Classification of Dengue Illness Based on Readily Available Laboratory Data

被引:25
|
作者
Potts, James A. [1 ,2 ]
Thomas, Stephen J. [3 ]
Srikiatkhachorn, Anon [1 ,2 ]
Supradish, Pra-on [4 ]
Li, Wenjun [1 ,2 ]
Nisalak, Ananda [3 ]
Nimmannitya, Suchitra [4 ]
Endy, Timothy P. [5 ]
Libraty, Daniel H. [1 ,2 ]
Gibbons, Robert V. [3 ]
Green, Sharone [1 ,2 ]
Rothman, Alan L. [1 ,2 ]
Kalayanarooj, Siripen [4 ]
机构
[1] Univ Massachusetts, Sch Med, Ctr Infect Dis & Vaccine Res, Worcester, MA USA
[2] Univ Massachusetts, Sch Med, Dept Med, Worcester, MA USA
[3] Armed Forces Res Inst Med Sci, Dept Virol, Bangkok 10400, Thailand
[4] Queen Sirikit Natl Inst Child Hlth, Bangkok, Thailand
[5] SUNY Upstate Med Univ, Dept Med, Syracuse, NY USA
来源
基金
美国国家卫生研究院;
关键词
JAPANESE ENCEPHALITIS; HEMORRHAGIC-FEVER; CASE DEFINITIONS; SEVERITY; NEED; INFECTIONS; NICARAGUA; FEATURES; CHILDREN; SYSTEM;
D O I
10.4269/ajtmh.2010.10-0135
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
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 OF!) 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.
引用
收藏
页码:781 / 788
页数:8
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