Parker Jessica L, Kirmiz Samer, Noyes Sabrina L, Davis Alan T, Babitz Stephen K, Alter David, Hu Susie, Lane Brian R
Spectrum Health Hospital System, Grand Rapids, MI; Spectrum Health Office of Research and Education, Grand Rapids, MI.
Michigan State University College of Human Medicine, Grand Rapids, MI; Department of Urology, Wayne State University, Detroit, MI.
Urol Oncol. 2020 Nov;38(11):853.e9-853.e15. doi: 10.1016/j.urolonc.2020.06.035. Epub 2020 Jul 30.
Chronic kidney disease (CKD) is classified according to cause, glomerular filtration rate, and proteinuria. Identification of proteinuria with urinalysis (UA) is less accurate than quantification via other methods. We investigated factors leading to discordant UA findings when compared against paired albumin-to-creatinine ratio (ACR) testing.
Four thousand three hundred and twenty-three UAs were grouped by proteinuria level (A1-A3); concordance with ACR was examined. Classification of UA with confounding factors (UA+CF) or without (UA-CF) was based on CF that resulted in >10% increase in false-positive proteinuria readings. The presence of ≥3+ blood, ≥3+ leukocyte esterase, any ketonuria, specific gravity ≥1.020, ≥1+ urobilinogen, ≥2+ bilirubin, ≥2+ bacteria, ≥3 RBC/hpf (high powered field), ≥10 WBC/hpf, and/or ≥6 epithelial cells/hpf led to UA+CF classification.
Proteinuria was determined to be present in 14.1% by UA dipstick and 24.9% by ACR. Using ACR as the standard, overall concordance was 80.4%, with 17.2% false-negatives and 2.3% false-positives by UA. UA+CF represented 55.6% of UA overall (n = 2404), and 98.0% of those false-positive for proteinuria. High specific gravity and hematuria are the strongest predictors of false positives. For A2 proteinuria (30-300 mg/g, 1+,2+,3+ on UA) UA-CF had a higher negative predictive value (NPV) (99.8%) than UA+CF (77.6%); NPV for A3 proteinuria (>300 mg/g, 4+ on UA) was 100% for UA-CF and UA+CF.
Additional abnormalities were noted in >50% of outpatient UAs indicating proteinuria. Given the significant proportion of patients having a false-positive UA for proteinuria when these CFs were present, we recommend that such patients undergo ACR confirmatory testing, according to a clinical algorithm for the incorporation of UA results into the management of CKD.
慢性肾脏病（CKD）根据病因、肾小球滤过率和蛋白尿进行分类。通过尿液分析（UA）识别蛋白尿的准确性低于通过其他方法进行的定量分析。我们研究了与配对的白蛋白与肌酐比值（ACR）检测相比，导致UA结果不一致的因素。
4323次UA检测按蛋白尿水平（A1 - A3）分组；检查与ACR的一致性。根据导致蛋白尿假阳性读数增加>10%的混杂因素（CF），对有CF（UA + CF）或无CF（UA - CF）的UA进行分类。存在≥3+血尿、≥3+白细胞酯酶、任何酮尿、比重≥1.020、≥1+尿胆原、≥2+胆红素、≥2+细菌、≥3个红细胞/高倍视野（hpf）、≥10个白细胞/hpf和/或≥6个上皮细胞/hpf导致UA + CF分类。
通过UA试纸条检测确定蛋白尿的比例为14.1%，通过ACR检测为24.9%。以ACR为标准，总体一致性为80.4%，UA检测的假阴性率为17.2%，假阳性率为2.3%。UA + CF占UA总数的55.6%（n = 2404），占蛋白尿假阳性病例的98.0%。高比重和血尿是假阳性的最强预测因素。对于A2级蛋白尿（30 - 300mg/g，UA上为1+、2+、3+），UA - CF的阴性预测值（NPV）（99.8%）高于UA + CF（77.6%）；对于A3级蛋白尿（>300mg/g，UA上为4+），UA - CF和UA + CF的NPV均为100%。
在超过50%提示蛋白尿的门诊UA检测中发现了其他异常。鉴于存在这些CF时，有相当比例的患者UA检测蛋白尿呈假阳性，我们建议此类患者根据将UA结果纳入CKD管理的临床算法，接受ACR确认检测。
