Dataset Information

Evaluation of Kawasaki disease risk-scoring systems for intravenous immunoglobulin resistance.

ABSTRACT:

Objectives

To assess the performance of 3 risk scores from Japan that were developed to predict, in children with Kawasaki disease, resistance to intravenous immunoglobulin (IVIG) treatment.

Study design

We used data from a randomized trial of pulsed steroids for primary treatment of Kawasaki disease to assess operating characteristics of the 3 risk scores, and we examined whether steroid therapy lowers the risk of coronary artery abnormalities in patients prospectively classified as IVIG resistant.

Results

For comparability with published cohorts, we analyzed the data of 99 patients who were not treated with steroids (16% IVIG-retreated) and identified male sex, lower albumin level, and higher aspartate aminotransferase level as independent risk factors for IVIG resistance. The Kobayashi score was similar in IVIG-resistant and -responsive patients, yielding a sensitivity of 33% and specificity of 87%. There was no interaction of high-risk versus low-risk status by treatment received (steroid versus placebo) with any of the 3 risk score algorithms.

Conclusion

Risk-scoring systems from Japan have good specificity but low sensitivity for predicting IVIG resistance in a North American cohort. Primary steroid therapy did not improve coronary outcomes in patients prospectively classified as being at high-risk for IVIG resistance.

SUBMITTER: Sleeper LA

PROVIDER: S-EPMC3075321 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature

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Publications

Evaluation of Kawasaki disease risk-scoring systems for intravenous immunoglobulin resistance.

Sleeper Lynn A LA Minich L Luann LL McCrindle Brian M BM Li Jennifer S JS Mason Wilbert W Colan Steven D SD Atz Andrew M AM Printz Beth F BF Baker Annette A Vetter Victoria L VL Newburger Jane W JW

The Journal of pediatrics 20101218 5

<h4>Objectives</h4>To assess the performance of 3 risk scores from Japan that were developed to predict, in children with Kawasaki disease, resistance to intravenous immunoglobulin (IVIG) treatment.<h4>Study design</h4>We used data from a randomized trial of pulsed steroids for primary treatment of Kawasaki disease to assess operating characteristics of the 3 risk scores, and we examined whether steroid therapy lowers the risk of coronary artery abnormalities in patients prospectively classified ...[more]

PMID: 21168857

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Project description:BackgroundAbout 10-20% of Kawasaki disease (KD) patients are resistant to the initial infusion of intravenous immunoglobin (IVIG). The aim of this study was to assess whether IVIG resistance in KD patients could be predicted using standard clinical and laboratory features.MethodsData were from two cohorts: a Korean cohort of 7101 KD patients from 2015 to 2017 and a cohort of 649 KD patients from San Diego enrolled from 1998 to 2021. Features included laboratory values, the worst Z-score from the initial echocardiogram or during hospitalization, and the five clinical KD signs at presentation.ResultsFive machine learning models achieved a maximum median AUC of 0.711 [IQR: 0.706-0.72] in the Korean cohort and 0.696 [IQR: 0.609-0.722] in the San Diego cohort during stratified 10-fold cross-validation using significant laboratory features identified from univariate analysis. Adding the Z-score, KD clinical signs, or both did not considerably improve the median AUC in either cohort.ConclusionsUsing commonly measured clinical laboratory data alone or in conjunction with echocardiographic findings and clinical features is not sufficient to predict IVIG resistance. Further attempts to predict IVIG resistance will need to incorporate additional data such as transcriptomics, proteomics, and genetics to achieve meaningful predictive utility.ImpactWe demonstrated that laboratory, echocardiographic, and clinical findings cannot predict intravenous immunoglobin (IVIG) resistance to a clinically meaningful extent using machine learning in a homogenous Asian or ethnically diverse population of patients with Kawasaki disease (KD). Visualizing these features using uniform manifold approximation and projection (UMAP) is an important step to evaluate predictive utility in a qualitative manner. Further attempts to predict IVIG resistance in KD patients will need to incorporate novel biomarkers or other specialized features such as genetic differences or transcriptomics to be clinically useful.

Project description:ObjectiveWe aimed to develop a nomogram to predict risk of resistance to intravenous immunoglobulin (IVIG) in children with Kawasaki disease in eastern China.MethodsWe retrospectively analysed the data of children with Kawasaki disease who received IVIG during hospitalisation at Soochow University Affiliated Children's Hospital. IVIG resistance was defined as recrudescent or persistent fever ≥36 h after the end of the IVIG infusion. Baseline variables were analysed using least absolute shrinkage and selection operator (LASSO) to identify the predictors of IVIG resistance, which were then used to construct a predictive nomogram. Calibration curve and area under the receiver operating characteristic curve (AUC) were used to evaluate the performance of the model. The predictive nomogram was validated on test sets of external data and prospective data.ResultsBetween January 2015 and December 2020, 1293 Kawasaki disease patients were hospitalized in Soochow University Affiliated Children's Hospital. Among them, 72 (5.57%) showed IVIG resistance. LASSO identified haemoglobin, percentage of neutrophils, C-reactive protein level, platelet count, serum albumin, serum sodium, serum alkaline phosphatase, coronary artery damage, and complete Kawasaki disease as risk factors for IVIG resistance. The nomogram constructed using these factors showed satisfactory discriminatory power (AUC, 0.75), and sensitivity (0.74) and specificity (0.64). In the external data and prospective data, the AUC was 0.66 and 0.83, respectively, the sensitivity was 0.86 and 1, respectively, and the specificity was 0.49 and 0.60, respectively.ConclusionsThe predictive nomogram constructed using nine factors associated with IVIG resistance in children with Kawasaki disease could be a useful tool for identifying patients likely to show IVIG resistance. This nomogram may help reduce the risk of coronary artery lesions.Key MessagesNone of the IVIG resistance scoring systems has shown consistently good performance in previous studies. Tools to predict the risk of IVIG resistance in eastern China are lacking.In our series, haemoglobin level, percentage of neutrophils, platelet count, coronary artery damage, incomplete Kawasaki disease, and CRP, serum albumin, serum sodium, and serum alkaline phosphatase levels were risk factors of IVIG resistance in hospitalized children in the eastern China cities of Suzhou and Fuzhou.We propose an easy-to-use nomogram to predict the risk factors of IVIG resistance in hospitalized children.

Dataset Information

Evaluation of Kawasaki disease risk-scoring systems for intravenous immunoglobulin resistance.

Objectives

Study design

Results

Conclusion

Publications

Evaluation of Kawasaki disease risk-scoring systems for intravenous immunoglobulin resistance.

Similar Datasets

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