Predictive model based on gene and laboratory data for intravenous immunoglobulin resistance in Kawasaki disease in a Chinese population.

ABSTRACT:

Background

Here, we investigated the predictive efficiency of a newly developed model based on single nucleotide polymorphisms (SNPs) and laboratory data for intravenous immunoglobulin (IVIG) resistance in Kawasaki disease (KD) in a Chinese population.

Methods

Data relating to children with KD were acquired from a single center between December 2015 and August 2019 and used to screen target SNPs. We then developed a predictive model of IVIG resistance using previous laboratory parameters. We then validated our model using data acquired from children with KD attending a second center between January and December 2019.

Results

Analysis showed that rs10056474 GG, rs746994GG, rs76863441GT, rs16944 (CT/TT), and rs1143627 (CT/CC), increased the risk of IVIG-resistance in KD

SUBMITTER: Meng L 

PROVIDER: S-EPMC8236184 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature