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Article

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Accepted version

Publication date

2023-07

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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/214991

Practical diagnostic algorithms for Chagas disease: a focus on low resource settings

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https://doi.org/10.1080/14787210.2023.2279110

Abstract

Introduction: Chagas disease, caused by parasite Trypanosoma cruzi, is the most important neglected tropical disease in the Americas. Two drugs are available for treatment, but access to them is challenging, in part due to complex diagnostic algorithms. These are stage-dependent, involve multiple tests, and are ill-adapted to the reality of vast areas where the disease is endemic. Molecular and serologic tools are used to detect acute and chronic infections, with the performance of the latter showing geographic differences. Breakthroughs in the development of new diagnostic tools include the validation of a loop-mediated isothermal amplification assay for acute infections (T. cruzi-LAMP), and the regional validation of several rapid diagnostic tests (RDTs) for chronic infection, which simplify testing in resource-limited settings. The literature search was carried out in the MEDLINE database until 1 August 2023. Areas covered: This review outlines existing algorithms, and proposes new ones focused on point-of-care testing. Expert opinion: Integrating point-of-care testing into existing diagnostic algorithms in certain endemic areas will increase access to timely diagnosis and treatment. However, additional research is needed to validate the use of these techniques across a wider geography, and to better understand the cost-effectiveness of their large-scale implementation.

Subject

Epidemiologia, Algorismes, Malaltia de Chagas, Diagnòstic

Subject (English)

Epidemiology, Algorithms, Chagas' disease, Diagnosis

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Articles publicats en revistes (Biologia, Sanitat i Medi Ambient)
Articles publicats en revistes (ISGlobal)

Citation

GABALDÓN FIGUEIRA, Juan Carlos, et al. Practical diagnostic algorithms for Chagas disease: a focus on low resource settings. Expert Review of Anti-infective Therapy. 2023. Vol. 21, num. 12, pags. 1287-1299. ISSN 1478-7210. [consulted: 8 of August of 2026]. Available at: https://hdl.handle.net/2445/214991

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