Predictors of Hospital-Acquired Urinary Tract-Related Bloodstream Infection in VA

描述（由申请人提供）： 减少退伍军人尿路相关血流感染的预防工作受到缺乏确定病因因素的分析研究的阻碍，特别是那些可能影响住院期间预后的时间依赖性因素。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。 这项基于VA的临床研究的目的是描述导致住院退伍军人尿路相关血流感染的宿主和时间依赖性因素。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，同时考虑到退伍军人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、糖尿病和血流感染之间的关系。具体目标#2针对影响感染发生率的时间相关治疗因素。特别令人感兴趣的是使用抗菌剂、免疫抑制剂治疗和他汀类药物。具体目标#3评估输血相关风险因素与血流感染之间的关系。 一项病例对照研究计划将包括来自安阿伯、底特律和印第安纳波利斯三个VA医疗中心的成年患者。将使用发病密度采样随机选择对照。病例和对照组的信息将从电子数据库（电子医疗、药房和实验室记录）中提取，时间跨度为2000年至2010年11年。分析将确定与住院退伍军人尿路相关血流感染发展相关的因素。分析将使用按医院位置聚类的条件logistic回归，以及对数线性模型的滑动时间窗和具有时间特异性权重函数的三次B样条。 我们预计，从拟议的研究中获得的信息-评估新的风险因素，并与退伍军人的临床护理和安全有关-将增强临床决策工具，并为VA患者的预防性试验提供框架。

DESCRIPTION (provided by applicant): Preventive efforts to reduce urinary tract-related bloodstream infection in veterans 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 VA-based clinical study is to delineate both host- and time- dependent factors that contribute to urinary tract-related bloodstream infection in hospitalized veterans. This study is unique in that it will ascertain potential causal mechanisms of bloodstream infection taking into account the time course of a veteran's hospital stay and the multiple procedures and treatments that occur during this stay. Specific Aim #1 addresses the relation between obesity, diabetes, and bloodstream infection. Specific Aim #2 is directed to time-related treatment factors that impact the incidence of infection. Of particular interest are the use of antimicrobials, immunosuppressant therapies and statin use. Specific Aim #3 assesses the relationship between transfusion-related risk factors and bloodstream infection. A case-control study is planned that will include adult patients from three VA medical centers in Ann Arbor, Detroit, and Indianapolis. Incidence density sampling will be utilized for random selection of controls. Information from cases and controls will be extracted from electronic databases (electronic medical, pharmacy, and laboratory records) over an eleven-year period, 2000 to 2010. Analyses will identify factors related to the development of urinary tract-related bloodstream infection in hospitalized veterans. Conditional logistic regression with clustering by hospital location 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 both novel risk factors and is relevant to the clinical care and safety of veterans - will enhance tools for clinical decision-making and provide a framework for preventive trials in VA patients.