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

• Main Authors: Poh, Abdul Halim, Adikan, Faisal Rafiq Mahamd, Moghavvemi, Mahmoud, Omar, Sharifah Faridah Syed, Poh, Khadijah, Mahyuddin, Mohamad Badrol Hisyam, Yan, Grace, Azizah Ariffin, Mohammad Aizuddin, Harun, Sulaiman Wadi
• Format: Article
• Published: Public Library of Science 2020
• Subjects: R Medicine; TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.um.edu.my/25393/; https://doi.org/10.1371/journal.pone.0228923

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. © 2020 Poh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.