Correlation of Nitrite, Leucocyte Esterase and Protein Detection to Diagnosis of Urinary Tract Infections
Journal of Advances in Medicine and Medical Research · pp. 1–6 · Published 6 Feb 2016
10.9734/BJMMR/2016/23444Abstract
Aim: To determine the relationship between detection of nitrite, Leucocyte esterase (LE) and protein in urine and significant bacteriuria. Study Design: Cross-sectional descriptive study. Place and Duration of Study: Department of Medical Microbiology and Parasitology, University of Port Harcourt Teaching Hospital, between March and September 2015. Methodology: 240 urine samples were analyzed. Dipstick analysis using Combi-UriScreen 10SL reagent strips (Axiom Medical limited, UK) and culture for significant bacteriuria were performed according to manufacturer’s instruction/ using standard protocols. Data was coded, entered into Microsoft Excel ® version 2010 and analysed using Epi-Info version 7.02. Categorical data were presented as frequencies and percentages using tables. Univariate analysis using logistic regression (Odds Ratio) was used to determine the association between the presence of nitrite, LE and protein and significant bacterial yield in urine. A P-value of ≤ 0.05 was considered statistically significant. Likelihood ratios were calculated. Results: 23 (23.2%) out of 99 samples with significant bacteriuria were nitrite positive, while 42 (42.4%) and 45 (45.5%) were positive for leucocyte esterase and protein respectively. Nitrite (P = 0.001, OR = 5.03, 95% CI = 2.02-12.93) and leucocyte esterase positivity (P = 0.001, OR = 3.59, 95% CI = 1.91-6.80) were significantly associated with significant bacteriuria while proteinuria was not (P = 0.989, OR = 1.03, 95% CI = 0.60-1.79). Nitrite positivity alone had the best positive likelihood ratio (4.09, 95% CI: 1.91, 8.78) followed by the combination of nitrite and LE positivity (3.65, 95% CI: 1.90, 7.03). Conclusion: The use of dipstick analysis of urine as a screening tool for samples to be cultured may be a very effective way of reducing laboratory costs and wastage of man hours, which both ultimately improve the effectiveness of clinical laboratories especially in resource-poor settings.
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