Risk factors for cardiac damage in children with Kawasaki disease
Objective To explore the risk factors for cardiac damage in children with Kawasaki disease(KD),and to identify cardiac damage as early as possible and make timely intervention measures.Methods The clinical data of 437 children with KD in the First Affiliated Hospital of Zhengzhou University from May 2018 to November 2023 were collected for a retrospective study,including 249 boys and 188 girls,aged from 2 months to 10 years.The patients were divided into a cardiac damage group(52 cases)and a non-cardiac damage group(385 cases)according to whether cardiac damage occurred.The clinical data of the two groups were compared,the risk factors of cardiac damage were analyzed,and the predictive value of the logistic prediction model was analyzed using receiver operating characteristic curve(ROC).Independent sample t test and x2 test were used.Results The proportions of the children with fever duration ≥10 d,intravenous immunoglobulin(IVIG)treatment delay,IVIG non-response,white blood cell count ≥10x 109/L,total bile acid＞14 μmol/L,C-reactive protein(CRP)＞46 mg/L,and hemoglobin(HGB)≥90 g/L in the cardiac damage group were higher than those in the non-cardiac damage group(all P＜0.05).The duration of fever,IVIG treatment delay,IVIG non-response,CRP,and HGB were the risk factors for cardiac damage in children with KD(all P＜0.05);Logit(P)=-11.754+1.333x duration of fever+1.520xIVIG treatment delay+1.761xIVIG non-response+1.676xCRP+1.345xHGB.The logistic regression equation predicted cardiac damage with an area under the curve(AUC)of 0.905(95％CI:0.874-0.931),with an optimal sensitivity and specificity of 90.38％and 90.65％,respectively,when compared with each of the correlates alone.Conclusions The occurrence of cardiac damage in children with KD is mainly related to the duration of fever,IVIG treatment delay,IVIG non-response,CRP,HGB,etc.Timely treatment and more strict monitoring and follow-up should be given to the children with the above clinical characteristics to optimize the long-term prognosis.
万方数据
维普
