| Autor: |
Scarpaleggia, Marianna, Garzillo, Giada, Lucente, Miriana, Fraccalvieri, Chiara, Randazzo, Nadia, Massaro, Elvira, Galano, Barbara, Ricucci, Valentina, Bruzzone, Bianca, Domnich, Alexander |
| Předmět: |
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| Zdroj: |
Medicina (1010660X); Sep2024, Vol. 60 Issue 9, p1557, 10p |
| Abstrakt: |
Background and Objectives: The steady spread of dengue virus (DENV) poses a profound public health threat worldwide. Reverse transcription real-time polymerase chain reaction (RT2-PCR) has been increasingly recognized as a reference method for the diagnosis of acute dengue infection. The goal of this study was to assess the diagnostic accuracy of five different RT2-PCR kits for the detection of DENV in a historically processed set of sera samples. Materials and Methods: In this retrospective study, 25 sera samples from routinely processed unique adult patients with a known DENV status (previously tested in both molecular and serological assays) were tested in parallel using four conventional (RealStar Dengue PCR Kit 3.0, Clonit'ngo Zika, Dengue & Chikungunya, BioPerfectus Zika Virus/Dengue Virus/Chikungunya Virus Real Time PCR Kit and Novaplex Tropical fever virus) and one sample-to-result (STANDARD M10 Arbovirus Panel) RT2-PCR assays. Additionally, an end-point dilution analysis was conducted in quintuplicate on six serial dilutions of an RNA preparation obtained from a culture-grown DENV serotype 1 strain for a total of 150 tests. Results: The overall accuracy of the evaluated tests ranged from 84% to 100%. In particular, the sensitivity of three conventional RT2-PCR assays (RealStar, Clonit'ngo and Novaplex) was 100% (95% CI: 79.6–100%), while it was lower (73.3%; 95% CI: 48.1–89.1%) for the BioPerfectus kit. The sample-to-result STANDARD M10 panel performed comparatively well, showing a sensitivity of 92.9% (95% CI: 68.5–98.7%). No false positive results were registered in any assay. The end-point dilution analysis suggested that the RealStar kit had the lowest limit of detection. Conclusions: Available RT2-PCR kits for the detection of DENV are highly specific and generally sensitive and, therefore, their implementation in diagnostic pathways is advisable. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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