Predicting Wound Healing Complications in the Emergency Department

描述(申请人提供)：2003年有1.14亿急诊科就诊，其中5.7%涉及急性开放性伤口的治疗。总体而言，缺乏临床结果研究来确定治疗这些伤口的最有效方法。目前对急性伤口的治疗是以旧教条为指导的，其中一些可能是不合适的。证据基于动物试验和陈旧的临床研究，缺乏足够的方法，或者实际上是不存在的，并被观点所延续。一个经典的例子是手撕裂伤的治疗和被狗咬伤的伤口感染率，这两项都是在候选人的K-23奖项中研究的。旧文献表明，狗咬伤的基线感染率总体上约为15%，手部伤口的感染率可能高达30%，这导致许多人倡导预防性使用抗生素。目前的研究表明，目前的感染率可能是5%，这使得治疗所有伤口的理由都是无效的。这位候选人还挑战了一种教条，即无论是缝合还是保守治疗，简单的手撕裂伤都会愈合。大多数急性伤口是简单和不复杂的，只有偶尔会出现感染和裂开等并发症。不同的医生在伤口护理实践上有很大的差异。这包括伤口清洁(什么溶液和多少冲洗？)、伤口闭合(一次和二次)，以及预防性抗生素的使用。根据结果研究确定哪些伤口有并发症的风险，将指导治疗和后续决定，并最终实现最具成本效益的护理。应聘者拥有伤口护理领域的专业知识，并已完成临床研究方面的额外研究生培训。在成功完成他的K-23奖项后，候选人已经为自己的职业生涯做好了准备，成为一名独立的临床科学家。建议申请的目的是让候选人能够利用他在临床决策规则开发方面的研究技能和对伤口护理研究的热情来开发临床决策指南，以预测急救治疗后有并发症风险的伤口。这项应用的具体目的是利用候选人的K-23中建立的伤口护理网络来收集大量预期的撕裂伤和急性狗咬伤伤口，以制定预测伤口愈合并发症的决策规则。使用他的实时通知和跟踪系统来识别符合条件的患者，他将让医生前瞻性地完成基于网络的标准化数据收集表格。然后，他将在30天内确定伤口结局(感染和裂开)，以确定急性伤口并发症的发生率。利用他在临床预测规则开发方面的技能，特别是利用递归分区技术，他将推导出高度敏感和特定的临床预测规则，用于预测急性撕裂伤和狗咬伤的并发症。如果候选人能够成功地得出R-21中的规则，这些规则将随后得到验证和实施，以提高急性伤口护理的效率。 这项应用将研究人们在该国寻求医疗保健的第二个最常见的原因，即急性创伤性撕裂伤和咬伤的治疗。这项研究的潜在影响是巨大的，因为研究结果将指导在有争议的问题上做出有效和成本效益高的管理决策，例如哪些患者将受益于预防性抗生素。这将通过研究一大群到急诊科就诊的急性撕裂伤和被狗咬伤的患者来实现，以确定目前伤口并发症的发生率，主要是感染。然后将分析许多变量，以确定导致这些并发症的一组危险因素。了解哪些患者有并发症的风险将有助于指导治疗和管理决策。

DESCRIPTION (provided by applicant): In 2003 there were 114 million emergency department visits, of which 5.7 percent involved the treatment of acute open wounds. In general there is a lack of clinical outcomes research to determine the most efficient method to treat these wounds. Current treatment of acute wounds is guided by old dogma, some of which may not be appropriate. Evidence is based on animal trials and on old clinical research lacking sufficient methods or in fact non-existent and perpetuated by opinion. A classic example is the treatment of hand lacerations and the rate of wound infections from dog bites, both studied in the candidate's K-23 award. Old literature suggests the baseline infection rates for dog bites is about 15 percent overall and perhaps as high as 30 percent for hand wounds leading to many advocating for prophylactic antibiotics. Current work suggests that the current rate of infection is probably 5 percent making the rationale to treat all wounds invalid. The candidate has also challenged dogma demonstrating that simple hand lacerations heal regardless of whether they are treated with sutures or conservatively. The majority of acute wounds are simple and uncomplicated that only occasionally may develop complications such as infection and dehiscence. There are tremendous variations in wound care practices among physicians. This includes wound cleansing (what solution and how much irrigation?), wound closure (primary vs. secondary and modality), and the use of prophylactic antibiotics. Determining which wounds are at risk for complications based on outcomes research will guide treatment and follow-up decisions and ultimately allow for the most cost-effective care. The candidate has expertise in the area of wound care and has completed extra graduate training in clinical research. Having successfully completed his K-23 award the candidate has prepared himself for a career as an independent clinical scientist .The purpose of the proposed application is to allow the candidate to utilize his research skills in clinical decision rule development and his passion for wound care research to develop clinical decision guidelines to predict wounds at risk for complications after ED treatment. The specific aim of this application is to utilize the wound care network established in the candidate's K-23 to collect a large prospective cohort of lacerations and acute dog bite wounds to develop a decision rule to predict wound healing complications. Using his real-time notification and tracking system to identify eligible patients, he will have physicians prospectively complete a standardized web based data collection form. He will then determine wound outcomes (infection and dehiscence) within 30 days to determine the rates of acute wound complications. Using his skills in clinical prediction rule development specifically utilizing recursive partitioning techniques he will derive highly sensitive and specific clinical prediction rules for predicting complications of acute lacerations and dog bite wounds. If the candidate can successfully derive the rules in this R-21 they will be subsequently validated and implemented to improve the efficiency of acute wound care. This application will study the second most common reason why people seek medical care in the country, the treatment of acute traumatic lacerations and bites. The potential impact of this study is enormous as the study results will guide efficient and cost effective management decisions on controversial issues such as which patients would benefit from prophylactic antibiotics. This will be accomplished by studying a large group of patients presenting to emergency departments with acute lacerations and dog bites to determine the current incidence of wound complications, primarily infection. Numerous variables will then be analyzed to determine a group of risk factors for developing these complications. Knowing which patients are at risk for complications will help guide treatment and management decisions.