Gehringer Christian, Regeniter Axel, Rentsch Katharina, Tschudin-Sutter Sarah, Bassetti Stefano, Egli Adrian
University Hospital Basel, Division of Internal Medicine, University of Basel, Basel, Switzerland.
University Hospital Basel, Division of Clinical Bacteriology and Mycology, University of Basel, Petersgraben 4, 4031, Basel, Switzerland.
BMC Infect Dis. 2021 Feb 25;21(1):209. doi: 10.1186/s12879-021-05893-3.
Urinary tract infection (UTI) is diagnosed combining urinary symptoms with demonstration of urine culture growth above a given threshold. Our aim was to compare the diagnostic accuracy of Urine Flow Cytometry (UFC) with urine test strip in predicting bacterial growth and in identifying contaminated urine samples, and to derive an algorithm to identify relevant bacterial growth for clinical use.
Species identification and colony-forming unit (CFU/ml) quantification from bacterial cultures were matched to corresponding cellular (leucocytes/epithelial cells) and bacteria counts per μl. Results comprise samples analysed between 2013 and 2015 for which urine culture (reference standard) and UFC and urine test strip data (index tests, Sysmex UX-2000) were available.
47,572 urine samples of 26,256 patients were analysed. Bacteria counts used to predict bacterial growth of ≥10 CFU/ml showed an accuracy with an area under the receiver operating characteristic curve of > 93% compared to 82% using leukocyte counts. The relevant bacteriuria rule-out cut-off of 50 bacteria/μl reached a negative predictive value of 98, 91 and 89% and the rule-in cut-off of 250 bacteria/μl identified relevant bacteriuria with an overall positive predictive value of 67, 72 and 73% for microbiologically defined bacteriuria thresholds of 10, 10 or 10 CFU/ml, respectively. Measured epithelial cell counts by UFC could not identify contaminated urine.
Prediction of a relevant bacterial growth by bacteria counts was most accurate and was a better predictor than leucocyte counts independently of the source of the urine and the medical specialty ordering the test (medical, surgical or others).
尿路感染（UTI）的诊断是将泌尿系统症状与尿培养菌落生长超过特定阈值相结合。我们的目的是比较尿流式细胞术（UFC）和尿试纸条在预测细菌生长及识别污染尿样方面的诊断准确性，并推导一种算法以识别临床上相关的细菌生长情况。
将细菌培养物的菌种鉴定和菌落形成单位（CFU/ml）定量与相应的每微升细胞（白细胞/上皮细胞）及细菌计数相匹配。结果包括2013年至2015年期间分析的样本，这些样本同时有尿培养（参考标准）以及UFC和尿试纸条数据（指标检测，Sysmex UX - 2000）。
对26256例患者的47572份尿样进行了分析。用于预测细菌生长≥10 CFU/ml的细菌计数显示，受试者操作特征曲线下面积的准确率>93%，而使用白细胞计数时为82%。50个细菌/微升的相关菌尿排除临界值的阴性预测值分别为98%、91%和89%，250个细菌/微升的纳入临界值识别相关菌尿，对于微生物学定义的菌尿阈值分别为10 CFU/ml、10 CFU/ml或10 CFU/ml时，总体阳性预测值分别为67%、72%和73%。通过UFC测量的上皮细胞计数无法识别污染尿样。
细菌计数对相关细菌生长的预测最为准确，且与白细胞计数相比是更好的预测指标，与尿样来源及开具检测的医学专科（内科、外科或其他）无关。
