Dengue NS1 antigen as a marker of severe clinical disease View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2014-12

AUTHORS

Shiran Ajith Paranavitane, Laksiri Gomes, Achala Kamaladasa, Thiruni N Adikari, Nilanka Wickramasinghe, Chandima Jeewandara, Narangoda Liyanage Ajantha Shyamali, Graham Stuart Ogg, Gathsaurie Neelika Malavige

ABSTRACT

BACKGROUND: Early detection of complications significantly reduces dengue associated mortality and morbidity. We set out to determine if the NS1 rapid antigen detection test could be used as a point of care test to predict severe disease. METHODS: 186 adult patients with confirmed dengue were enrolled during day 3-8 of illness. Clinical and laboratory parameters were recorded during the course of the illness and NS1 antigen levels were determined using both the Panbio dengue early ELISA (Panbio, Australia) and a NS1 rapid antigen detection kit (SD Bioline, South Korea). RESULTS: 59.1% of patients presented to hospital on day 5-6 of illness when NS1 antigen positivity was significantly (p = 0.008) associated with severe dengue (odds ratio 3.0, 95% CI 1.39 to 6.47) and the NS1 antigen levels were significantly higher (p = 0.03) in those who went on to develop shock. Serum NS1 antigen levels significantly (p < 0.0001) and inversely correlated with the total white cell counts and lymphocyte counts. The bedside NS1 test showed comparable sensitivity (97.4%) and specificity (93.7%) to the laboratory NS1 test in our setting and cohort. CONCLUSION: NS1 antigen positivity is associated with a higher risk of developing severe dengue especially when positive beyond day 5 of illness in our cohort, and while further validation studies are required, the test can therefore potentially be used as a bedside point of care test as a warning sign of severe dengue. More... »

PAGES

570

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s12879-014-0570-8

DOI

http://dx.doi.org/10.1186/s12879-014-0570-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1032350092

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/25366086


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RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s12879-014-0570-8'


 

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312 MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, Oxford NIHR Biomedical Research Centre and University of Oxford, OX3 9DS, Oxford, UK
313 rdf:type schema:Organization
 




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