ArticleScientific reports2019
A new model for predicting intravenous immunoglobin-resistant Kawasaki disease in Chongqing: a retrospective study on 5277 patients.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 4 of them syntheses that pooled it.
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Who cites it
33 citing papers in PubMed, 4 syntheses or guidelines pooled it, 54 citations in OpenAlex.
- 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
- Machine learning prediction models for intravenous immunoglobulin resistance in Kawasaki disease: a meta-analysis.BMC medical informatics and decision making · 2026Pooled it
- Pooled it
- Risk Factors of Intravenous Immunoglobulin Resistance in Children With Kawasaki Disease: A Meta-Analysis of Case-Control Studies.Frontiers in pediatrics · 2020Pooled it
- Machine learning model for intravenous immunoglobulin resistance in Kawasaki disease: model development and validation study.World journal of pediatrics : WJP · 2026Article
- Predictive value of the hemoglobin-albumin-lymphocyte-platelet score for intravenous immunoglobulin resistance in children with Kawasaki disease.Italian journal of pediatrics · 2026Article
- Development and validation of a novel interpretable machine learning model integrating immune-inflammatory indicators for intravenous immunoglobulin resistance in Kawasaki disease.Translational pediatrics · 2026Article
- Analysis of risk factors of coronary artery lesions in Kawasaki disease and study of IVIG treatment response.BMC immunology · 2026Article
- Red blood cell distribution width predicts coronary artery lesions in Kawasaki disease: insights from a Japanese cohort.Pediatric rheumatology online journal · 2025Article
- Identification of novel metabolism-related biomarkers of Kawasaki disease by integrating single-cell RNA sequencing analysis and machine learning algorithms.Frontiers in immunology · 2025Article
- Nutrition-Associated Biomarkers in Predicting Intravenous Immunoglobulin Resistance and Coronary Artery Lesions in Kawasaki Disease: A Systematic Review and Meta-Analysis.Food science & nutrition · 2025Review
- Neutrophil percentage-to-albumin ratio is a potential marker of intravenous immunoglobulin resistance in Kawasaki disease.Scientific reports · 2024Article
- Risk-prediction models for intravenous immunoglobulin resistance in Kawasaki disease: Risk-of-Bias Assessment using PROBAST.Pediatric research · 2023Article
- Predictive value of albumin for intravenous immunoglobulin resistance in a large cohort of Kawasaki disease patients.Italian journal of pediatrics · 2023Article
- Clinical Signs of Kawasaki Disease from the Perspective of Epithelial-to-Mesenchymal Transition Recruiting Erythrocytes: A Literature Review.Reviews in cardiovascular medicine · 2023Review
- Distinctive serum lipidomic profile of IVIG-resistant Kawasaki disease children before and after treatment.PloS one · 2023Article
- Evaluation of Formosa score and diagnostic sensitivity and specificity of four Asian risk scores for predicting intravenous immunoglobulin resistance in Kawasaki disease: a bivariate meta-analysis.Frontiers in cardiovascular medicine · 2023Review
- Predicting immunoglobulin resistance in Kawasaki disease: an assessment of neutrophil to lymphocyte platelet ratio.Italian journal of pediatrics · 2022Article
- Comparison of IVIG resistance predictive models in Kawasaki disease.Pediatric research · 2022Article
- Serum sodium level associated with coronary artery lesions in patients with Kawasaki disease.Clinical rheumatology · 2022Article
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7 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Accurate evaluation of individual risk of intravenous immunoglobin (IVIG)-resistance is critical for adopting regimens for the first treatment and prevention of coronary artery lesions (CALs) in patients with Kawasaki disease (KD).
methodsThe KD patients hospitalized in Chongqing Children's Hospital, in west China, from October 2007 to December 2017 were retrospectively reviewed. Data were collected and compared between IVIG-resistant group and IVIG-responsive group. The independent risk factors were determined using multivariate regression analysis. A new prediction model was built and compared with the previous models.
resultsA total of 5277 subjects were studied and eight independent risk factors were identified including higher red blood cell distribution width (RDW), lower platelet count (PLT), lower percentage of lymphocyte (P-LYM), higher total bile acid (TBA), lower albumin, lower serum sodium level, higher degree of CALs (D-CALs) and younger age. The new predictive model showed an AUC of 0.74, sensitivity of 76% and specificity of 59%. For individual's risk probability of IVIG-resistance, an equation was given.
conclusionsIVIG-resistance could be predicted by RDW, PLT, P-LYM, TBA, albumin, serum sodium level, D-CALs and age. The new model appeared to be superior to those previous models for KD population in Chongqing city.
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