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Precursors to non-invasive clinical dengue screening: Multivariate signature analysis of in-vivo diffuse skin reflectance spectroscopy on febrile patients in Malaysia

Dengue diagnostics have come a long way. Attempts at breaking away from lab-oriented dengue detection, such as NS1 antigen, IgM or IgG antibodies detection have extensively received numerous coverage. As a result, rapid detection tests (RDTs) have started to gain inroads in medical practice. Rapid d...

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Detalles Bibliográficos
Autores principales: Poh, Abdul Halim, Mahamd Adikan, Faisal Rafiq, Moghavvemi, Mahmoud, Syed Omar, Sharifah Faridah, Poh, Khadijah, Mahyuddin, Mohamad Badrol Hisyam, Yan, Grace, Azizah Ariffin, Mohammad Aizuddin, Harun, Sulaiman Wadi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7112162/
https://www.ncbi.nlm.nih.gov/pubmed/32236132
http://dx.doi.org/10.1371/journal.pone.0228923
Descripción
Sumario:Dengue diagnostics have come a long way. Attempts at breaking away from lab-oriented dengue detection, such as NS1 antigen, IgM or IgG antibodies detection have extensively received numerous coverage. As a result, rapid detection tests (RDTs) have started to gain inroads in medical practice. Rapid detection tests notwithstanding, analysis of blood serum is still a relatively complicated task. This includes the necessity of phlebotomy, centrifugation for blood serum, and other reagent-based tests. Therefore, a non-invasive method of dengue detection was considered. In this study, we present the utility of diffuse reflectance skin spectroscopy (bandwidth of 200-2500nm) on the forearm during the triaging period for dengue screening potential. This is performed with multivariate analysis of 240 triaged febrile/suspected dengue patients. The data is then scrutinized for its clinical validity to be included as either confirmed or probable dengue, or a control group. Based on discriminant analysis of several data normalization models, we can predict the patients’ clinical dengue-positivity at ranges of accuracy between ~93–98% depending on mode of the data, with a probably optimal sensitivity and specificity to the clinical diagnosis of ~89% and ~100% respectively. From the outcomes of this study, we recommend further trials with cautious optimism. With these findings, it is hoped that the elusive non-invasive detection of tropical diseases may gain platform in the near future.