Institute for Medical Microbiology, Immunology and Hygiene, School of Medicine, Technical University of Munich, Munich, Germany.
Department of Internal Medicine II, School of Medicine, Technical University of Munich, Munich, Germany.
PLoS One. 2020 Oct 22;15(10):e0240981. doi: 10.1371/journal.pone.0240981. eCollection 2020.
For acute medicine physicians, distinguishing between asymptomatic bacteriuria (ABU) and clinically relevant urinary tract infections (UTI) is challenging, resulting in overtreatment of ABU and under-recognition of urinary-source bacteraemia without genitourinary symptoms (USB). We conducted a retrospective analysis of ED encounters in a university hospital between October 2013 and September 2018 who met the following inclusion criteria: Suspected UTI with simultaneous collection of paired urinary cultures and blood cultures (PUB) and determination of Procalcitonin (PCT). We sought to develop a simple algorithm based on clinical signs and PCT for the management of suspected UTI. Individual patient presentations were retrospectively evaluated by a clinical "triple F" algorithm (F1 ="fever", F2 ="failure", F3 ="focus") supported by PCT and PUB. We identified 183 ED patients meeting the inclusion criteria. We introduced the term UTI with systemic involvement (SUTI) with three degrees of diagnostic certainty: bacteremic UTI (24.0%; 44/183), probable SUTI (14.2%; 26/183) and possible SUTI (27.9%; 51/183). In bacteremic UTI, half of patients (54.5%; 24/44) presented without genitourinary symptoms. Discordant bacteraemia was diagnosed in 16 patients (24.6% of all bacteremic patients). An alternative focus was identified in 67 patients, five patients presented with S. aureus bacteremia. 62 patients were diagnosed with possible UTI (n = 20) or ABU (n = 42). Using the proposed "triple F" algorithm, dichotomised PCT of < 0.25 pg/ml had a negative predictive value of 88.7% and 96.2% for bacteraemia und accordant bacteraemia respectively. The application of the algorithm to our cohort could have resulted in 33.3% reduction of BCs. Using the diagnostic categories "possible" or "probable" SUTI as a trigger for initiation of antimicrobial treatment would have reduced or streamlined antimicrobial use in 30.6% and 58.5% of cases, respectively. In conclusion, the "3F" algorithm supported by PCT and PUB is a promising diagnostic and antimicrobial stewardship tool.
对于急性医学医师来说，区分无症状菌尿症（ABU）和临床相关尿路感染（UTI）具有挑战性，这导致了对 ABU 的过度治疗以及对无泌尿生殖系统症状的尿源菌血症（USB）的认识不足。我们对 2013 年 10 月至 2018 年 9 月期间在一所大学医院就诊的 ED 患者进行了回顾性分析，这些患者符合以下纳入标准：疑似 UTI，同时采集配对的尿液培养物和血液培养物（PUB），并测定降钙素原（PCT）。我们试图基于临床体征和 PCT 为疑似 UTI 制定一个简单的管理算法。个体患者的表现由 PCT 和 PUB 支持的临床“三重 F”算法（F1=“发热”，F2=“失败”，F3=“焦点”）进行回顾性评估。我们确定了 183 名符合纳入标准的 ED 患者。我们引入了“系统受累性尿路感染（SUTI）”这一术语，并根据诊断确定性的三个程度进行分类：菌血症性 UTI（24.0%，44/183）、可能的 SUTI（14.2%，26/183）和可能的 SUTI（27.9%，51/183）。在菌血症性 UTI 中，一半的患者（54.5%，24/44）没有泌尿生殖系统症状。在 16 名患者（所有菌血症患者的 24.6%）中诊断出不一致性菌血症。在 67 名患者中确定了替代焦点，5 名患者表现为金黄色葡萄球菌菌血症。62 名患者被诊断为可能的 UTI（n=20）或 ABU（n=42）。使用拟议的“三重 F”算法，<0.25pg/ml 的二分类 PCT 对菌血症和一致菌血症的阴性预测值分别为 88.7%和 96.2%。将该算法应用于我们的队列中，可使 BCs 的减少 33.3%。使用“可能”或“可能”SUTI 的诊断类别作为开始抗菌治疗的触发因素，可分别减少或简化 30.6%和 58.5%的抗菌药物使用。总之，由 PCT 和 PUB 支持的“3F”算法是一种很有前途的诊断和抗菌药物管理工具。
