Predictors of Urinary Tract Infection and Their Diagnostic Performances among Cameroonian Under-five

Year 2019, Volume: 09 Issue: 02, 68 - 77, 15.06.2019

Dorgelesse Francine Kouemo Motse Guy Pascal Ngaba Loick Pradel Kojom Danielle Christiane Kedy Koum Cecile Ebongue Okalla Calixte İda Penda Evelyn Mah Andreas Chiabi Dieudonné Désiré Adiogo

https://doi.org/10.5799/jmid.574542

Cited By: 2

Abstract

ABSTRACT

Objective: Urinary tract infection (UTIs) in child is serious
public health problem especially in developing countries. This aimed at
identifying factors associated with urinary tract infection and determining
their diagnosis performances as well as resulting algorithms among Cameroonian
under-five.

Methods:
A descriptive and analytical cross sectional study took place from May 2013 to
March 2014 at Pediatrics Department of the Bonassama District hospital in the
town of Douala. Urine samples were collected dependent on the age of children
and its aptitude to micturate. Ten microliters (10 µL) of urine specimen were
cultured at 37°C for 24-48 hours. In addition, sociodemographic,
anthropometric, clinic and biological information of each child were
documented.

Results:
The prevalence of UTI was 32.2% (129/400) which was mainly caused by Escherichia coli (41.1%). A total of
four risk factors for UTI were found after adjustment for all pertinent
characteristics of children. These included female gender (ARR= 0.55; p= 0.0046),
presence of fever (ARR = 1.83; p= 0.0426), trouble urine (ARR = 1.36; p=
0.0063) and presence of nitrites in urine (ARR = 1.09; p= 0.0001). Presence of
nitrites was the most discriminant parameter based on specificity (98.1%),
positive predictive value (95.4%) and negative predictive value (90.1%). The
diagnosis performances have gradually improved with the increasing number of
parameters. 

Conclusion: This study reported four factors associated with
increased risk for UTI. This also outlined that the presence of nitrites in
urine had best diagnosis performances and different predictors-based clinical
algorithms could be helpful especially in the identification of UTI-negative
children.  J Microbiol Infect Dis 2019; 9(2):68-77.

Keywords

Under-five, urinary tract infection, predictors, predictive potential, Cameroon

References

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