 years old in the UK and costing 1 billion for the National Health Service to treat every year. Secondly, the information obtained will directly inform the best treatment for each patient, avoiding unnecessary antibiotic use.Two systems will be researched, one to be left on the wound over time at home and the other for the doctor to use for an immediate report in the clinic. The intelligent dressing materials will work by measuring bacterial indicators by using biological proteins to create a digital instrument signal. The dressings will be tested first in the laboratory and then with patients suffering from leg wounds that are not healing.The intelligent dressings will help reduce antibiotic use, indicating when wounds need treatment. The intelligent real-time systems also help to research the properties essential in new generations of antibiotics and explore the mechanisms that lead to bacteria becoming resistant to these treatments.

150年前，科赫设计了观察标本中细菌的方法。这些方法至今没有改变。鉴定临床样品中的细菌是非常劳动密集型的工作，需要很长时间——长达十天。收到临床标本信息的这段时间延迟意味着医生必须最好地猜测是哪种细菌引起了感染。由于这个原因，治疗感染的抗生素处方往往是猜测工作，可能是错误的。不正确的处方导致了细菌的出现，这些细菌对传统疗法产生了抗药性。这现在是一个主要的世界卫生问题。我们的研究计划使细菌感染的快速评估，在临床现场，并在未来通过家庭测试类似于糖尿病监测。了解伤口中存在哪些细菌以及有多少细菌，将使医生能够迅速开出有效的抗生素，并根据每个人的需要进行最佳治疗。我们的研究项目将开发两种新的测试系统来测量腿部伤口中细菌的数量和类型。作为一个模型，我们将研究慢性皮肤伤口中的细菌，有两个原因。首先，这些伤口代表了一个巨大的临床问题，在英国，每100个60岁以上的人中就有3个受到影响，每年国民健康服务（National Health Service）要花费10亿美元用于治疗。其次，获得的信息将直接告知每个患者的最佳治疗方法，避免不必要的抗生素使用。研究人员将研究两种系统，一种可以长期留在家里的伤口上，另一种则供医生在诊所立即报告使用。这种智能敷料将通过使用生物蛋白来产生数字仪器信号来测量细菌指标。这种敷料将首先在实验室进行测试，然后在腿部伤口未愈合的患者身上进行测试。这种智能敷料将有助于减少抗生素的使用，并在伤口需要治疗时提示。智能实时系统还有助于研究新一代抗生素的基本特性，并探索导致细菌对这些治疗产生耐药性的机制。