Hui XU, Jing LIU, Tong-ru ZHANG. Construction of risk model for heart damage in children with Kawasaki disease and predictive value of pro-BNP[J]. Chinese Heart Journal, 2022, 34(1): 36-40. DOI: 10.12125/j.chj.202101061
    Citation: Hui XU, Jing LIU, Tong-ru ZHANG. Construction of risk model for heart damage in children with Kawasaki disease and predictive value of pro-BNP[J]. Chinese Heart Journal, 2022, 34(1): 36-40. DOI: 10.12125/j.chj.202101061

    Construction of risk model for heart damage in children with Kawasaki disease and predictive value of pro-BNP

    •   AIM  To explore the risk of complicated heart damage in children with Kawasaki disease (KD) and the predictive value of forebrain natriuretic peptide (pro-BNP) and to establish and verify a line graph model to predict the risk factors of heart damage.
        METHODS  A total of 450 KD children admitted to our hospital from January 2016 to July 2020 were randomly selected by using the random number table, among whom 56 had heart damage and 394 had no heart damage. Clinical data of the patients was analyzed retrospectively and independent risk factors for heart damage of KD children were screened out by logistic regression analysis. R software was used to establish the nomogram prediction model for the screened independent risk factors, and the prediction and accuracy of the model were verified.
        RESULTS  By logistic binary regression analysis of the risk factor data of the patients, we could know that gender (OR=2.856, 95%CI: 1.493 - 5.461), days of fever (OR=3.636, 95%CI: 1.636 - 8.083), CRP (OR=2.519, 95%CI: 1.332 - 4.763), treatment timing (OR=6.057, 95%CI: 2.289 - 16.024) and course of disease during proglobulin treatment (OR=3.963, 95%CI: 2.065 - 7.607) were the independent risk factors for heart damage in children with KD. Based on the above five risk factors, a calibration graph model was established and the calibration result showed that the predicted value matched the measured value curve more closely, indicating that the predicted model had better accuracy than the actual measured value. Meanwhile, the internal validation results of Bootstrap showed that the C-index index was as high as (OR=4.705, 95%CI: 2.474-8.947), indicating that the model had good accuracy and differentiation.
        CONCLUSION  Through the establishment of a risk model, gender, fever days, CRP, treatment timing and HGB are screened out as the risks of heart damage in KD children. Effective prevention and treatment measures aimed at these risks could reduce the incidence of heart damage in KD children and are of significance for the prognosis of patients.
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