ArticleBMC pediatrics2024
Evaluating the performance of egami, kobayashi and sano scores in predicting IVIG resistance in infant kawasaki disease.
Article in BMC pediatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.
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Who cites it
9 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Quality and performance of machine learning versus logistic regression for predicting IVIG resistance in Kawasaki disease: a PROBAST+AI systematic comparison.BMC medical research methodology · 2026Pooled it
- Prevalence of IVIG resistance in Kawasaki disease: a systematic review and meta-analysis.Frontiers in pediatrics · 2025Pooled it
- Association between post-intravenous immunoglobulin hypothermia and lower receipt of second-line therapy in Kawasaki disease: a single-center retrospective cohort study.Clinical rheumatology · 2026Article
- Machine learning model for intravenous immunoglobulin resistance in Kawasaki disease: model development and validation study.World journal of pediatrics : WJP · 2026Article
- Construction and subgroup validation of a predictive model for IVIG-resistance in kawasaki disease.Frontiers in cardiovascular medicine · 2026Article
- Clinical utility of CBC-Derived inflammatory markers for predicting IVIG resistance: findings from a Korean infant Kawasaki disease cohort.Pediatric rheumatology online journal · 2025Article
- The clinical value of dynamic monitoring of complete blood count in predicting immunoglobulin resistance in Chinese children with Kawasaki disease.Scientific reports · 2025Article
- Navigating the 2024 AHA guidelines for Kawasaki disease: practical insights for clinicians.World journal of pediatrics : WJP · 2025Article
- Clinical prediction of intravenous immunoglobulin-resistant Kawasaki disease based on interpretable Transformer model.PloS one · 2025Article
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3 authors.
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Abstract
backgroundThis study aimed to evaluate the effectiveness of Egami, Kobayashi and Sano scores in predicting intravenous immunoglobulin (IVIG) resistance in infant Kawasaki disease (KD), considering its unique clinical presentation.
methodsWe retrospectively analysed 143 infants aged < 12 months and diagnosed with KD at a single centre from 2019 to 2023. Patients were divided into IVIG-resistant and IVIG-responsive groups. Demographic, clinical and laboratory data were compared between the groups. The diagnostic performance of Egami, Kobayashi and Sano scores in predicting IVIG resistance was evaluated using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and area under the receiver operating characteristic curve (AUC). Additionally, we developed a new scoring system based on significant predictors identified in our cohort.
resultsAmong 143 infants, 45 (31.5%) showed IVIG resistance. The IVIG-resistant group had a significantly higher rate of coronary artery lesions (15.6% vs. 5.1%, p = 0.036). Incomplete KD was observed in 61.5% of cases. Egami, Kobayashi and Sano scores exhibited low sensitivity (35.6%, 55.6% and 20%, respectively) and moderate specificity (77.6%, 63.3% and 95.9%, respectively) in predicting IVIG resistance. The AUC ranged from 0.583 to 0.674, indicating poor to fair discriminative ability. Our newly developed scoring system, based on total bilirubin and albumin levels, showed similar performance (AUC 0.633) to existing scores.
conclusionsExisting Japanese risk scoring systems and our newly developed score showed limited effectiveness in predicting IVIG resistance in infant KD. The high proportion of incomplete presentation and IVIG resistance in infants highlights the need for age-specific risk assessment and management. Further research is necessary to develop more sophisticated, dedicated prediction model for IVIG resistance in infants with KD.
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