Chotiprasitsakul Darunee, Kijnithikul Akara, Uamkhayan Anuchat, Santanirand Pitak
Department of Medicine, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
Department of Pathology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
Infect Drug Resist. 2021 Dec 30;14:5699-5709. doi: 10.2147/IDR.S343021. eCollection 2021.
Urinary tract infections are diagnosed by clinical symptoms and detection of causative uropathogen. Antibiotics are usually not indicated in candiduria and no-growth urine. We aimed to develop a predictive score to distinguish bacteriuria, candiduria, and no-growth urine, and to describe the distribution of microorganisms in urine.
A single-center, retrospective cohort study was conducted between January 2017 and November 2017. Patients with concomitant urinalysis and urine culture were randomly sorted for a clinical prediction model. Multivariable regression analysis was performed to determine factors associated with bacteriuria, candiduria, and no-growth urine. A scoring system was constructed by rounding the regression coefficient for each predictor to integers. Accuracy of the score was measured by the concordance index (c-index).
There were 8091 positive urine cultures: bacteria 85.6%, 13.7%. Randomly selected cases were sorted into derivation and validation cohorts (448 cases and 272 cases, respectively). Numerous yeast on urinalysis predicted candiduria with complete accuracy; therefore, it was excluded from a score construction. We developed a NABY score based on: positive nitrite, 1 point; Antibiotic exposure within 30 days, -2 points; numerous Bacteria in urine, 2 points; few Yeast in urine, -2 points; moderate Yeast in urine, -5 points. The c-index was 0.85 (derivation) and 0.82 (validation). A score ≥0 predicted 76% and 54% of bacteriuria in the derivation and validation cohorts, respectively. A score ≤-3 predicted 96% of candiduria in both cohorts.
Numerous yeast on urinalysis and the NABY score may help identify patients with a low risk of bacteriuria in whom empiric antibiotics for UTIs can be avoided.
尿路感染通过临床症状及致病尿路病原体检测来诊断。念珠菌尿症和无细菌生长的尿液通常不使用抗生素治疗。我们旨在开发一种预测评分系统,以区分菌尿症、念珠菌尿症和无细菌生长的尿液,并描述尿液中微生物的分布情况。
于2017年1月至2017年11月进行了一项单中心回顾性队列研究。对同时进行尿液分析和尿培养的患者进行随机分组,用于构建临床预测模型。进行多变量回归分析以确定与菌尿症、念珠菌尿症和无细菌生长尿液相关的因素。通过将每个预测因子的回归系数四舍五入为整数来构建评分系统。评分的准确性通过一致性指数(c指数)来衡量。
共有8091份阳性尿培养结果:细菌占85.6%,念珠菌占13.7%。随机选择的病例被分为推导队列和验证队列(分别为448例和272例)。尿液分析中大量酵母可准确预测念珠菌尿症;因此,它被排除在评分构建之外。我们基于以下因素开发了NABY评分:亚硝酸盐阳性,1分;30天内使用过抗生素,-2分;尿液中大量细菌,2分;尿液中少量酵母,-2分;尿液中中等量酵母,-5分。推导队列的c指数为0.85,验证队列的c指数为0.82。评分≥0分别预测推导队列和验证队列中76%和54%的菌尿症。评分≤ -3在两个队列中均能预测96%的念珠菌尿症。
尿液分析中大量酵母及NABY评分可能有助于识别菌尿症低风险患者,从而避免对这些患者经验性使用治疗尿路感染的抗生素。