Rapid diagnostic tests and ELISA for diagnosing chronic Chagas disease: Systematic revision and meta-analysis

Objective To determine the diagnostic validity of the enzyme-linked immunosorbent assay (ELISA) and Rapid Diagnostic Tests (RDT) among individuals with suspected chronic Chagas Disease (CD). Methodology A search was made for studies with ELISA and RDT assays validity estimates as eligibility criteria, published between 2010 and 2020 on PubMed, Web of Science, Scopus, and LILACS. This way, we extracted the data and assessed the risk of bias and applicability of the studies using the QUADAS-2 tool. The bivariate random effects model was also used to estimate the overall sensitivity and specificity through forest-plots, ROC space, and we visually assessed the heterogeneity between studies. Meta-regressions were made using subgroup analysis. We used Deeks' test to assess the risk of publication bias. Results 43 studies were included; 27 assessed ELISA tests; 14 assessed RDTs; and 2 assessed ELISA and RDTs, against different reference standards. 51.2% of them used a non-comparative observational design, and 46.5% a comparative clinical design (case-control type). High risk of bias was detected for patient screening and reference standard. The ELISA tests had a sensitivity of 99% (95% CI: 98-99) and a specificity of 98% (95% CI: 97-99); whereas the Rapid Diagnostic Tests (RDT) had values of 95% (95% CI: 94-97) and 97% (95% CI: 96-98), respectively. Deeks' test showed asymmetry on the ELISA assays. Conclusions ELISA and RDT tests have high validity for diagnosing chronic Chagas disease. The analysis of these two types of evidence in this systematic review and meta-analysis constitutes an input for their use. The limitations included the difficulty in extracting data due to the lack of information in the articles, and the comparative clinical-type design of some studies.

Automated summary

This study examined the diagnostic validity of ELISA and RDT tests for chronic Chagas Disease. The results showed that both tests have high sensitivity and specificity. However, some studies had biases and design limitations.