This study aimed to identify risk factors for the progression of coronary artery lesions (CALs) in children with Kawasaki disease (KD) and to establish a nomogram for predicting this risk. We retrospectively analyzed clinical and echocardiographic data from KD patients diagnosed at Beijing Children’s Hospital from 1 January 2021 to 30 December 2023.The patients were categorized into the progression and non-progression groups on the basis of coronary artery Z-scores and diameters at the 1-month follow-up compared with baseline. Univariate logistic regression identified significant indicators, supplemented by factors from the literature. We used full permutation to examine potential combinations, followed by multivariate logistic regression to calculate the Akaike information criterion (AIC) and area under the curve (AUC) for each model. We selected the best values for establishing a prediction score and nomogram. Model performance was assessed using the AUC, calibration curves, and tenfold cross-validation. Among 1249 patients, 183 (14.7%) experienced progression of CALs, while 1066 (85.3%) showed improvement or stability. Eight independent factors were identified: the baseline maximum Z-score, age, percentage of neutrophils, hemoglobin concentrations, erythrocyte sedimentation rate, albumin, fibrinogen, and intravenous immunoglobulin resistance. The nomogram model showed an AUC of 0.788, with a mean AUC of 0.775 and an accuracy of 85.6% after tenfold cross-validation. Conclusion: The baseline maximum Z-score, age, percentage of neutrophils, hemoglobin concentrations, erythrocyte sedimentation rate, albumin, fibrinogen, and intravenous immunoglobulin resistance are predictive factors for CALs progression in KD. The established nomogram shows high accuracy and reliability, aiding clinicians in decision-making.<Table Float="No" ID="Taba"> <tgroup cols="1"> <colspec align="left" colname="c1" colnum="1" /> <tbody> <row> <entry align="left" colname="c1"> What is known: • Since the introduction of IVIG therapy, most children with KD show CALs regression, yet a subset experience progressive CALs despite treatment. • CALs progression is associated with increased adverse cardiovascular events, yet predictors of this progression remain poorly characterized. </entry> </row> <row> <entry align="left" colname="c1"> What is new: • The eight-factor predictive model developed in this study effectively identifies progression risks in CALs following treatment, providing a basis for personalized clinical management. • Echocardiography, the primary modality for assessing coronary arteries in children, demonstrates that early baseline Z-score evaluation serves as the strongest predictor for CALs progression, while non-coronary cardiac abnormalities show no significant association. </entry> </row> </tbody> </tgroup> </Table>

Development of a predictive model for the progression of Kawasaki disease: a retrospective analysis of clinical and echocardiographic data

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发表日期：

2025年5月22日

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Hongqiang Yin,
Ruijuan Su,
Dongmei Liu,
Yawen Deng,
Ning Ma

摘要

This study aimed to identify risk factors for the progression of coronary artery lesions (CALs) in children with Kawasaki disease (KD) and to establish a nomogram for predicting this risk. We retrospectively analyzed clinical and echocardiographic data from KD patients diagnosed at Beijing Children’s Hospital from 1 January 2021 to 30 December 2023.The patients were categorized into the progression and non-progression groups on the basis of coronary artery Z-scores and diameters at the 1-month follow-up compared with baseline. Univariate logistic regression identified significant indicators, supplemented by factors from the literature. We used full permutation to examine potential combinations, followed by multivariate logistic regression to calculate the Akaike information criterion (AIC) and area under the curve (AUC) for each model. We selected the best values for establishing a prediction score and nomogram. Model performance was assessed using the AUC, calibration curves, and tenfold cross-validation. Among 1249 patients, 183 (14.7%) experienced progression of CALs, while 1066 (85.3%) showed improvement or stability. Eight independent factors were identified: the baseline maximum Z-score, age, percentage of neutrophils, hemoglobin concentrations, erythrocyte sedimentation rate, albumin, fibrinogen, and intravenous immunoglobulin resistance. The nomogram model showed an AUC of 0.788, with a mean AUC of 0.775 and an accuracy of 85.6% after tenfold cross-validation.

Conclusion: The baseline maximum Z-score, age, percentage of neutrophils, hemoglobin concentrations, erythrocyte sedimentation rate, albumin, fibrinogen, and intravenous immunoglobulin resistance are predictive factors for CALs progression in KD. The established nomogram shows high accuracy and reliability, aiding clinicians in decision-making.

What is known:

• Since the introduction of IVIG therapy, most children with KD show CALs regression, yet a subset experience progressive CALs despite treatment.

• CALs progression is associated with increased adverse cardiovascular events, yet predictors of this progression remain poorly characterized.

What is new:

• The eight-factor predictive model developed in this study effectively identifies progression risks in CALs following treatment, providing a basis for personalized clinical management.

• Echocardiography, the primary modality for assessing coronary arteries in children, demonstrates that early baseline Z-score evaluation serves as the strongest predictor for CALs progression, while non-coronary cardiac abnormalities show no significant association.