Treatment of immunoglobulin-resistant kawasaki disease: a Bayesian network meta-analysis of different regimens

Pan, Yan; Fan, Qihong; Hu, Lifen

doi:10.3389/fped.2023.1149519

Cited by 4 publications

(4 citation statements)

References 28 publications

(49 reference statements)

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“…Prevention of CAL is a significant step in the treatment of KS. The standard therapy for KS is effective in reducing the incidence of CAL significantly [ 24 ]. However, even with timely initiation of IVIG treatment, coronary artery dilatation might occur in 30% of children, and 5–10% of children might eventually develop permanent coronary artery disease [ 25 ].…”

Section: Discussionmentioning

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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Section: Discussionmentioning

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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“…Other options include intravenous infliximab or intravenous methylprednisolone pulse therapy. Methotrexate, cyclophosphamide, cyclosporine A, plasmapheresis and plasma exchange are considered third-line treatments for KD patients with initial IVIG-resistance [30].…”

Section: Kawasaki Disease (Kd)mentioning

confidence: 99%

“…The disorder is multisystemic with mucocutaneous, gastrointestinal, respiratory cardiovascular (including coronary-artery aneurysms), central nervous system, and hematologic symptoms. MIS-C is characterized by SARS-CoV-2 antigenemia, unchecked neutrophil activation, and the release of extracellular traps in blood vessels [30]. It is a life-threatening post-COVID-19 disease with a reported mortality rate of 1.9 % [31].…”

Section: Covid-19 Associated Multisystem Inflammatory Syndrome In Chi...mentioning

confidence: 99%

Pediatric dermatological vital emergencies

Chiriac,

Diaconeasa,

Miulescu

et al. 2024

Aktuelle Dermatologie

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Pediatric patients in the emergency unit often present with muco-cutaneous symptoms. Most muco-cutaneous findings are not life-threatening, but it is crucial to identify those dermatoses with urgent need of treatment. In this review, we present infectious and non-infectious pediatric disorders with muco-cutaneous red-flag signs for a potential severe course and complications associated with significant mortality. By recognizing these dermatological symptoms, early confirmation of diagnosis and initiation of appropriate treatment outcome can be optimized.

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“…Identifying high-risk patients who may benefit from more aggressive treatment is important. Administering a second dose of IVIG (2 g/kg over 10–12 h, following the same dosage and treatment duration as the initial IVIG) is a consideration [ 65 , 66 ] methylprednisolone pulse therapy [ 67 ] tumor necrosis factor-alpha blockade [ 68 ] cyclophosphamide; cyclosporine A; plasmapheresis [ 69 ] methotrexate [ 70 ] and plasma exchange [ 71 ] have all been reported to be beneficial for KD patients with initial IVIG-resistance. IVIG is recognized as the primary standard treatment for KD in accordance with AHA and Japanese guidelines.…”

Section: Ivig Resistance (Ivig Non-responsiveness or Ivig Failure) In...mentioning

confidence: 99%

Diagnosis, Progress, and Treatment Update of Kawasaki Disease

Kuo

2023

IJMS

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Kawasaki disease (KD) is an acute inflammatory disorder that primarily affects children and can lead to coronary artery lesions (CAL) if not diagnosed and treated promptly. The original clinical criteria for diagnosing KD were reported by Dr. Tomisaku Kawasaki in 1967 and have been used for decades. However, research since then has highlighted the limitations of relying solely on these criteria, as they might lead to underdiagnosis or delayed diagnosis, potentially increasing the risk of coronary artery complications. This review appears to discuss several important aspects related to KD diagnosis and management. The current diagnostic methods for KD might need updates, especially considering cases that do not fit the typical clinical criteria. Recognizing diagnostic pitfalls and distinguishing KD from other conditions that might have similar clinical presentations is essential. The differences and similarities between KD and Multisystem Inflammatory Syndrome in Children (MIS-C), another inflammatory condition that has been associated with COVID-19, were also reviewed. The review explores the potential role of eosinophil count, new biomarkers, microRNA panels, and scoring systems in aiding the diagnosis of KD. Overall, the review article provides a comprehensive overview of the evolving landscape of KD diagnosis and management, incorporating new diagnostic methods, biomarkers, and treatment approaches to improve patient outcomes and reduce the risk of complications.

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Treatment of immunoglobulin-resistant kawasaki disease: a Bayesian network meta-analysis of different regimens

Cited by 4 publications

References 28 publications

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

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

Pediatric dermatological vital emergencies

Diagnosis, Progress, and Treatment Update of Kawasaki Disease

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