Urinary Colorimetric Sensor Array and Algorithm to Distinguish Kawasaki Disease from Other Febrile Illnesses

RESEARCH ARTICLE Urinary Colorimetric Sensor Array and Algorithm to Distinguish Kawasaki Disease from Other Febrile Illnesses Zhen Li 1,2☯‡ , Zhou Tan 2☯‡ , Shiying Hao 2☯‡ , Bo Jin 2 , Xiaohong Deng 2 , Guang Hu 2 , Xiaodan Liu 2 , Jie Zhang 2 , Hua Jin 2 , Min Huang 3 , John T. Kanegaye 4,5 , Adriana H. Tremoulet 4,5 , Jane C. Burns 4,5 , Jianmin Wu 1‡ , Harvey J. Cohen 6‡ , Xuefeng B. Ling 2‡ *, Emergency Medicine Kawasaki Disease Research Group ¶ 1 Institution of Microanalytical System, Zhejiang University, Hangzhou, Zhejiang, China, 2 Department of Surgery, Stanford University, Stanford, California, United States of America, 3 Shanghai Children's Hospital, Shanghai Jiao Tong University, Shanghai, China, 4 Department of Pediatrics, University of California San Diego, La Jolla, California, United States of America, 5 Rady Children’s Hospital San Diego, San Diego, California, United States of America, 6 Department of Pediatrics, Stanford University, Stanford, California, United States of America OPEN ACCESS Citation: Li Z, Tan Z, Hao S, Jin B, Deng X, Hu G, et al. (2016) Urinary Colorimetric Sensor Array and Algorithm to Distinguish Kawasaki Disease from Other Febrile Illnesses. PLoS ONE 11(2): e0146733. doi:10.1371/journal.pone.0146733 Editor: Richard C. Willson, University of Houston, UNITED STATES Received: September 28, 2015 Accepted: December 20, 2015 Published: February 9, 2016 Copyright: © 2016 Li 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. Data Availability Statement: Data are available upon request, by contacting bxling@stanford.edu. Funding: This work was supported by Stanford University Spark Program (2013–2014) (URL: http:// med.stanford.edu/sparkmed.html) to XBL and HJC, and American Heart Association (14GRNT20510026) (URL: www.heart.org) to XBL and HJC. This work was supported by the Chinese Scholarship Council (CSC) (URL: http://en.csc.edu.cn/) to ZL. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ☯ These authors contributed equally to this work. ‡ ZL, ZT, and SH are shared first authors on this work. JW, HJC and XBL also contributed equally to this work and are shared last authors on this work. ¶ Membership of the Emergency Medicine Kawasaki Disease Research Group is provided in the Acknowledgments. * bxling@stanford.edu Abstract Objectives Kawasaki disease (KD) is an acute pediatric vasculitis of infants and young children with unknown etiology and no specific laboratory-based test to identify. A specific molecular diagnostic test is urgently needed to support the clinical decision of proper medical interven- tion, preventing subsequent complications of coronary artery aneurysms. We used a simple and low-cost colorimetric sensor array to address the lack of a specific diagnostic test to dif- ferentiate KD from febrile control (FC) patients with similar rash/fever illnesses. Study Design Demographic and clinical data were prospectively collected for subjects with KD and FCs under standard protocol. After screening using a genetic algorithm, eleven compounds including metalloporphyrins, pH indicators, redox indicators and solvatochromic dye cate- gories, were selected from our chromatic compound library (n = 190) to construct a colori- metric sensor array for diagnosing KD. Quantitative color difference analysis led to a decision-tree-based KD diagnostic algorithm. Results This KD sensing array allowed the identification of 94% of KD subjects (receiver operating characteristic [ROC] area under the curve [AUC] 0.981) in the training set (33 KD, 33 FC) and 94% of KD subjects (ROC AUC: 0.873) in the testing set (16 KD, 17 FC). Color PLOS ONE | DOI:10.1371/journal.pone.0146733 February 9, 2016