SynthesisRevista da Sociedade Brasileira de Medicina Tropical2026
A systematic review of comparative accuracy studies of the Kato-Katz and spontaneous sedimentation methods for schistosomiasis diagnosis.
Synthesis in Revista da Sociedade Brasileira de Medicina Tropical, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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4 authors.
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Abstract
backgroundAlthough alternatives to the Kato-Katz (KK) method for the diagnosis of schistosomiasis are not widely available, other egg detection methods may have a role, especially considering the immediate need for confirmatory diagnosis and management of individual patients. One such widely available and easy-to-perform option is the Lutz method. We aimed to compare the diagnostic accuracy of KK and Lutz to support clinical decision-making.
methodsWe conducted a systematic review searching PUBMED, EMBASE, and LILACS databases. We included primary diagnostic accuracy studies comparing KK and Lutz. No restriction was imposed on the type of test used as the reference standard. QUADAS-2 and QUADAS-C tools were used to assess the risk of bias and applicability, and GRADE was used to assess the certainty of evidence. The primary outcomes were sensitivity and specificity. Due to clinical and methodological heterogeneity, a meta-analysis was not performed.
resultsOut of 1,060 citations, three studies were included in our review. The studies were cross-sectional and conducted in Brazil and Ethiopia. The sensitivity of Lutz ranged from 0.34 to 0.81, while that of KK ranged from 0.64 to 0.84. Specificity for both tests ranged from 0.81 to 1.0, with no significant differences observed between the diagnostic tests evaluated. Limitations included inconsistent reference standards, lack of blinding, and small sample sizes. The certainty of evidence ranged from very low to moderate.
conclusionsData on the relative accuracy of the KK and Lutz methods for schistosomiasis diagnosis are limited. The current evidence is insufficient to determine the best method.
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