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Rama Naghshidaian, Rasoul Nasiri Kalmarzi , Alireza Eskandarifar, Behzad Khalafi , Ahmad Fotoohi, Soroush Noshadi, Hedayat Rasouli,
Volume 3, Issue 4 (11-2017)
Abstract

Background and Objectives: Urinary Tract Infections (UTI) is a common disorder in pediatrics and early diagnosis is important. However, in young children diagnosis is problematic. A problem is variety in sign and symptoms and for exact diagnosis in some case we need expensive modalities. Thus, new way is needed. IL-6 at last decades was preferred to UTI diagnosis and upper/lower involvement differentiation. According to contrariety in IL-6 accuracy this study was performed to learn about diagnostic accuracy of plasma IL-6 in UTI diagnosis and its power for differentiating upper from lower involvement.
Methods: At this descriptive study, 83 patients were included and examined for Interleukin 6 value in both urinary tract diagnosis and upper/lower involvement differentiation. Demographic characteristic like age, gender, history, physical examination beside of blood tests like white blood cell count, ESR, CRP, IL-6 were done and results listed. Descriptive parameters were reported by mean and frequency and for statistical analysis was performed using t-test in SPSS v.16. ROC curve was checked for diagnosed value.
Results: In this study 83 patients (14 control group, 33(39.8%) cystitis, 36(43.4%) pyelonephritis) with 3.93±3.069 mean age enrolled. Age distribution at this study was 20, 63 for males and females, respectively. The IL-6 level in cystitis was higher than control and but was not significant. In ROC curve sensitivity and specify of IL-6 for cystitis were 52%, 50% and for pyelonephritis 60%, 50%, respectively.
Conclusion: According to this study, IL-6 is not a good biomarker for Urinary tract infection and differentiation upper tract involvement from the lower tract. A wide range of Il-6 level and useless of this biomarker can be due to gender distribution, time of disease presence, bacterial virulence and other factors. Therefore, studies on large sample is recommended.
 

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