A Nomogram Model Identifies Eosinophilic Frequencies to Powerfully Discriminate Kawasaki Disease From Febrile Infections

Frontiers in Pediatrics

article

Xiao-Ping Liu¹  Xi Liu¹  Yi-Shuang Huang¹  Han-Bing Xia¹  Yi Sun¹  Xin-Ling Lang¹  Qiang-Zi Li¹  Chun-Yi Liu¹  Ho-Chang Kuo²  Wei-Dong Huang¹ 

[1] The Department of Emergency and Pediatrics, Shenzhen Baoan Women's and Children's Hospital, Jinan University;Department of Pediatrics, Kawasaki Disease Center, Kaohsiung Chang Gung Memorial Hospital;College of Medicine, Chang Gung University

关键词: Kawasaki disease;    nomogram model;    white blood cell (WBC);    alanine transaminase (ALT);    eosinophil;    albumin (ALB);    C-reactive protein;   

DOI  :  10.3389/fped.2020.559389

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

Background: Kawasaki disease (KD) is a form of systemic vasculitis that occurs primarily in children under the age of 5 years old. No single laboratory data can currently distinguish KD from other febrile infection diseases. The purpose of this study was to establish a laboratory data model that can differentiate between KD and other febrile diseases caused by an infection in order to prevent coronary artery complications in KD. Methods: This study consisted of a total of 800 children (249 KD and 551 age- and gender-matched non-KD febrile infection illness) as a case-control study. Laboratory findings were analyzed using univariable, multivariable logistic regression, and nomogram models. Results: We selected 562 children at random as the model group and 238 as the validation group. The predictive nomogram included high eosinophil percentage (100 points), high C-reactive protein (93 points), high alanine transaminase (84 points), low albumin (79 points), and high white blood cell (64 points), which generated an area under the curve of 0.873 for the model group and 0.905 for the validation group. Eosinophilia showed the highest OR: 5.015 (95% CI:−3.068–8.197) during multiple logistic regression. The sensitivity and specificity in the validation group were 84.1 and 86%, respectively. The calibration curves of the validation group for the probability of KD showed near an agreement to the actual probability. Conclusion: Eosinophilia is a major factor in this nomogram model and had high precision for predicting KD. This report is the first among the existing literature to demonstrate the important role of eosinophil in KD by nomogram.

【 授权许可】

CC BY