Diagnosis, Progress, and Treatment Update of Kawasaki Disease

Kuo, Ho-Chang

doi:10.3390/ijms241813948

Cited by 13 publications

(4 citation statements)

References 77 publications

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“…Numerous studies examining eosinophils' role in KD suggest that elevated eosinophil counts may induce allergic diseases, thus contributing to CAD. Kuo et al reported in their study that the eosinophil count is an important factor in distinguishing KD from other febrile diseases [41]. In a study reported in 2023, eosinophils have been found to possess a relative predictive value for coronary artery dilation.…”

Section: Discussionmentioning

confidence: 97%

Comparison of Eosinophil Counts in Inflammatory Conditions: Multisystem Inflammatory Syndrome in Children, Kawasaki Disease, and Infectious Mononucleosis

Sarı,

Erdede

2024

Children

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This study examined the distinctions between multisystem inflammatory syndrome associated with coronavirus disease 2019, Kawasaki disease, and infectious mononucleosis. These three inflammatory disorders have commonalities according to clinical and laboratory results, particularly in relation to eosinophil levels. In this retrospective, single-center study, we documented the examination records (acute phase reactants and complete blood count) and clinical and cardiological findings of 130 patients diagnosed with multisystem inflammatory syndrome, Kawasaki disease, and infectious mononucleosis. These patients were treated and received follow-up care in our hospital from March 12, 2020, to September 13, 2022, as per the hospital records. Statistical analyses were performed using NCSS 2007, version 1 software. Eosinopenia was more prevalent in children with multisystem inflammatory syndrome than in those with Kawasaki disease, who showed normal or elevated eosinophil counts. The eosinophil counts in patients with infectious mononucleosis typically fell within the normal range. Our study found no correlation between the eosinophil counts and cardiac involvement in pediatric patients with either condition. These findings indicate a higher prevalence of eosinopenia in patients with multisystem inflammatory syndrome, irrespective of cardiac involvement, than in those with Kawasaki disease. Despite similarities in clinical findings, Kawasaki disease and multisystem inflammatory syndrome in children necessitate further studies for distinct characteristic elucidation.

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Section: Discussionmentioning

confidence: 97%

Comparison of Eosinophil Counts in Inflammatory Conditions: Multisystem Inflammatory Syndrome in Children, Kawasaki Disease, and Infectious Mononucleosis

Sarı,

Erdede

2024

Children

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“…The most serious complication of KD is coronary artery damage, which is also an important risk factor for ischemic heart attack in adulthood ( 28 ). The coronary artery is a common invasive site of KD, that can cause destruction, dilatation, rupture, stenosis, and even embolism of the vascular wall ( 29 ).…”

Section: Discussionmentioning

confidence: 99%

Ubiquitin ligase MDM2 mediates endothelial inflammation in Kawasaki disease vasculitis development

Xu,

Qian,

Zhu

et al. 2024

Transl Pediatr

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Background Kawasaki disease (KD) often complicates coronary artery lesions (CALs). Despite the established significance of STAT3 signaling during the acute phase of KD and signal transducer and activator of transcription 3 (STAT3) signaling being closely related to CALs, it remains unknown whether and how STAT3 was regulated by ubiquitination during KD pathogenesis. Methods Bioinformatics and immunoprecipitation assays were conducted, and an E3 ligase, murine double minute 2 (MDM2) was identified as the ubiquitin ligase of STAT3. The blood samples from KD patients before and after intravenous immunoglobulin (IVIG) treatment were utilized to analyze the expression level of MDM2. Human coronary artery endothelial cells (HCAECs) and a mouse model were used to study the mechanisms of MDM2-STAT3 signaling during KD pathogenesis. Results The MDM2 expression level decreased while the STAT3 level and vascular endothelial growth factor A (VEGFA) level increased in KD patients with CALs and the KD mouse model. Mechanistically, MDM2 colocalized with STAT3 in HCAECs and the coronary vessels of the KD mouse model. Knocking down MDM2 caused an increased level of STAT3 protein in HCAECs, whereas MDM2 overexpression upregulated the ubiquitination level of STAT3 protein, hence leading to significantly decreased turnover of STAT3 and VEGFA. Conclusions MDM2 functions as a negative regulator of STAT3 signaling by promoting its ubiquitination during KD pathogenesis, thus providing a potential intervention target for KD therapy.

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“…The latest national survey conducted by the Japan Circulation Society (JCS) shows that 7% of children with KS present vascular complications in the acute phase, and 2.3% develop cardiovascular sequelae after discharge [ 7 ]. About 20-25% of untreated cases will develop into severe CAL, which makes KS the most common cause of pediatric acquired heart disease in developed countries [ 8 ]. Therefore, it is necessary to carry out CAL risk prediction stratification for early diagnosis and intensive care.…”

Section: Introductionmentioning

confidence: 99%

Prediction of coronary artery lesions in children with Kawasaki syndrome based on machine learning

Tang,

Liu,

et al. 2024

BMC Pediatr

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Objective Kawasaki syndrome (KS) is an acute vasculitis that affects children < 5 years of age and leads to coronary artery lesions (CAL) in about 20-25% of untreated cases. Machine learning (ML) is a branch of artificial intelligence (AI) that integrates complex data sets on a large scale and uses huge data to predict future events. The purpose of the present study was to use ML to present the model for early risk assessment of CAL in children with KS by different algorithms. Methods A total of 158 children were enrolled from Women and Children’s Hospital, Qingdao University, and divided into 70–30% as the training sets and the test sets for modeling and validation studies. There are several classifiers are constructed for models including the random forest (RF), the logistic regression (LR), and the eXtreme Gradient Boosting (XGBoost). Data preprocessing is analyzed before applying the classifiers to modeling. To avoid the problem of overfitting, the 5-fold cross validation method was used throughout all the data. Results The area under the curve (AUC) of the RF model was 0.925 according to the validation of the test set. The average accuracy was 0.930 (95% CI, 0.905 to 0.956). The AUC of the LG model was 0.888 and the average accuracy was 0.893 (95% CI, 0,837 to 0.950). The AUC of the XGBoost model was 0.879 and the average accuracy was 0.935 (95% CI, 0.891 to 0.980). Conclusion The RF algorithm was used in the present study to construct a prediction model for CAL effectively, with an accuracy of 0.930 and AUC of 0.925. The novel model established by ML may help guide clinicians in the initial decision to make a more aggressive initial anti-inflammatory therapy. Due to the limitations of external validation and regional population characteristics, additional research is required to initiate a further application in the clinic.

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Diagnosis, Progress, and Treatment Update of Kawasaki Disease

Cited by 13 publications

References 77 publications

Comparison of Eosinophil Counts in Inflammatory Conditions: Multisystem Inflammatory Syndrome in Children, Kawasaki Disease, and Infectious Mononucleosis

Comparison of Eosinophil Counts in Inflammatory Conditions: Multisystem Inflammatory Syndrome in Children, Kawasaki Disease, and Infectious Mononucleosis

Ubiquitin ligase MDM2 mediates endothelial inflammation in Kawasaki disease vasculitis development

Prediction of coronary artery lesions in children with Kawasaki syndrome based on machine learning

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