Evaluation of Four Lateral Flow Assays for the Detection of Legionella Urinary AntigenShow others and affiliations
2021 (English)In: Microorganisms, E-ISSN 2076-2607, Vol. 9, no 3, article id 493Article in journal (Refereed) Published
Abstract [en]
Urinary antigen tests (UATs) are often used to diagnose Legionnaires' disease as they are rapid and easy to perform on readily obtainable urine samples without the need for specialized skills compared to conventional methods. Recently developed automated readers for UATs may provide objective results interpretation, especially in cases of weak result bands. Using 53 defined patient urine samples, we evaluated the performance of the BinaxNOW Legionella Antigen Card (Abbott), ImmuView S. pneumoniae and Legionella (SSI Diagnostica), STANDARD F Legionella Ag FIA (SD Biosensor), and Sofia Legionella FIA (Quidel) simultaneously with their respective automated readers. Automatic and visual interpretation of result bands were also compared for the immunochromatography-based BinaxNOW and ImmuView UATs. Overall sensitivity and specificity of Legionella UATs were 53.9-61.5% and 90.0-94.9%, respectively. All four UATs successfully detected all samples from L. pneumophila serogroup 1-positive patients, but most failed to detect samples for Legionella spp., or other serogroups. Automatic results interpretation of results was found to be mostly concordant with visual results reading. In conclusion, the performance of the four UATs were similar to each other in the detection of Legionella urinary antigen with no major difference between automated or visual results reading.
Place, publisher, year, edition, pages
MDPI, 2021. Vol. 9, no 3, article id 493
Keywords [en]
BinaxNOW, ImmuView, Legionella antigen, Legionella pneumophila, STANDARD F, Sofia, pneumonia, urinary antigen test (UAT)
National Category
Infectious Medicine
Identifiers
URN: urn:nbn:se:oru:diva-90123DOI: 10.3390/microorganisms9030493ISI: 000633910400001PubMedID: 33652772Scopus ID: 2-s2.0-85101620403OAI: oai:DiVA.org:oru-90123DiVA, id: diva2:1533917
Funder
Vinnova, 2018-038962021-03-042021-03-042021-04-06Bibliographically approved