Predictors of Hospital-Acquired Urinary Tract-Related Bloodstream Infection

描述（由申请人提供）：由于缺乏确定病因的分析研究，特别是那些可能影响住院期间预后的时间依赖性因素，减少尿路相关血流感染的预防性工作受到阻碍。因此，临床医生以有意义的方式进行调解的能力受到了限制。本研究的目的是描述导致住院患者尿路相关血流感染的宿主和时间依赖因素。这项研究的独特之处在于，它将确定血流感染的潜在因果机制，同时考虑到住院患者住院的时间过程以及住院期间发生的多种程序和治疗。具体目标#1解决肥胖，糖尿病和尿脓毒症之间的关系。具体目标2是针对影响感染发生率的与时间相关的程序和治疗因素。特别值得关注的是导尿管的使用、尿潴留的超声检测、抗生素、免疫抑制剂治疗、他汀类药物的使用和异体输血。计划进行一项巢式病例对照研究，将包括来自密歇根大学卫生系统的成年患者。发病率密度抽样将用于随机选择对照。病例和对照的信息将在5年期间从多个电子数据库（电子医疗、药房和实验室记录）中提取，产生640名受试者。分析将确定与住院患者尿路相关血流感染发展相关的因素。将使用按区聚类的条件逻辑回归进行分析，以及对数线性模型的滑动时间窗口和具有时间特定权重函数的三次b样条。我们期望从拟议的研究中获得的信息，评估新的风险因素，并通过利用二手数据响应项目公告PA-06-151，将增强临床决策工具，并为预防性试验提供框架。尿路感染是最常见的卫生保健相关感染，当传播到血液中时，可能是致命的。尿路相关血流感染的死亡率在不同队列中从5%到33%不等，老年患者的死亡率要高得多。我们预计，从这项研究中获得的信息将为筛查试验的发展奠定基础，以确定住院期间特定时间点有感染风险的患者，并规划预防性干预试验。公共卫生相关性：尿路感染是最常见的卫生保健相关感染，当传播到血液中时，可能是致命的。尿路相关血流感染的死亡率在不同队列中从5%到33%不等，老年患者的死亡率要高得多。我们预计，从这项研究中获得的信息将为筛查试验的发展奠定基础，以确定住院期间特定时间点有感染风险的患者，并规划预防性干预试验。

DESCRIPTION (provided by applicant): Preventive efforts to reduce urinary tract-related bloodstream infection are hampered by the scarcity of analytic studies that identify etiologic factors, particularly those specific to the time-dependent elements that may impact prognosis during hospitalization. Therefore, the ability of clinicians to intercede in a meaningful way has been restricted. The objective of this study is to delineate both host- and time-dependent factors that contribute to urinary tract-related bloodstream infection in hospitalized patients. This study is unique in that it will ascertain potential causal mechanisms of bloodstream infection taking into account the time course of a hospitalized patient's stay and the multiple procedures and treatments that occur during this stay. Specific Aim #1 addresses the relation between obesity, diabetes, and urosepsis. Specific Aim #2 is directed to time-related procedural and treatment factors that impact the incidence of infection. Of particular interest are the use of catheterization, ultrasound detection of urinary retention, antibiotics, immunosuppressant therapies, statin use, and allogeneic blood transfusions. A nested case-control study is planned that will include adult patients from the University of Michigan Health System. Incidence density sampling will be utilized for random selection of controls. Information from cases and controls will be extracted from multiple electronic databases (electronic medical, pharmacy, and laboratory records) over a 5-year period to yield 640 subjects. Analyses will identify factors related to the development of urinary tract-related bloodstream infection in hospitalized patients. Conditional logistic regression with clustering by ward will be utilized for the analyses, as well as sliding time windows for log-linear models and cubic B-splines with time-specific weight functions. We anticipate that the information obtained from the proposed study which evaluates novel risk factors and is responsive to program announcement PA-06-151 by utilizing secondary data will enhance tools for clinical decision making and provide a framework for preventive trials. Urinary tract infection is the most frequent healthcare-associated infection and, when disseminated to the bloodstream, can be fatal. The mortality rate of urinary tract-related bloodstream infection varies from 5% to 33% in different cohorts and is considerably higher in elderly patients. We anticipate that the information obtained from this study will form the foundation for the development of screening tests to identify patients at risk of infection at specific points in time during hospitalization and for planning preventive intervention trials. PUBLIC HEALTH RELEVANCE: Urinary tract infection is the most frequent healthcare-associated infection and, when disseminated to the bloodstream, can be fatal. The mortality rate of urinary tract-related bloodstream infection varies from 5% to 33% in different cohorts and is considerably higher in elderly patients. We anticipate that the information obtained from this study will form the foundation for the development of screening tests to identify patients at risk of infection at specific points in time during hospitalization and for planning preventive intervention trials.