tamara micaela Gar

Mrs. tamara micaela Gar


Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 October 2026 in Pathogens
Verified
Journal Article
Open access
PDF file
RCRubén Cimino
Rubén Cimino
ESErnesto Candela Senti
Ernesto Candela Senti
TGtamara micaela Gar
tamara micaela Gar
SCSofía Ciotta
Sofía Ciotta
ENElvia Nieves
Elvia Nieves
Maria Victoria PeriagoMaria Victoria Periago
Maria Victoria Periago
Background: Strongyloides stercoralis is frequently underdiagnosed due to the limited sensitivity of stool-based methods. Serology improves detection, but venous blood collection and cold-chain requirements complicate field implementation. Dried blood spots (DBS) offer a practical alternative for large-scale surveys. This study aimed to evaluate the diagnostic accuracy of DBS-based serology and compare its performance with conventional ELISA. Methods: A cross-sectional study was conducted in peri-urban communities of Puerto Iguazú, Misiones, Argentina. Stool samples were examined using sedimentation–concentration and Baermann techniques. Venous blood on DBS was analyzed using a commercial ELISA (cELISA) and an in-house NIE-ELISA. Diagnostic accuracy was assessed using a primary reference standard. Agreement between serum and DBS was evaluated using kappa statistics, and ROC curves were generated for paired samples. Results: DBS cELISA showed the highest sensitivity (89.1%), followed by serum cELISA (81.1%) and in-house NIE-ELISA (71.7%). Concordance between sera vs DBS was substantial for cELISA (κ = 0.68) and fair for NIE-ELISA (κ = 0.21). ROC analysis showed comparable AUCs for cELISA using sera (0.85) and DBS (0.83), whereas in-house NIE-ELISA performance declined with DBS (AUC = 0.61). Conclusion: DBS-based cELISA demonstrated high diagnostic accuracy and strong agreement with sera, supporting its use as a field-adapted tool for strongyloidiasis surveillance. DBS serology represents a feasible and reliable alternative for epidemiological studies in resource-limited settings.