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Machine learning prediction models for intravenous immunoglobulin resistance in Kawasaki disease: a meta-analysis

Abstract Background Intravenous immunoglobulin (IVIG) is the standard initial treatment for Kawasaki disease (KD). However, approximately 20% of patients are resistant, who have a significantly increased risk of coronary artery lesions. Early prediction of IVIG resistance is crucial for improving ou...

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Hoofdauteurs: Chuankun Zhang, Yongle Zhao, Yangzhongyi Liu, Chang Liu, Yi Wei, Nuo Xu, Hengpeng Luo, Penghui Yang, Qijian Yi
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: BMC 2026-04-01
Reeks:BMC Medical Informatics and Decision Making
Onderwerpen:
Kawasaki disease
Intravenous immunoglobulin resistance
Machine learning
Prediction model
Meta-analysis
Predictors
Online toegang:https://doi.org/10.1186/s12911-026-03494-1
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