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Visceral leishmaniasis (VL) is a fatal disease caused by Leishmania parasites and transmitted by female phlebotomine sandflies. The disease is a serious public health problem in eastern Africa; including Kenya where an estimated 4000 cases occur annually and 5 million people are at risk of infection. Accurate diagnosis of VL is critical for appropriate treatment. Currently, VL diagnosis in Kenya is based on testing suspected patients with the IT-Leish rK39 rapid diagnostic test (RDT) followed by other tests such as the Direct Agglutination Tests (DAT) and microscopy of tissue aspirates (splenic, bone marrow, lymph node) on rK39-negative patients. However, these diagnostic tools present several challenges including; the need for expertise, equipment and low diagnostic sensitivity of (85%) for DAT and rK39. Alternative VL diagnostic tools that are readily available, easy to use with increased sensitivity are needed to improve VL surveillance and control in Kenya. In the present study, we will assess rK28 as a diagnostic tool including performance with increased sensitivity when used together with IT-Leish rK39 and its potential for inclusion in VL diagnosis algorithms and evaluate Kala-azar Detect rK39 for potential use in Kenya. Suspected patients presenting at VL testing facilities in Marsabit, Turkana and Wajir Counties will be recruited prospectively and tested using IT-Leish rK39 followed by DAT for case confirmation according to the national guidelines. Alongside the case confirmation, samples from participants will also be tested using the rK28 and Kala-azar Detect rK39 in whole blood and serum. The collected data will be analyzed and compared separately between the RDTs as well as in combination, and the performance of the algorithms determined retrospectively. This design will enable the assessment of the sensitivity of combining rK28 and rK39 (Kala-azar Detect) compared to rK39 (IT-Leish/Kala-azar Detect) alone. Microscopy will be used as confirmatory test. We will also assess the feasibility, usefulness, and cost-effectiveness of rK28 in the VL diagnostic algorithm, through sensitivity analyses. The improved understanding of rK28 as a VL diagnostic tool and its potential for inclusion in the VL diagnosis algorithm could enable faster and more effective management of cases and accelerate elimination of VL.
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Dawn K Maranga; Joseph Ndung'u
Data sourced from clinicaltrials.gov
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