Aug 22, 2022

Public workspaceRapid Diagnostic Tests and ELISA for diagnosing Chronic Chagas Disease: Systematic revision and meta-analysis

DOI
https://dx.doi.org/10.17504/protocols.io.4r3l2oxppv1y/v1
  • Sandra Helena Suescún-Carrero1,
  • Philippe Tadger2,
  • Carolina Sandoval Cuellar3,
  • lauramirez 3,
  • Lluis Armadans-Gil4
  • 1Universidad de Boyacá, Universitat Autónoma de Barcelona, Barcelona, Spain.;
  • 2Real World Solutions, IQVIA, Zaventem, Belgium, Universidad de Boyacá, Tunja, Colombia;
  • 3Universidad de Boyacá;
  • 4Epidemiology and Preventive Medicine Service, Hospital Universitari Vall d’Hebron - Universitat Autónoma de Barcelona, Barcelona, Spain.
Sandra Helena Suescún-Carrero
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DOI: https://dx.doi.org/10.17504/protocols.io.4r3l2oxppv1y/v1
Protocol Citation: Sandra Helena Suescún-Carrero, Philippe Tadger, Carolina Sandoval Cuellar, lauramirez , Lluis Armadans-Gil 2022. Rapid Diagnostic Tests and ELISA for diagnosing Chronic Chagas Disease: Systematic revision and meta-analysis. protocols.io https://dx.doi.org/10.17504/protocols.io.4r3l2oxppv1y/v1
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License,  which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
We use this protocol and it's working
Created: August 19, 2022
Last Modified: August 22, 2022
Protocol Integer ID: 68919
Keywords: Rapid Diagnostic Tests, ELISA, diagnosing Chronic, Chagas Disease, Systematic revision, meta-analysis, diagnosing chronic chagas disease, suspected chronic chagas disease, chronic chagas disease, assessed elisa test, diagnostic validity, assessed elisa, diagnostic validity of the enzyme, elisa test, immunosorbent assay, studies with elisa, rapid diagnostic test, linked immunosorbent assay, conclusions elisa, applicability of the study, systematic review, heterogeneity between study, risk of publication bias, patient screening, results 43 study, disease
Funders Acknowledgements:
Universidad de Boyacá
Grant ID: www.uniboyaca.edu.co
Universitat Autónoma de Barcelona, Barcelona, Spain.
Grant ID: www.UAB.cat
Abstract
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 May and August 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. This article was funded through the Universidad de Boyacá.
Attachments
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Materials
Bases de datos PubMed, Web of Science, Scopus, and LILACS; hojas, esferos, packages (meta4diag: Binomial-normal with probit, and metandi and IGS: Binomial-normal with logit); (R DTAplots program), R 1.3 software (DTAplots, bamdit::plotcompare and meta4diag::meta-regression), Stata 15 (metandi), midas and JAGS
Troubleshooting
Protocol and registration
Eligibility criteria
Data sources
Study search and selection
Data collection process
Definition for data extraction
Risk of bias and applicability
Diagnostic accuracy measures
Summary of results
Addinitional analyses