Classification of Dengue Illness Based on Readily Available Laboratory Data

James A. Potts Center for Infectious Disease and Vaccine Research, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Virology, United States Army Medical Component–Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand; Queen Sirikit National Institute of Child Health, Bangkok, Thailand; State University of New York, Upstate Medical University, Syracuse, New York

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Stephen J. Thomas Center for Infectious Disease and Vaccine Research, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Virology, United States Army Medical Component–Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand; Queen Sirikit National Institute of Child Health, Bangkok, Thailand; State University of New York, Upstate Medical University, Syracuse, New York

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Anon Srikiatkhachorn Center for Infectious Disease and Vaccine Research, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Virology, United States Army Medical Component–Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand; Queen Sirikit National Institute of Child Health, Bangkok, Thailand; State University of New York, Upstate Medical University, Syracuse, New York

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Pra-on Supradish Center for Infectious Disease and Vaccine Research, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Virology, United States Army Medical Component–Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand; Queen Sirikit National Institute of Child Health, Bangkok, Thailand; State University of New York, Upstate Medical University, Syracuse, New York

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Wenjun Li Center for Infectious Disease and Vaccine Research, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Virology, United States Army Medical Component–Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand; Queen Sirikit National Institute of Child Health, Bangkok, Thailand; State University of New York, Upstate Medical University, Syracuse, New York

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Ananda Nisalak Center for Infectious Disease and Vaccine Research, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Virology, United States Army Medical Component–Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand; Queen Sirikit National Institute of Child Health, Bangkok, Thailand; State University of New York, Upstate Medical University, Syracuse, New York

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Suchitra Nimmannitya Center for Infectious Disease and Vaccine Research, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Virology, United States Army Medical Component–Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand; Queen Sirikit National Institute of Child Health, Bangkok, Thailand; State University of New York, Upstate Medical University, Syracuse, New York

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Timothy P. Endy Center for Infectious Disease and Vaccine Research, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Virology, United States Army Medical Component–Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand; Queen Sirikit National Institute of Child Health, Bangkok, Thailand; State University of New York, Upstate Medical University, Syracuse, New York

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Daniel H. Libraty Center for Infectious Disease and Vaccine Research, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Virology, United States Army Medical Component–Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand; Queen Sirikit National Institute of Child Health, Bangkok, Thailand; State University of New York, Upstate Medical University, Syracuse, New York

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Robert V. Gibbons Center for Infectious Disease and Vaccine Research, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Virology, United States Army Medical Component–Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand; Queen Sirikit National Institute of Child Health, Bangkok, Thailand; State University of New York, Upstate Medical University, Syracuse, New York

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Sharone Green Center for Infectious Disease and Vaccine Research, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Virology, United States Army Medical Component–Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand; Queen Sirikit National Institute of Child Health, Bangkok, Thailand; State University of New York, Upstate Medical University, Syracuse, New York

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Alan L. Rothman Center for Infectious Disease and Vaccine Research, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Virology, United States Army Medical Component–Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand; Queen Sirikit National Institute of Child Health, Bangkok, Thailand; State University of New York, Upstate Medical University, Syracuse, New York

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Siripen Kalayanarooj Center for Infectious Disease and Vaccine Research, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Virology, United States Army Medical Component–Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand; Queen Sirikit National Institute of Child Health, Bangkok, Thailand; State University of New York, Upstate Medical University, Syracuse, New York

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The aim of this study was to examine retrospective dengue-illness classification using only clinical laboratory data, without relying on X-ray, ultrasound, or percent hemoconcentration. We analyzed data from a study of children who presented with acute febrile illness to two hospitals in Thailand. Multivariable logistic regression models were used to distinguish: (1) dengue hemorrhagic fever (DHF) versus dengue fever (DF), (2) DHF versus DF + other febrile illness (OFI), (3) dengue versus OFI, and (4) severe dengue versus non-severe dengue + OFI. Data from the second hospital served as a validation set. There were 1,227 patients in the analysis. The sensitivity of the models ranged from 89.2% (dengue versus OFI) to 79.6% (DHF versus DF). The models showed high sensitivity in the validation dataset. These models could be used to calculate a probability and classify patients based on readily available clinical laboratory data, and they will need to be validated in other dengue-endemic regions.

Author Notes

*Address correspondence to Alan L. Rothman, 55 Lake Avenue North, Worcester, MA 01655. E-mail: Alan.Rothman@umassmed.edu

Financial support: This work was supported by National Institutes of Health Grant NIH-P01AI34533, Centers for Disease Control and Prevention Office of the Director Grant 1R36CK00123-01, and the Military Infectious Disease Research Program. The opinions or assertions contained herein are the private ones of the authors and are not to be construed as official or reflecting the view of the US Government. The authors have no conflicting financial interests.

Authors' addresses: James A. Potts, Anon Srikiatkhachorn, Wenjun Li, Daniel H. Libraty, Sharone Green, and Alan L. Rothman, Center for Infectious Disease and Vaccine Research and Department of Medicine, University of Massachusetts Medical School, Worcester, MA, E-mails: James.Potts@umassmed.edu, Anon.Srikiatkhachorn@umassmed.edu, Wenjun.Li@umassmed.edu, Daniel.Libraty@umassmed.edu, Sharone.Green@umassmed.edu, and Alan.Rothman@umassmed.edu. Stephen J. Thomas, Ananda Nisalak, and Robert V. Gibbons, Department of Virology, Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand, E-mails: stephen.thomas@afrims.org, anandan@afrims.org, and robert.gibbons@afrims.org. Pra-on Supradish, Suchitra Nimmannitya, and Siripen Kalayanarooj, Queen Sirikit National Institute of Child Health, Bangkok, Thailand, E-mails: praonsu@yahoo.com, sujitran@health.moph.go.th, and sirip@health.moph.go.th. Timothy P. Endy, Department of Medicine, University of New York, Upstate Medical University, Syracuse, NY, E-mail: endyt@upstate.edu.

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