Related Experiment Video
Updated: Aug 1, 2025

Assessment of Antibody-based Drugs Effects on Murine Bone Marrow and Peritoneal Macrophage Activation
Published on: December 26, 2017
Prediction Models for Intravenous Immunoglobulin Resistance in Kawasaki Disease: A Meta-analysis
Yasutaka Kuniyoshi1,2, Yasushi Tsujimoto2,3,4, Masahiro Banno2,5,6
1Department of Pediatrics, Tsugaruhoken Medical COOP Kensei Hospital, Hirosaki, Aomori, Japan.
Context:
Approximately 10% to 20% of patients with Kawasaki disease (KD) are refractory to initial intravenous immunoglobulin (IVIG) therapy. KD is mainly associated with coronary artery abnormalities.
Objectives:
To identify and evaluate all developed prediction models for IVIG resistance in patients with KD and synthesize evidence from external validation studies that evaluated their predictive performances.
Data Sources:
PubMed Medline, Dialog Embase, the Cochrane Central Register of Controlled Trials, the World Health Organization International Clinical Trials Registry Platform, and ClinicalTrials.gov were searched from inception until October 5, 2021.
Study Selection:
All cohort studies that reported patients diagnosed with KD who underwent an initial IVIG of 2 g/kg were selected.
Data Extraction:
Study and patient characteristics and model performance measures. Two authors independently extracted data from the studies.
Results:
The Kobayashi, Egami, Sano, Formosa, and Harada scores were the only prediction models with 3 or more external validation of the161 model analyses in 48 studies. The summary C-statistics were 0.65 (95% confidence interval [CI]: 0.57-0.73), 0.63 (95% CI: 0.55-0.71), 0.58 (95% CI: 0.55-0.60), 0.50 (95% CI: 0.36-0.63), and 0.63 (95% CI: 0.44-0.78) for the Kobayashi, Egami, Sano, Formosa, and Harada models, respectively. All 5 models showed low positive predictive values (0.14-0.39) and high negative predictive values (0.85-0.92).
Limitations:
Potential differences in the characteristics of the target population among studies and lack of assessment of calibrations.
Conclusions:
None of the 5 prediction models with external validation accurately distinguished between patients with and without IVIG resistance.
Related Concept Videos
Acute Kidney Injury IV: Diagnostic Studies and Prevention
Two-Compartment Open Model: IV Bolus Administration
The disparity between drug input and the sum of drug transfer rates between...
One-Compartment Model: IV Infusion
The one-compartment model for IV infusion uses mathematical equations to describe the rate of change in drug quantity in the body. At steady-state or infusion equilibrium, the drug input...
Pharmacokinetic Models: Overview
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
Pharmacokinetic Models: Comparison and Selection Criterion
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.

