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IP International Journal of Medical Paediatrics and Oncology

A study establishing correlation of proteinuria and urine protein/creatinine ratio with disease severity in pediatric dengue fever

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Author Details: Priyanka Datla, Uma Raju, Padmanabh Reddy, Srikrishna S, Tejas Deshmukh

Volume : 3

Issue : 1

Online ISSN : 2581-4702

Print ISSN : 2581-4699

Article First Page : 24

Article End Page : 28


Dengue fever has emerged as a major health problem globally with several complications occurring which lead to increasing morbidity and mortality particularly in children. It has therefore become important to establish accurate, easy to perform predictors of disease severity to enable timely management and prevent associated complications. Such markers have not been well researched in the paediatric population. The study was undertaken to establish early predictors of disease severity viz urine protein creatinine ratio (UPCR) and proteinuria in children with dengue. All of the 76 children hospitalized with dengue fever were categorized according to disease severity as per WHO guidelines. Of these, 25% had category 1 disease, 36.8% had category 2 and 38.2% category 3 disease. All children were classified according to UPCR into 4groups. It was observed that 34.2% had UPRC <0.5, 26.3% had 0.5-1.0, 26.3% had 1-3 and 13.2% children had UPRC >3. UPRC was inversely proportional to age and had no association with gender. There was a positive correlation between UPRC and the severity of illness in dengue fever. The association of occurrence of bleeding manifestations, requirement of inotropes and outcome with UPCR was statistically significant. Significant proteinuria had a statistically significant association with mortality, but did not correlate well with disease severity. Thus both UPCR and proteinuria assessment appear to be useful tools for deciding hospitalization, management as well as prognostication in childhood dengue fever.

Pediatric Dengue Fever, Urine Protein Creatinine Ratio, Proteinuria, Prognostic Indicators, Predictor Tools