Literature DB >> 30026252

Predictive tool for intravenous immunoglobulin resistance of Kawasaki disease in Beijing.

Shuai Yang1, Junmei Zhang2, Ruixia Song1, Xiaohui Li1, Caifeng Li2.   

Abstract

OBJECTIVE: To construct a predictive tool for the efficacy of intravenous immunoglobulin (IVIG) therapy in children with Kawasaki disease (KD) in Beijing, China.
DESIGN: This was a cohort study. Data set (including clinical profiles and laboratory findings) of children with KD diagnosed between 1 January 2010 and 31 December 2015 was used to analyse the risk factors and construct a scoring system. Data set of children with KD diagnosed between 1 January 2016 and 1 December 2016 was used to validate this model.
SETTING: Children's Hospital Capital Institute of Pediatrics and Beijing Children's Hospital. PATIENTS: 2102 children diagnosed with KD.
INTERVENTIONS: No. MAIN OUTCOME MEASURES: Responsiveness to IVIG.
RESULTS: The predictive tool included C reactive protein ≥90 mg/L (3 points), neutrophil percentage ≥70% (2.5 points), sodium ion concentration <135 mmol/L (3 points), albumin <35 g/L (2.5 points) and total bilirubin >20 μmol/L (5 points), which generated an area under the the receiver operating characteristic curve of 0.77 (95% CI 0.71 to 0.82) for the internal validation data set, and 0.69 (95% CI 0.58 to 0.81) and 0.63 (95% CI 0.53 to 0.72) for two external validation data sets, respectively. If a total of ≥6 points were considered high-risk for IVIG resistance, sensitivity and specificity were 56% and 79% in the internal verification, and the predictive ability was similar in the external validation.
CONCLUSIONS: The predictive tool is helpful in early screening of high-risk IVIG resistance of KD in the Beijing area. Consequently, it will guide the clinician in selecting appropriate individualised regimens for the initial treatment of this disease, which is important for the prevention of coronary complications. © Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.

Entities:  

Keywords:  cardiology; statistics

Year:  2018        PMID: 30026252     DOI: 10.1136/archdischild-2017-314512

Source DB:  PubMed          Journal:  Arch Dis Child        ISSN: 0003-9888            Impact factor:   3.791


  17 in total

1.  The role of age-specific N-terminal pro-brain natriuretic peptide cutoff values in predicting intravenous immunoglobulin resistance in Kawasaki disease: a prospective cohort study.

Authors:  Shuran Shao; Chunyan Luo; Kaiyu Zhou; Yimin Hua; Mei Wu; Lei Liu; Xiaoliang Liu; Chuan Wang
Journal:  Pediatr Rheumatol Online J       Date:  2019-09-18       Impact factor: 3.054

2.  A new model for predicting intravenous immunoglobin-resistant Kawasaki disease in Chongqing: a retrospective study on 5277 patients.

Authors:  Xu-Hai Tan; Xiao-Wei Zhang; Xiao-Yun Wang; Xiang-Qian He; Chu Fan; Tie-Wei Lyu; Jie Tian
Journal:  Sci Rep       Date:  2019-02-11       Impact factor: 4.379

3.  Predictive value of serum procalcitonin for both initial and repeated immunoglobulin resistance in Kawasaki disease: a prospective cohort study.

Authors:  Shuran Shao; Chunyan Luo; Kaiyu Zhou; Yimin Hua; Mei Wu; Lei Liu; Xiaoliang Liu; Chuan Wang
Journal:  Pediatr Rheumatol Online J       Date:  2019-11-27       Impact factor: 3.054

4.  A New Scoring System for Prediction of Intravenous Immunoglobulin Resistance of Kawasaki Disease in Infants Under 1-Year Old.

Authors:  Shu Wu; Yuan Long; Selena Chen; Yaqian Huang; Ying Liao; Yan Sun; Qingyou Zhang; Chunyu Zhang; Hui Yan; Jianguang Qi; Xueqin Liu; Yonghong Chen; Yong Zhang; Junbao Du
Journal:  Front Pediatr       Date:  2019-12-11       Impact factor: 3.418

5.  Predictive value of C-reactive protein to albumin ratio as a biomarker for initial and repeated intravenous immunoglobulin resistance in a large cohort of Kawasaki disease patients: a prospective cohort study.

Authors:  Xiaoliang Liu; Lin Wang; Kaiyu Zhou; Shuran Shao; Yimin Hua; Mei Wu; Lei Liu; Chuan Wang
Journal:  Pediatr Rheumatol Online J       Date:  2021-03-12       Impact factor: 3.054

6.  Comparison of Machine Learning Models for Prediction of Initial Intravenous Immunoglobulin Resistance in Children With Kawasaki Disease.

Authors:  Yasutaka Kuniyoshi; Haruka Tokutake; Natsuki Takahashi; Azusa Kamura; Sumie Yasuda; Makoto Tashiro
Journal:  Front Pediatr       Date:  2020-12-03       Impact factor: 3.418

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

Authors:  Xiao-Ping Liu; Yi-Shuang Huang; Han-Bing Xia; Yi Sun; Xin-Ling Lang; Qiang-Zi Li; Chun-Yi Liu; Ho-Chang Kuo; Wei-Dong Huang; Xi Liu
Journal:  Front Pediatr       Date:  2020-12-11       Impact factor: 3.418

8.  Serum sodium level associated with coronary artery lesions in patients with Kawasaki disease.

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Journal:  Clin Rheumatol       Date:  2021-08-07       Impact factor: 2.980

9.  Prognostic value of pretreatment prognostic nutritional index in intravenous immunoglobulin-resistant Kawasaki disease.

Authors:  Gang Li; Xiumei Xu; Pengyuan Chen; Rumeng Zeng; Bin Liu
Journal:  Heart Vessels       Date:  2021-03-08       Impact factor: 2.037

10.  Predictive model based on gene and laboratory data for intravenous immunoglobulin resistance in Kawasaki disease in a Chinese population.

Authors:  Li Meng; Zhen Zhen; Xiao-Hui Li; Yue Yuan; Qian Jiang; Wei Yao; Ming-Ming Zhang; Ai-Jie Li; Lin Shi
Journal:  Pediatr Rheumatol Online J       Date:  2021-06-26       Impact factor: 3.054

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