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作 者:郑翠玲[1] 韩晓红[1] 冯莎娜[1] 王景智[1] 殷梦前[1] 程焱[1] 齐军[1]
机构地区:[1]中国医学科学院北京协和医学院肿瘤医院检验科,100021
出 处:《中华肿瘤杂志》2016年第1期35-39,共5页Chinese Journal of Oncology
基 金:国家自然科学基金(81201357);国家高技术研究发展(863)计划(2011AA02A110)
摘 要:目的评估UF-1000i全自动尿沉渣分析仪(UF-1000i)对疑似尿路感染(UTI)的肿瘤患者的筛查价值。方法比较1053例患者的中段尿标本应用UF—1000i检测的细菌计数结果与尿细菌培养的结果,以及细菌散点图区分细菌种类的结果与尿细菌培养结果。评价UF-1000i全自动尿沉渣分析仪对筛查UTI的灵敏度、特异度、阳性预测值和阴性预测值。结果1053例患者中,病原菌构成比位居前3位的分别为大肠埃希菌、肠球菌和铜绿假单胞菌。UTI发生率位居前3位的恶性肿瘤分别为膀胱癌、肺癌和宫颈癌。UF-1000i的阳性率为20.0%(211/1053),尿细菌培养的阳性率为17.9%(188/1053),差异无统计学意义(P〉0.05);且2种方法的一致性较好(Kappa-0.756)。与临床确诊的201例UTI比较,UF-1000i筛选UTI的灵敏度为79.6%(160/201),特异度为95.5%(814/852),阳性预测值为80.8%(160/198),阴性预测值为95.2%(814/855)。UF-1000i细菌散点图显示的细菌球杆菌分布与尿细菌培养结果基本一致。结论UF—1000i细菌计数在早期筛查UTI中发挥着重要作用,细菌散点图分布有助于区分细菌种类,从而为临床早期用药治疗提供参考依据。Objective To evaluate the value of urine sediment analyzer in the screening of clinically suspected urinary tract infection (UTI) in cancer patients. Methods The results of bacterial count of 1 053 midstream urine samples by UF-IO00i urine sediment analyzer (UF-1000i urine sediment analyzer, UF- 1000i) were compared with the results of bacterial culture. Moreover, the results of distinguishing bacterial species by the bacterial scattergram were compared with the results of bacteria culture. At the same time, the sensitivity, specificity, positive predictive value and negative predictive value of UF-1000i analyzer for UTI screening were evaluated. Results Of all the 1 053 samples, the top three bacteria were E. coli, Enterococci and P. aeruginosa. The top three malignant tumors of UTI were bladder, lung cancer and cervical cancers. The positive rate of UF-1000i analyzer was 20% (211/1 053), and that of bacteria culture was 17.9% (188/1 053). There was statistically no significant difference in the positive rates between the two methods (X2= 1.636,P〉0.05) , and the two methods had a considerable consistency (Kappa= 0.756). Compared with the clinical diagnosis, UTI screening by UF-1000i analyzer showed a sensitivity of 79.6% (160/201) , specificity of 95.5% (814/852), positive predictive value of 80.8% (160/198) and negative predictive value of 95.2% (814/855). The distribution of cocci and bacilli acquired by the bacterial scattergram was basically in accordance with the results of bacterial culture. Conclusions Bacterial count by UF-1000i analyzer plays an important role in early screening of UTI, and the bacterial scattergram may help to distinguish bacterial species, providing reference for the use of antibiotics in early medication.
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