Urinary biomarkers and haematuria as indicators of urogenital schistosomiasis: A systematic review and meta-analysis.

BACKGROUND

Schistosomiasis, is a parasitic infection that leads to chronic illness and socioeconomic challenges in tropical regions. Adult Schistosoma (S.) haematobium worms inhabit the bladder's venous plexus and produce eggs that cause tissue inflammation and systemic pathologies, detectable as urinary biomarkers in bodily fluids like urine, blood, and serum. Urinalysis offers a rapid, cost-effective, non-invasive assessment of schistosomiasis-related urinary biomarkers.

OBJECTIVES

This systematic review aimed to identify urinary biomarkers indicative of S. haematobium infections and assess their diagnostic relevance.

METHODS

A systematic search was conducted in databases including PubMed, EbscoHost, and Google Scholar to find studies on urogenital schistosomiasis urinary biomarkers detected by point-of-care dipsticks in sub-Saharan Africa. From 699 screened studies, 19 met the inclusion criteria. These studies focused on point-of-care dipstick use for all age groups, excluding those using laboratory-based methods. The Joana Briggs quality assesment tool was used to evaluate the selected articles, and a detailed narrative summary was created. A meta-analysis assessed study variability.

RESULTS

The analysis identified haematuria and proteinuria as key urinary markers for diagnosing urinary schistosomiasis infections. The meta-analysis found a statistically significant pooled prevalence for haematuria, proteinuria, leukocyturia, nitrates, bilirubin, and urobilinogen. Significant heterogeneity was observed in studies measuring haematuria, proteinuria, leukocyturia, and nitrates (over 80 %), with lower but still non-significant heterogeneity for nitrates (39.3 %).

CONCLUSION

Haematuria, proteinuria and leukocyturia are indicators of urogenital schistosomiais morbidity; nonetheless, further investigation is necessary to measure metabolite concentrations directly associated with schistosomiasis morbidity for improved diagnostic precision.