English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Intravenous immunoglobulin (IVIG) resistance is an independent risk factor for the development of coronary artery lesions (CAL) in patients with Kawasaki disease (KD). Accurate identification of IVIG-resistant patients is one of the biggest clinical challenges in the treatment of KD. In this review article, we will go over current IVIG resistance scoring systems and other biological markers of IVIG resistance, with a particular focus on advances in machine-based learning techniques and high-throughput omics data. Traditional scoring models, which were developed using logistic regression, including the Kobayashi score and Egami score, are inadequate at identifying IVIG resistance in non-Japanese populations. Newer machine-learning methods and high-throughput technologies including transcriptomic and epigenetic arrays have identified several potential targets for IVIG resistance including gene expression of the Fc receptor, and components of the interleukin (IL)-1β and pyroptosis pathways. As we enter an age where access to big data has become more commonplace, interpretation of large data sets that are able take into account complexities in patient populations will hopefully usher in a new era of precision medicine, which will enable us to identify and treat KD patients with IVIG resistance with increased accuracy.

The state of play in tools for predicting immunoglobulin resistance in Kawasaki disease