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J Clin Microbiol ; 60(2): e0155021, 2022 02 16.
Artigo em Inglês | MEDLINE | ID: mdl-34851685

RESUMO

The diagnosis of neurocysticercosis (NCC) depends on neuroimaging and serological confirmation. While antibody detection by enzyme-linked immunoelectrotransfer blot (EITB) fails to predict viable NCC, EITB banding patterns provide information about the host's infection course. Adding antigen enzyme-linked immunosorbent assay (Ag-ELISA) results to EITB banding patterns may improve their ability to predict or rule out of viable NCC. We assessed whether combining EITB banding patterns with Ag-ELISA improves discrimination of viable infection in imaging-confirmed parenchymal NCC. EITB banding patterns were grouped into classes using latent class analysis. True-positive and false-negative Ag-ELISA results in each class were compared using Fisher's exact test. Four classes were identified: 1, EITB negative or positive to GP50 alone (GP50 antigen family); 2, positive to GP42-39 and GP24 (T24/42 family), with or without GP50; and 3 and 4, positive to GP50, GP42-39, and GP24 and reacting to bands in the 8-kDa family. Most cases in classes 3 and 4 had viable NCC (82% and 88%, respectively) compared to classes 2 and 1 (53% and 5%, respectively). Adding positive Ag-ELISA results to class 2 predicted all viable NCC cases (22/22 [100%]), whereas 11/40 patients (27.5%) Ag-ELISA negative had viable NCC (P < 0.001). Only 1/4 patients (25%) Ag-ELISA positive in class 1 had viable NCC, whereas 1/36 patients (2.8%) Ag-ELISA negative had viable NCC (P = 0.192). In classes 3 and 4, adding Ag-ELISA was not contributory. Combining Ag-ELISA with EITB banding patterns improves discrimination of viable from nonviable NCC, particularly for class 2 responses. Together, these complement neuroimaging more appropriately for the diagnosis of viable NCC.


Assuntos
Neurocisticercose , Taenia solium , Animais , Anticorpos Anti-Helmínticos , Antígenos de Helmintos , Ensaio de Imunoadsorção Enzimática/métodos , Humanos , Neurocisticercose/diagnóstico , Sensibilidade e Especificidade
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