ArticleFrontiers in cardiovascular medicine2023
A novel model for predicting intravenous immunoglobulin-resistance in Kawasaki disease: a large cohort study.
Article in Frontiers in cardiovascular medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 5 of them syntheses that pooled it.
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Who cites it
12 citing papers in PubMed, 5 syntheses or guidelines pooled it, 10 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
- Establishment and validation of risk prediction model to predict intravenous immunoglobulin-resistance in Kawasaki disease based on meta-analysis of 15 cohorts.Italian journal of pediatrics · 2025Pooled it
- Prevalence of IVIG resistance in Kawasaki disease: a systematic review and meta-analysis.Frontiers in pediatrics · 2025Pooled it
- C-reactive protein to albumin ratio as a prognostic tool for predicting intravenous immunoglobulin resistance in children with kawasaki disease: a systematic review of cohort studies.Pediatric rheumatology online journal · 2024Pooled it
- Machine learning model for intravenous immunoglobulin resistance in Kawasaki disease: model development and validation study.World journal of pediatrics : WJP · 2026Article
- Nomogram for Predicting Regression of Persistent Coronary Artery Aneurysms in Kawasaki Disease: A Three-year Follow-up Cohort Study in Southwest China.Journal of inflammation research · 2026Article
- Association between C-reactive protein-albumin-lymphocyte (CALLY) index with intravenous immunoglobulin non-response in Kawasaki disease.Annals of medicine · 2025Article
- C-reactive protein-to-albumin ratio as a predictor of 28-day mortality in critically ill pediatric patients: a retrospective cohort study.BMC pediatrics · 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
- Knowledge framework of intravenous immunoglobulin resistance in the field of Kawasaki disease: A bibliometric analysis (1997-2023).Immunity, inflammation and disease · 2024Article
- Role of Pyroptosis in IVIG-Resistant Kawasaki Disease and the Establishment of a New Predictive Model.Journal of inflammation research · 2024Article
Corrections and comments
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Authors and funding
17 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Predicting intravenous immunoglobulin (IVIG)-resistant Kawasaki disease (KD) can aid early treatment and prevent coronary artery lesions. A clinically consistent predictive model was developed for IVIG resistance in KD. Methods: In this retrospective cohort study of children diagnosed with KD from January 1, 2016 to December 31, 2021, a scoring system was constructed. A prospective model validation was performed using the dataset of children with KD diagnosed from January 1 to June 2022. The least absolute shrinkage and selection operator (LASSO) regression analysis optimally selected baseline variables. Multivariate logistic regression incorporated predictors from the LASSO regression analysis to construct the model. Using selected variables, a nomogram was developed. The calibration plot, area under the receiver operating characteristic curve (AUC), and clinical impact curve (CIC) were used to evaluate model performance. Results: Of 1975, 1,259 children (1,177 IVIG-sensitive and 82 IVIG-resistant KD) were included in the training set. Lymphocyte percentage; C-reactive protein/albumin ratio (CAR); and aspartate aminotransferase, sodium, and total bilirubin levels, were risk factors for IVIG resistance. The training set AUC was 0.825 (sensitivity, 0.723; specificity, 0.744). CIC indicated good clinical application of the nomogram. Conclusion: The nomogram can well predict IVIG resistance in KD. CAR was an important marker in predicting IVIG resistance in Kawasaki disease.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.