Prediction of intravenous immunoglobulin resistance in Kawasaki disease in children

A machine learning-based model to predict intravenous immunoglobulin resistance in Kawasaki disease

Accurate prediction of intravenous immunoglobulin (IVIG) resistance is crucial for the effective treatment of Kawasaki disease(KD). This study aimed to develop a predictive model for IVIG resistance in patients with Kawasaki disease and to identify the key predictors. The training set underwent cross-validation, and models were constructed using six machine learning algorithms. Model performance was validated through cross-validation, test set evaluation, and two external validation sets evaluation. The model constructed using the random forest algorithm demonstrated the best overall performance among six models. The areas under the receiver operating characteristic curve (AUCs) for 5-fold cross-validation, internal validation, and external validations from Shaoxing and Quzhou were 0.711, 0.751, 0.827, and 0.735, respectively. According to the Shapley additive explanation (SHAP) method, C-reactive protein-to-albumin ratio, prognostic nutritional index, and sex were identified as the most important predictors. Our model demonstrates strong predictive capability for assessing IVIG resistance in Kawasaki disease patients.

Establishment and validation of a nomogram for predicting intravenous immunoglobulin resistance and coronary artery lesion involvement in Kawasaki disease: a retrospective study

OBJECTIVE

We aimed to develop a useful nomogram for early identification of Kawasaki disease (KD) children at a high risk of intravenous immunoglobulin (IVIG) resistance and coronary artery lesion (CAL) complications to improve KD management.

METHODS

Clinical data from 400 patients treated at our hospital between January 1, 2016, and December 31, 2023, were collected. Lasso regression was utilized to screen risk factors for IVIG resistance and CAL involvement. Subsequently, a Logistic regression model incorporating parameters screened by Lasso regression was established and visualized as a nomogram. The discrimination, calibration, clinical applicability, and universality of the model were evaluated using receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), and internal validation.

RESULTS

NEU%, HDL-C, and MHR were identified as predictors of IVIG resistance by Lasso regression, with C-index of the Logistic model being 0.886 for the training set and 0.855 for the validation set. For predicting CAL development, sex, fever date before the first IVIG administration, KD type, and the level of HDL-C and MHR were the optimal variables, yielding C-index of 0.915 and 0.866 for the training and validation set, respectively. Calibration curves for both validation sets performed well, indicating strong predictive abilities of the models.

CONCLUSIONS

We established a nomogram for predicting IVIG resistance that incorporates NEU%, HDL-C, and MHR and a second nomogram for CAL complications incorporating sex, fever date, KD type, and the level of HDL-C and MHR in KD patients, based on the Lasso-Logistic regression model. These nomograms were of guiding significance for screening KD children at high risk of developing IVIG resistance and CAL complications, thereby improving prognosis. Key Points • Two nomograms were established to predict IVIG resistance and CAL complications in KD patients, based on the Lasso-Logistic regression model.

[Development of a predictive scoring model for non-response to intravenous immunoglobulin in Kawasaki disease]

OBJECTIVES

To explore the predictive factors for non-response to intravenous immunoglobulin (IVIG) in children with Kawasaki disease (KD) and to establish an IVIG non-response prediction scoring model for the Sichuan region.

METHODS

A retrospective study was conducted by collecting clinical data from children with KD admitted to four tertiary hospitals in Sichuan Province between 2019 and 2023. Among them, 940 children responded to IVIG, while 74 children did not respond. Multivariate logistic regression analysis was used to identify the predictive factors for non-response to IVIG and to establish a predictive scoring model. The model's effectiveness was assessed using the receiver operating characteristic curve (ROC) and validated with an independent dataset.

RESULTS

Multivariate logistic regression analysis showed that the platelet-to-lymphocyte ratio (PLR), hemoglobin (Hb), serum creatinine, aspartate aminotransferase (AST), and platelet count (PLT) were closely related to non-response to IVIG in children with KD (P<0.05). Based on these indicators, a predictive scoring model was established: PLR > 199, 0.4 points; Hb ≤ 116 g/L, 4 points; AST > 58 U/L, 0.2 points; serum creatinine > 38 µmol/L, 3.9 points; PLT count ≤ 275 × 109/L, 0.3 points. Using this model, children with KD were scored, and a total score greater than 4.3 was considered high risk of non-response to IVIG. The sensitivity of the model in predicting non-response to IVIG was 77.0%, specificity was 65.7%, and the area under the ROC curve was 0.746 (95%CI: 0.688-0.805).

CONCLUSIONS

The predictive scoring model based on PLR, Hb, serum creatinine, AST, and PLT demonstrates good predictive performance for non-response to IVIG in children with KD in the Sichuan region and can serve as a reference for clinical decision-making.

Nutrition-Associated Biomarkers in Predicting Intravenous Immunoglobulin Resistance and Coronary Artery Lesions in Kawasaki Disease: A Systematic Review and Meta-Analysis

Several studies explored the associations of pre-albumin (PA)/albumin (ALB) and ALB-combined indicators (prognostic nutrition index [PNI], albumin-to-globulin ratio [AGR], bilirubin-to-albumin [BAR], and C-reactive protein/albumin ratio [CAR]) with intravenous immunoglobulin (IVIG) resistance and coronary artery lesions (CALs) in Kawasaki disease (KD) patients. However, the results were controversial. A meta-analysis was conducted to reconfirm their associations and predictive performance. Databases of PubMed, EMBASE, and the Cochrane library were searched. The pooled standardized mean difference (SMD) or odds ratios (ORs) assessed the association, while the pooled area under the receiver operating characteristic curve (AUC) evaluated the predictive power. Ninety-four studies were included. Overall and subgroup meta-analyses demonstrated lower ALB and higher CAR were associated with IVIG resistance (ALB: SMD = -0.61; OR = 0.83; CAR: SMD = 1.47; OR = 1.69) and CALs (ALB: SMD = -0.56; OR = 0.92; CAR: SMD = 0.52). PNI was reduced in IVIG-resistant (SMD = -0.82) and coronary artery aneurysm (SMD = -0.18) patients in subgroup analysis and high PNI predicted the decreased risk of CALs in overall analysis (OR = 0.82). ALB, CAR, and PNI were a good or fair biomarker for differentiating IVIG-resistant (CALs) from IVIG-sensitive (non-CALs) patients (AUC > 0.6 or > 0.7). PA (SMD = -0.72) and BAR (SMD = 1.10) were differential in IVIG-resistant, but not in CAL patients compared with controls. AGR was not associated with CALs (p > 0.05). In conclusion, ALB, CAR, PNI, PA, and BAR may represent promising biomarkers for the prediction of IVIG resistance and CALs in KD patients.

Analysis and validation of clinical subgroups of Kawasaki disease in children in China: a retrospective study

OBJECTIVE

Although Kawasaki disease (KD) is commonly regarded as a single disease entity, clinical subgroups have recently been described. We aimed to validate previous research on clinical subgroups and establish a KD subgroup differentiation model specific to China.

METHODS

We analysed clinical data of 1682 patients diagnosed with KD at the Kunming Children's Hospital from December 2014 to December 2022. We performed principal component analysis and hierarchical clustering on 13 continuous variables. Then, we grouped the patients based on the optimal number of clusters and analysed the clinical characteristics of each subgroup.

RESULTS

We ultimately identified three subgroups. In cluster 1, younger patients predominantly exhibited the highest risk of coronary artery aneurysm and the lowest rate of intravenous immunoglobulin resistance. Cluster 2 was characterised by high inflammatory markers and a lowered risk of coronary artery aneurysm. Cluster 3 was characterised by liver involvement, with significant elevations in liver enzymes, gamma-glutamyl transferase and total bilirubin. We found a positive correlation between the ratio of the rising trend and intravenous immunoglobulin resistance. Cluster 1 and cluster 3 shared similarities with the previously identified younger age subgroup and liver subgroup, respectively, whereas cluster 2 was unique to our study.

CONCLUSIONS

Our study preliminarily validated a previous KD subgroup study and established a KD subgroup model in China.

Development of an immunoinflammatory indicator-related dynamic nomogram based on machine learning for the prediction of intravenous immunoglobulin-resistant Kawasaki disease patients

BACKGROUND

Approximately 10-20% of Kawasaki disease (KD) patients suffer from intravenous immunoglobulin (IVIG) resistance, placing them at higher risk of developing coronary artery aneurysms. Therefore, we aimed to construct an IVIG resistance prediction tool for children with KD in Shanghai, China.

METHODS

Retrospective analysis was conducted on data from 1271 patients diagnosed with KD and the patients were randomly divided into a training set and a validation set in a 2:1 ratio. Machine learning algorithms were employed to identify important predictors associated with IVIG resistance and to build a predictive model. The best-performing model was used to construct a dynamic nomogram. Moreover, receiver operating characteristic curves, calibration plots, and decision-curve analysis were utilized to measure the discriminatory power, accuracy, and clinical utility of the nomogram.

RESULTS

Six variables were identified as important predictors, including C-reactive protein, neutrophil ratio, procalcitonin, CD3 ratio, CD19 count, and IgM level. A dynamic nomogram constructed with these factors was available at https://hktk.shinyapps.io/dynnomapp/. The nomogram demonstrated good diagnostic performance in the training and validation sets (area under the receiver operating characteristic curve = 0.816 and 0.800, respectively). Moreover, the calibration curves and decision curves analysis indicated that the nomogram showed good consistency between predicted and actual outcomes and had good clinical benefits.

CONCLUSION

A web-based dynamic nomogram for IVIG resistance was constructed with good predictive performance, which can be used as a practical approach for early screening to assist physicians in personalizing the treatment of KD patients in Shanghai.

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

BACKGROUND

Intravenous immunoglobulin (IVIG) is the primary treatment for Kawasaki disease (KD). However, 10-20% of KD patients show no response to IVIG treatment, making the early prediction of IVIG resistance a key focus of KD research. Our aim is to explore the application of the C-reactive protein to albumin ratio (CAR) for predicting IVIG resistance in children with KD through meta-analysis.

METHODS

Cochrane Library, PubMed, MEDLINE, EMbase, CNKI, WanFang, the Chinese Biomedical Database, and CQVIP were searched up to November 2023 for cohort studies on predicting IVIG-resistant KD using the CAR. Articles were selected based on pre-established inclusion and exclusion criteria after extracting literature data and assessing them using the QUADAS-2.0 tool for evaluating the accuracy of diagnostic tests. Stata 15.0 software was used for meta-analysis.

RESULTS

Four Chinese and English literature reports were included in this meta-analysis. The results revealed the presence of a threshold effect and high heterogeneity among the included studies. The combined sensitivity for CAR predicting IVIG-resistant KD was calculated as 0.65 (95% CI 0.58-0.72), specificity as 0.71 (95% CI 0.57-0.81), and the area under the curve (AUC) as 0.70 (95% CI 0.66-0.74) using the random-effects model. The combined positive likelihood ratio was 2.22 (95% CI 1.35-3.65), the combined negative likelihood ratio was 0.49 (95% CI 0.35-0.69), and the diagnostic odds ratio was 5 (95% CI 2-10).

CONCLUSION

CAR is an auxiliary predictive indicator with moderate diagnostic value that provides guidance in the early treatment of the disease, demonstrating a certain predictive value that warrants further investigation. However, CAR cannot yet be considered as a definitive diagnostic or exclusionary marker for IVIG-resistant KD. Therefore, multi-center, large sample, and high-quality long-term follow-up trials are warranted to confirm the current findings.

[Predictive value of peripheral blood lymphocyte subsets for children with intravenous immunoglobulin-resistant Kawasaki disease]

OBJECTIVES

Based on peripheral blood lymphocyte subsets and common laboratory test indexes, this study aimed to construct a predictive scoring system for intravenous immunoglobulin (IVIG)-resistant Kawasaki disease (KD).

METHODS

Children hospitalized in Tianjin Children's Hospital from January 2021 to March 2023 were included in the study (185 cases of IVIG-sensitive KD and 41 cases of IVIG -resistant KD). Forty-six healthy children matched for age and gender were selected as controls. The relative percentage and absolute counts of peripheral lymphocyte subsets were measured by flow cytometry. Multivariate logistic regression was used to identify the predictive factors for IVIG-resistant KD and to construct a predictive scoring system for predicting IVIG-resistant KD.

RESULTS

The multivariate logistic regression analysis showed that CD4+ T cell absolute count, natural killer cell absolute count, serum sodium level, globulin level, and total bilirubin level were identified as predictive factors for IVIG-resistant KD (P<0.05). The predictive scoring system based on these factors achieved a sensitivity of 70.7% and a specificity of 83.8% in predicting IVIG-resistant KD.

CONCLUSIONS

Peripheral blood lymphocyte subsets can serve as predictive indicators for IVIG-resistant KD in children. The introduction of this indicator and the establishment of a scoring system based on it can provide a higher accuracy in predicting IVIG-resistant KD in children.

Bioinformatics analysis and identification of hub genes of neutrophils in Kawasaki disease: a pivotal study

BACKGROUND

Kawasaki disease (KD) is considered the main contributor to acquired heart diseases in developed countries. However, the precise pathogenesis of KD remains unclear. Neutrophils play roles in KD. This study aimed to select hub genes in neutrophils in acute KD.

METHODS

mRNA microarray of neutrophils from four acute KD patients and three healthy controls was performed to screen differentially expressed mRNAs (DE-mRNAs). DE-mRNAs were analyzed and predicted by Gene Ontology (GO), Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathways, and protein-protein interaction networks. Real time-PCR was finally conducted to confirm the reliability and validity of the expression level of DE-mRNAs from blood samples of healthy controls and KD patients in both acute and convalescent stage.

RESULTS

A total of 1950 DE-mRNAs including 1287 upregulated and 663 downregulated mRNAs were identified. GO and KEGG analyses revealed the DE-mRNAs were mainly enriched in the regulation of transcription from RNA polymerase II promoter, apoptotic process, intracellular signal transduction, protein phosphorylation, protein transport, metabolic pathways, carbon metabolism, lysosome, apoptosis, pyrimidine metabolism, alzheimer disease, prion disease, sphingolipid metabolism, huntington disease, glucagon signaling pathway, non-alcoholic fatty liver disease, pyruvate metabolism, sphingolipid signaling pathway, and peroxisome. Twenty hub DE-mRNAs were selected including GAPDH, GNB2L1, PTPRC, GART, HIST2H2AC, ACTG1, H2AFX, CREB1, ATP5A1, ENO1, RAC2, PKM, BCL2L1, ATP5B, MRPL13, SDHA, TLR4, RUVBL2, TXNRD1, and ITGAM. The real-time PCR results showed that BCL2L1 and ITGAM mRNA were upregulated in acute KD and were normalized in the convalescent stage.

CONCLUSIONS

These findings may improve our understanding of neutrophils in KD. Key Points • Neutrophilic BCL2L1 and ITGAM mRNA were first reported to be correlated with the pathogenic mechanism of KD.

Risk-prediction models for intravenous immunoglobulin resistance in Kawasaki disease: Risk-of-Bias Assessment using PROBAST

BACKGROUND

The prediction model of intravenous immunoglobulin (IVIG) resistance in Kawasaki disease can calculate the probability of IVIG resistance and provide a basis for clinical decision-making. We aim to assess the quality of these models developed in the children with Kawasaki disease.

METHODS

Studies of prediction models for IVIG-resistant Kawasaki disease were identified through searches in the PubMed, Web of Science, and Embase databases. Two investigators independently performed literature screening, data extraction, quality evaluation, and discrepancies were settled by a statistician. The checklist for critical appraisal and data extraction for systematic reviews of prediction modeling studies (CHARMS) was used for data extraction, and the prediction models were evaluated using the Prediction Model Risk of Bias Assessment Tool (PROBAST).

RESULTS

Seventeen studies meeting the selection criteria were included in the qualitative analysis. The top three predictors were neutrophil measurements (peripheral neutrophil count and neutrophil %), serum albumin level, and C-reactive protein (CRP) level. The reported area under the curve (AUC) values for the developed models ranged from 0.672 (95% confidence interval [CI]: 0.631-0.712) to 0.891 (95% CI: 0.837-0.945); The studies showed a high risk of bias (ROB) for modeling techniques, yielding a high overall ROB.

CONCLUSION

IVIG resistance models for Kawasaki disease showed high ROB. An emphasis on improving their quality can provide high-quality evidence for clinical practice.

IMPACT STATEMENT

This study systematically evaluated the risk of bias (ROB) of existing prediction models for intravenous immunoglobulin (IVIG) resistance in Kawasaki disease to provide guidance for future model development meeting clinical expectations. This is the first study to systematically evaluate the ROB of IVIG resistance in Kawasaki disease by using PROBAST. ROB may reduce model performance in different populations. Future prediction models should account for this problem, and PROBAST can help improve the methodological quality and applicability of prediction model development.

A novel model for predicting intravenous immunoglobulin-resistance in Kawasaki disease: a large cohort study

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.

Risk Factors for Coronary Artery Aneurysm in a Chinese Pediatric Population with Kawasaki Disease at Low Risk of Intravenous Immunoglobulin Resistance: A Retrospective Cohort Study

INTRODUCTION

Multiple scoring systems for predicting intravenous immunoglobulin (IVIG) resistance have been developed. Although low-scoring patients with Kawasaki disease (KD) have a favorable prognosis, many develop coronary artery aneurysms (CAAs). Herein, we determined the risk factors for CAA development among patients with KD with low risk of IVIG resistance.

METHODS

We compared 14 scoring systems for predicting IVIG resistance among patients with KD hospitalized from 2003 to 2022. Patients were risk stratified using an optimal scoring system. Association between baseline characteristics and CAA development was assessed within the low-risk group.

RESULTS

Overall, 664 pediatric patients with KD were included; 108 (16.3%) had IVIG resistance, and the Liping scoring system had the highest area under the curve (0.714). According to this system, 444 (66.9%) patients with KD were classified as having low risk of developing IVIG resistance (<5 points). CAA development was significantly associated with male sex (odds ratio [OR], 1.946; 95% CI: 1.015-3.730), age <6 months at fever onset (OR, 3.142; 95% CI: 1.028-9.608), and a baseline maximum Z score of ≥2.72 (OR, 3.451; 95% CI: 2.582-4.612). CAA incidence increased with the number of risk factors, and comparisons with a Kobayashi score of <5 points among patients with KD revealed similar results.

CONCLUSIONS

Predicting the response to IVIG might help further reduce CAA development in patients with KD.

Plasma interleukin-41 serves as a potential diagnostic biomarker for Kawasaki disease

INTRODUCTION

Kawasaki disease (KD) is a systemic vasculitis that causes abnormalities in the coronary arteries. Interleukin (IL)-41 is a novel immunoregulatory cytokine involved in the pathogenesis of some inflammatory and immune-related diseases. However, the role of IL-41 in KD is unclear. The purpose of this study was to detect the expression of IL-41 in the plasma of children with KD and its relationship with the disease.

METHODS

A total of 44 children with KD and 37 healthy controls (HC) were recruited for this study. Plasma concentrations of IL-41 were determined by ELISA. Correlations between plasma IL-41 levels and KD-related clinical parameters were analyzed by Pearson correlation and multivariate linear regression analysis. Receiver operating characteristic curve analysis was used to assess the clinical value of IL-41 in the diagnosis of KD.

RESULTS

Our results showed that plasma IL-41 levels were significantly elevated in children with KD compared with HC. Correlation analysis demonstrated that IL-41 levels were positively correlated with D-dimer and N-terminal pro-B-type natriuretic peptide, and negatively correlated with IgM, mean corpuscular hemoglobin concentration, total protein, albumin and pre-albumin. Multivariable linear regression analysis revealed that IgM and mean corpuscular hemoglobin concentrations were associated with IL-41. Receiver operating characteristic curve analysis showed that the area under the curve of IL-41 was 0.7101, with IL-41 providing 88.64 % sensitivity and 54.05 % specificity.

CONCLUSION

Our study indicated that plasma IL-41 levels in children with KD were significantly higher than those in HC, and may provide a potential diagnostic biomarker for KD.

[Expression of interleukin-17A in serum of children with intravenous immunoglobulin-resistant Kawasaki disease and its clinical significance]

OBJECTIVES

To study the expression of interleukin-17A (IL-17A) in the serum of children with intravenous immunoglobulin (IVIG)-resistant Kawasaki disease (KD) and its clinical significance.

METHODS

A total of 143 children with KD who were hospitalized in Wuhan Children's Hospital, Tongji Medical College, Huazhong University of Science and Technology, from June 2021 to June 2022 were enrolled in this prospective study, among whom 115 had IVIG-sensitive KD and 28 had IVIG-resistant KD. After matching for sex and age, 110 children with acute respiratory infectious diseases (fever time ≥5 days but without KD) were enrolled as the control group. The enzyme-linked immunosorbent assay was used to measure the serum level of IL-17A. The levels of white blood cell count (WBC), neutrophil count (NE), platelet count, erythrocyte sedimentation rate, and C-reactive protein (CRP) were measured. The receiver operating characteristic curve was plotted to analyze the value of WBC, NE, CRP, and IL-17A in the prediction of IVIG-resistant KD. The multivariate logistic regression analysis was used to evaluate the predictive factors for resistance to IVIG in children with KD.

RESULTS

Before IVIG treatment, the KD group had a significantly higher serum level of IL-17A than the control group (P<0.05), and the children with IVIG-resistant KD had a significantly higher serum level of IL-17A than those with IVIG-sensitive KD (P<0.05). The receiver operating characteristic curve analysis showed that WBC, NE, CRP, and IL-17A had an area under the curve of 0.718, 0.741, 0.627, and 0.840, respectively, in the prediction of IVIG-resistant KD. With serum IL-17A ≥44.06 pg/mL as the cut-off value, IL-17A had a sensitivity of 84% and a specificity of 81% in the prediction of IVIG-resistant KD. The multivariate logistic regression analysis showed that a high serum level of IL-17A was a predictive factor for resistance to IVIG in children with KD (OR=1.161, P=0.001).

CONCLUSIONS

Serum IL-17A levels are elevated in children with IVIG-resistant KD, and serum IL-17A level (≥44.06 pg/mL) may have a predictive value for resistance to IVIG in children with KD.

Predicting immunoglobulin resistance in Kawasaki disease: an assessment of neutrophil to lymphocyte platelet ratio

BACKGROUND

Kawasaki disease (KD) is an acute febrile illness of unknown etiology and predictors for intravenous immunoglobulin (IVIG) resistance have been widely explored in recent decades. Neutrophil to lymphocyte platelet ratio (NLPR) was reported to be associated with the outcomes in many diseases. However, its relationship with IVIG resistance has not be explored.

METHODS

The medical data of patients diagnosed with KD in Children's Hospital of Soochow University between January 2019 and December 2020 were retrospectively reviewed and analyzed. Patients were trisected into three groups based on NLPR. Logistics regression was used to analyze the association between NLPR and IVIG resistance. Restricted cubic spine was used to exhibit the relationship. Sensitivity analysis and subgroup analysis were also carried out.

RESULTS

A total of 803 patients were included in the present study (61.8% males; median age: 24 months). IVIG resistance occurred in 74 (9.2%) patients. Multivariable-adjusted analyses revealed higher NLPR (odds ratio [95% confidence interval]: 1.12 [1.00-1.24]) was an independent predictor of IVIG resistance, which was strengthened by sensitivity analyses. The association of NLPR and IVIG resistance was not modified by age, sex, CALs, or days of IVIG initiation ≤ 4.

CONCLUSION

NLPR may be a valuable prognostic marker in KD patients with IVIG resistance.

Ultrasound evaluation of endothelial dysfunction in immunoglobulin-resistant children with acute Kawasaki disease

INTRODUCTION

Given the evidence that brachial artery flow-mediated dilation (FMD) is declined in children later after the onset of Kawasaki disease (KD), we hypothesized that indicators that detect the situation of the endothelium are useful parameters that can accurately reflect subclinical dysfunction in resistant patients and assist in differentiating patients with KD at a higher risk of IVIG resistance, which may be valuable in better understanding how to protect patients from endothelial and thrombotic complications.

METHODS

Fifty IVIG-resistant KD children, 120 IVIG-responsive KD children, 35 febrile children with acute upper respiratory infection, and 50 healthy controls were recruited, and indicators reflecting endothelial inflammation, including flow-mediated dilation (FMD), were measured. Receiver operating characteristic (ROC) curve analysis was utilized to determine the threshold values of these indicators of IVIG resistance. Multiple logistic regression analysis was performed to determine whether FMD was an independent predictor of IVIG-resistant patients.

RESULTS

In comparison with the lab data, PCT, Na + , and FMD exhibited AUCs of 0.727, 0.653, and 0.698 (P < 0.05), respectively, in predicting IVIG resistance in KD through ROC analysis. PCT > 1.69 ng/ml, Na +  < 133.2 mmol/l, and FMD < 5.79% were independent predictors of IVIG resistance in KD (OR 4.257, 3.516, 3.563, 95% CI 1.549 ~ 11.700, 1.277 ~ 9.680, 1.299 ~ 9.772, P < 0.05).

CONCLUSION

More severe endothelial dysfunction, especially lower FMD, was present in IVIG-resistant patients than in IVIG-responsive patients. It is a helpful diagnostic tool that provides supportive criteria to detect KD patients at a higher risk of IVIG resistance when FMD < 5.79% in children. Key Points • IVIG-resistant KD patients have more severe endothelial dysfunction than IVIG-sensitive patients. • FMD < 5.79% may indicate an increased risk of IVIG resistance in children with Kawasaki disease.

Predicting Intravenous Immunoglobulin Resistance Among North American Children Hospitalized With Kawasaki Disease

OBJECTIVE

The Kobayashi score (KS) is the most widely used tool for predicting intravenous immunoglobulin (IVIG) resistance in Kawasaki disease (KD). The KS has shown good sensitivity (86%) and specificity (68%) in Japanese children; however, its use is limited outside of Japan. No models accurately predict IVIG resistance of children with KD in the United States. We sought to develop and test a novel scoring system to predict IVIG resistance in hospitalized children with KD.

METHODS

A retrospective chart review was conducted of all children diagnosed with KD from January 2000 to December 2015. Subjects were divided into 2 groups: IVIG susceptible or resistant. Variables that differed between the groups were identified and used to create a "new score" to predict resistance to IVIG. The new score was then compared with the KS and performance characteristics were determined.

RESULTS

A total of 208 subjects were reviewed. White blood cell count, neutrophil percentage, age, and serum albumin were used in the new score with equal weighting. Overall, the new score achieved improved sensitivity (54% vs 26%) and similar specificity (69% vs 74%) compared with the KS in predicting IVIG resistance in hospitalized children diagnosed with KD.

CONCLUSIONS

Predicting IVIG resistance in children diagnosed with KD remains challenging. The KS has low sensitivity in predicting IVIG resistance in children with KD in the United States. The new score resulted in improved sensitivity, but many children with true IVIG resistance may be missed. Further research is needed to improve IVIG resistance prediction.

A decision tree model for predicting intravenous immunoglobulin resistance and coronary artery involvement in Kawasaki disease

Objectives

This study aims to develop a new algorithm for predicting intravenous immunoglobulin (IVIG) resistance and coronary artery involvement in Kawasaki disease (KD) through decision tree models.

Methods

Medical records of children hospitalized for KD were analysed retrospectively. We compared the clinical characteristics, and the laboratory data in the groups with IVIG resistance and coronary artery dilatations (CADs) in KD patients. The decision tree models were developed to predict IVIG resistance and CADs.

Results

A total 896 patients (511 males and 385 females; 1 month-12 years) were eligible. IVIG resistance was identified in 111 (12.3%) patients, and CADs were found in 156 (17.4%). Total bilirubin and nitrogen terminal- pro-brain natriuretic peptide (NT-proBNP) were significantly higher in IVIG resistant group than in IVIG responsive group (0.62 ± 0.8 mg/dL vs 1.38 ± 1.4 mg/dL and 1231 ± 2136 pg/mL vs 2425 ± 4459 mL, respectively, P < 0.01). Also, CADs were more developed in the resistant group (39/111; 14.9% vs. 117/785; 35.1%, P < 0.01). The decision tree for predicting IVIG resistance was classified based on total bilirubin (0.7 mg/mL, 1.46 mg/dL) and NT-proBNP (1561 pg/mL), consisting of two layers and four nodes, with 86.2% training accuracy and 90.5% evaluation accuracy. The Receiver Operating Characteristic (ROC) evaluated the predictive ability of the decision tree, and the area under the curve (AUC) (0.834; 95% confidence interval, 0.675–0.973; P < 0.05) showed relatively higher accuracy. The group with CADs had significantly higher total bilirubin and NT-proBNP levels than the control group (0.64 ± 0.82 mg/dL vs 1.04 ± 1.14 mg/dL and 1192 ± 2049 pg/mL vs 2268 ± 4136 pg/mL, respectively, P < 0.01). The decision trees for predicting CADs were classified into two nodes based on NT-proBNP (789 pg/mL) alone, with 83.5% training accuracy and 90.3% evaluation accuracy.

Conclusion

A new algorithm decision tree model presents for predicting IVIG resistance and CADs in KD, confirming the usefulness of NT-proBNP as a predictor of KD.

Risk Factors for Resistance to Intravenous Immunoglobulin Treatment and Coronary Artery Abnormalities in a Chinese Pediatric Population With Kawasaki Disease: A Retrospective Cohort Study

Background

The factors predicting high-risk Kawasaki disease (KD) remain unclear. Therefore, we aimed to determine the risk factors for resistance to intravenous immunoglobulin (IVIG) treatment and coronary artery aneurysm (CAA) development in a Chinese pediatric population with high-risk KD.

Methods

We compared the performances of 11 scoring systems that have been reported to predict IVIG resistance among patients with KD hospitalized from January 2013 through August 2021. Patients were risk-stratified based on the optimal scoring system. The association of baseline characteristics with IVIG treatment resistance and CAA development was investigated within the high-risk group of KD.

Results

In total, 346 pediatric patients with KD were included, of whom 63 (18.2%) presented with IVIG resistance. The Kobayashi score and five Chinese scoring system scores (Tang et al., Yang et al., Lan et al., Liping et al., and Wu et al.) were significantly higher in the IVIG non-responsive KD group than in the IVIG responsive KD group, and the results of the receiver operating characteristic (ROC) curves analysis were observed to be highest in the Xie Liping scoring system for IVIG resistance (area under the curve, 0.650). Especially, 87 (25.1%) patients comprised the high-risk KD group based on this optimal scoring system (≥5 points). IVIG resistance was significantly associated with the total bilirubin-to-albumin ratio (B/A ratio) [odds ratio, 7.427; 95% confidence interval (CI): 1.022-53.951]. The area under the ROC was 0.703 (95% CI: 0.586-0.821), and the cutoff point was 0.383, which indicated a sensitivity and specificity for predicting treatment resistance of 58% and 80%, respectively. The serum albumin level (odds ratio, 1.401; 95% CI: 1.049-1.869) and Z score of the left main coronary artery (odds ratio, 9.023; 95% CI: 1.070-76.112) were independent predictors of CAA development.

Conclusions

In the Chinese pediatric population with KD, the Xie Liping scoring system is the most appropriate method for identifying high-risk patients, and IVIG resistance could be predicted based on the B/A ratio. Serum albumin level and Z score of the left main coronary artery at baseline were warning indicators for CAA development. More intensified or adjunctive therapies and close follow-up should be considered for high-risk patients with these risk factors.

Comparison of IVIG resistance predictive models in Kawasaki disease

BACKGROUND

We aimed to compare the ten different scores (by Kobayashi, Egami, Harada, Formosa, Sano, Piram et al., Wu et al., Yang et al., Tan et al., and Kanai et al.) to assess their performance in predicting IVIG resistance in Turkish children.

METHODS

Complete and incomplete KD patients diagnosed with KD at Hacettepe University between June 2007 and September 2019 were evaluated retrospectively.

RESULTS

A total of 129 patients, 79 boys (61.2%), with a median age 36 (IQR 19.5-57.0) months were evaluated. Sixteen patients (12.4%) had IVIG resistance. Sensitivity was low for all the ten scores. Tan, Sano, and Egami predictive models had the highest specificity (97.3, 89.4, 86.7%, respectively). Almost all scoring systems distinguished the group of patients with low risk for IVIG resistance but could not differentiate IVIG-resistant patients. Multivariate analysis for the laboratory features showed that platelet count <300 × 10⁹/L and GGT serum levels were independent risk factors for IVIG resistance (OR: 3.896; 95% CI: 1.054-14.404; p = 0.042 and OR: 1.008; 95% CI: 1.001-1.015; p = 0.050).

CONCLUSIONS

The current scoring systems had a low sensitivity for predicting the risk for IVIG resistance in Turkish children. On the other hand, increased serum GGT levels and low platelet count were risk factors for predicting IVIG resistance.

IMPACT

Intravenous immunoglobulin (IVIG) resistance may be observed in 10-20% of patients diagnosed with Kawasaki disease. Coronary artery involvement is more frequent in IVIG-resistant patients. It is important to predict the patients who might develop IVIG resistance to improve prognosis. The performance of the IVIG resistance predictive models in Kawasaki disease in our population is limited due to the low sensitivity.

Anti-inflammatory Treatment of Kawasaki Disease: Comparison of Current Guidelines and Perspectives

Kawasaki disease (KD), an acute, generalized vasculitis, is associated with an increased risk of coronary heart disease and is the most common cause of acquired heart disease in childhood. The incidence of KD is increasing worldwide. There are numerous international treatment guidelines. Our study aims to perform the first one so far comparison of them. While the gold standard therapy remains still the same (intravenous immunoglobulins and aspirin), there is currently a lack of evidence for choosing optimal treatment for high-risk patients and refractory KD. In this review, we also discuss the treatment of complications of KD and Kawasaki-like phenotypes, present an anti-inflammatory treatment in the light of new scientific data, and present novel potential therapeutic targets for KD.

Prognostic value of pretreatment prognostic nutritional index in intravenous immunoglobulin-resistant Kawasaki disease

The aim of the present study was to investigate the potential predictive significance of pretreatment prognostic nutritional index (PNI) in intravenous immunoglobulin (IVIG) resistant Kawasaki disease (KD). The PNI, neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) were analyzed in 1257 eligible patients with KD. Receiver operating curve analysis was used to explore the prediction accuracy for IVIG-resistant KD. The optimal cut-off values were identified as 49.5 for PNI, 3.58 for NLR and 164.00 for PLR, respectively. Lower pretreatment PNI (< 49.5) was demonstrated to be associated with lower age, serum sodium levels and platelet counts, and with a higher incidence of IVIG resistance and higher C-reactive protein levels. There was a significantly negative association between the PNI and NLR, and PLR. Univariate and multivariate analyses revealed that PNI, NLR and PLR were independent predictive factors for IVIG resistance. The discriminatory ability of PNI was not inferior to NLR, PLR and their combination (NLR > 3.58 and PLR > 164) for predicting IVIG resistance, respectively. Pretreatment PNI may serve as a novel surrogate independent predictor for IVIG-resistant KD.