Background
The screening of
Trypanosoma cruzi
-infected blood donors using two serological techniques frequently leads to conflicting results. This fact prompted us to evaluate the diagnostic performance of four “in-house” immunodiagnostic tests and two commercially available enzyme-linked immunosorbent assays (ELISAs).
Material and Methods
One hundred and seventy-nine blood donors, whose screening for Chagas disease was doubtful, underwent three in-house ELISAs, one in-house immunoblotting test (TESA-blot), and two commercial ELISAs (bioMérieux and Wiener) in an attempt to define the presence or absence of infection. Simultaneously, 29 donors with previous positive results from three conventional serological tests and 30 donors with constant negative results were evaluated.
Results
The ELISA-Wiener showed the highest rate in sensitivity (98.92%) and the ELISA-bioMérieux, the highest specificity (99.45%), followed by the TESA-blot, which showed superior performance, with lower false-negative (2.18%) and false-positive (1.12%) rates. In series, the combination composed of the TESA-blot and ELISA-bioMérieux showed slightly superior performance, with trifunctional protein deficiency (TFP) = 0.01%.
Conclusion
Our study confirms the high sensitivity and specificity of commercial kits. To confirm the presence or absence of
T. cruzi
infection, the combination of TESA-blot and ELISA-bioMérieux may be suggested as the best alternative. Individually, the TESA-blot performed the closest to the gold standard; however, it is not commercially available.
We propose an extended parametric class of models for analysing multiple failure data where the study subjects can experience repeated events. The general framework allows a broad class of hazard or intensity models including the Poisson and renewal process models as very special cases. A proportional intensity baseline function is assumed for the model with covariates. Maximum likelihood estimation is discussed. A particular flexible parametrization is considered in details. Theoretical calculation of the information matrix is used to assess when discrimination between different kinds of dependency is likely to be feasible.
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