Advani Sonali D, Polage Christopher R, Fakih Mohamad G
Division of Infectious Diseases, Duke University School of Medicine, Durham, North Carolina.
Duke Infection Control Outreach Network, Durham, North Carolina.
Antimicrob Steward Healthc Epidemiol. 2021;1(1). doi: 10.1017/ash.2021.167. Epub 2021 Jun 28.
The extensive use of the urinalysis for screening and monitoring in diverse clinical settings usually identifies abnormal urinalysis parameters in patients with no suspicion of urinary tract infection, which in turn triggers urine cultures, inappropriate antimicrobial use, and associated harms like infection. We highlight how urinalysis is misused, and suggest deconstructing it to better align with evolving patterns of clinical use and the differential diagnosis being targeted. Reclassifying the urinalysis components into infectious and non-infectious panels and interpreting urinalysis results in the context of individual patient's pretest probability of disease is a novel approach to promote proper urine testing and antimicrobial stewardship, and achieve better outcomes.
在各种临床环境中广泛使用尿液分析进行筛查和监测,通常会在未怀疑有尿路感染的患者中发现尿液分析参数异常,这进而引发尿培养、不适当的抗菌药物使用以及诸如感染等相关危害。我们强调了尿液分析是如何被滥用的,并建议对其进行解构,以更好地与不断演变的临床使用模式和所针对的鉴别诊断相匹配。将尿液分析成分重新分类为感染性和非感染性组,并在个体患者疾病预测试验概率的背景下解读尿液分析结果,是一种促进正确尿液检测和抗菌药物管理并取得更好结果的新方法。