An early predictive model for Kawasaki disease shock syndrome in children in central China

Abstract

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IntroductionThis study aims to analyze the clinical features of Kawasaki disease (KD) shock syndrome (KDSS) and explore its early predictors.MethodsA retrospective case–control study was used to analyze KD cases from February 2016 to October 2023 in our hospital. A total of 28 children with KDSS and 307 children who did not develop KDSS were included according to matching factors. Baseline information, clinical manifestations, and laboratory indicators were compared between the two groups. Indicators of differences were analyzed based on univariate analysis; binary logistic regression analysis was used to identify the risk factors for KDSS, and then receiver operating characteristic analysis was performed to establish a predictive score model for KDSS.ResultsElevated neutrophil-to-lymphocyte ratio(NLR) and decreased fibrinogen (FIB) and Na were independent risk factors for KDSS; the scoring of the above risk factors according to the odds ratio value eventually led to the establishment of a new scoring system: NLR ≥ 7.99 (6 points), FIB ≤ 5.415 g/L (1 point), Na ≤ 133.05 mmol/L (3 points), and a total score of ≥3.5 points were high-risk factors for progression to KDSS; otherwise, they were considered to be low-risk factors.ConclusionChildren with KD with NLR ≥ 7.99, FIB ≤ 5.415 g/L, and Na ≤ 133.05 mmol/L, and those with two or more of the above risk factors, are more likely to progress to KDSS, which helps in early clinical diagnosis and treatment.

Keywords

• Kawasaki disease
• Kawasaki disease shock syndrome
• predictive scoring model
• NLR
• fibrinogen
• serum sodium