Molecular Diagnosis of Chagas Disease: A Systematic Review and Meta-Analysis.

Abstract Background: There is no consensus regarding the most effective molecular protocol for the diagnosis of Chagas disease. The diagnostic tools for Chagas disease are controversial within the scientific community. Currently, serology is the reference standard technique; occasionally, results are inconclusive, and a different diagnostic technique is needed. Some guidelines recommend molecular testing. A systematic review and meta-analysis of available molecular tools/techniques for the diagnosis of Chagas disease was performed to measure their heterogeneity and efficacy in detecting Trypanosoma cruzi infection in blood samples. Methods: A systematic review was conducted up to July 27, 2022, including studies published in international databases. Inclusion and exclusion criteria were defined to select eligible studies. Data were extracted and presented according to PRISMA 2020 guidelines. Study quality was assessed using Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). A random-effects model was used to calculate pooled sensitivity, specificity, and diagnostic odds ratio (DOR). Forest plots and a summary of the receiving operating characteristics (SROC) curves displayed the outcomes. Heterogeneity was determined by I 2 and Tau 2 statistics and p values. Funnel plots and Deek's test were used to assess publication bias. A quantitative meta-analysis of the different outcomes in the two different clinical phases was performed. Principal findings: We identified 858 records and selected 32 papers. Studies pertained to endemic countries and nonendemic areas with adult and paediatric populations. The sample sizes ranged from 17 to 708 patients. There were no concerns regarding the risk of bias and applicability of all included studies. This resulted in high heterogeneity between studies, with the master mix origin and guanidine addition representing significant sources. Interpretation/Conclusions and relevance: Continuous analysis and optimization of the different molecular techniques is crucial to implement this efficient diagnosis in endemic areas.