A comparison of efficacy of six prediction models for intravenous immunoglobulin resistance in Kawasaki disease

Ital J Pediatr. 2018 Mar 9;44(1):33. doi: 10.1186/s13052-018-0475-z.

Abstract

Background: Kawasaki disease (KD) is the most common pediatric vasculitis. Several models have been established to predict intravenous immunoglobulin (IVIG) resistance. The present study was aimed to evaluate the efficacy of prediction models using the medical data of KD patients.

Methods: We collected the medical records of patients hospitalized in the Department of Cardiology in Children's Hospital of Soochow University with a diagnosis of KD from Jan 2015 to Dec 2016. IVIG resistance was defined as recrudescent or persistent fever ≥36 h after the end of their IVIG infusion.

Results: Patients with IVIG resistance tended to be younger, have higher occurrence of rash and changes of extremities. They had higher levels of c-reactive protein, aspartate aminotransferase, neutrophils proportion (N%), total bilirubin and lower level of albumin. Our prediction model had a sensitivity of 0.72 and a specificity of 0.75. Sensitivity of Kobayashi, Egami, Kawamura, Sano and Formosa were 0.72, 0.44, 0.48, 0.20, and 0.68, respectively. Specificity of these models were 0.62, 0.82, 0.66, 0.91, and 0.48, respectively.

Conclusions: Our prediction model had a powerful predictive value in this area, followed by Kobayashi model while all the other prediction models had less excellent performances than ours.

Keywords: Children; Intravenous immunoglobulin resistance; Kawasaki disease; Prediction model.

MeSH terms

  • Child, Preschool
  • China / epidemiology
  • Drug Resistance*
  • Female
  • Forecasting*
  • Hospitals, Pediatric
  • Humans
  • Immunoglobulins, Intravenous / therapeutic use*
  • Immunologic Factors / therapeutic use
  • Infant
  • Male
  • Morbidity
  • Mucocutaneous Lymph Node Syndrome / drug therapy*
  • Mucocutaneous Lymph Node Syndrome / epidemiology
  • Prospective Studies
  • ROC Curve
  • Risk Assessment / methods*
  • Risk Factors

Substances

  • Immunoglobulins, Intravenous
  • Immunologic Factors