关键词: 川崎病, 冠状动脉损伤, 风险因素, 列线图模型, 红细胞分布宽度, 白细胞, 肌钙蛋白I

Abstract: Objective To analyze the risk factors of coronary artery lesions (CAL) in children with Kawasaki disease and construct a nomogram prediction model for Kawasaki disease concurrent CAL. Methods A total of 220 children with Kawasaki disease who received treatment in cardiovascular department of Wuhan Children's Hospital from January 2021 to December 2023 were collected and divided into an analysis group (172 cases) and a validation group (48 cases). By analyzing the risk factors of Kawasaki disease concurrent CAL through univariate analysis and multivariate logistic regression analysis, a nomogram prediction model for Kawasaki disease concurrent CAL was constructed using R software, and the prediction model was validated using receiver operating characteristic (ROC) curves and calibration curves. Results In the analysis group of 172 Kawasaki disease cases, 42 developed CAL, with an incidence rate of 24.42% (42/172). Multivariate logistic regression analysis indicated that red blood cell distribution width (RDW) > 13.3% (OR=3.838), white blood cell count (WBC) > 10×10⁹/L (OR=2.363), cardiac troponin-I (cTnI) > 0.5 μg/L (OR=3.644), and C-reactive protein (CRP) > 50 mg/L (OR=4.614) were independent risk factors for Kawasaki disease concurrent CAL (all P<0.05). The area under the curve (AUC) of the nomogram prediction model for the analysis group was 0.851, and for the validation group, it was 0.920, indicating good consistency of the prediction model, with no significant difference in the goodness-of-fit test between the analysis group and validation group (P=0.573). Conclusion A nomogram prediction model composed of RDW, WBC, cTnI, and CRP may help guide the prevention of Kawasaki disease concurrent CAL.

Key words: Kawasaki disease, Coronary artery lesions, Risk factors, Nomogram model, Red blood cell distribution width, White blood cell, Troponin cardiac troponin-I