Development and validation of a nomogram-based prognostic model to predict coronary artery lesions in Kawasaki disease from 6847 children in China

被引:0
|
作者
Li, Changjian [1 ]
Zhang, Huayong [1 ]
Yin, Wei [2 ]
Zhang, Yong [1 ]
机构
[1] Huazhong Univ Sci & Technol, Wuhan Childrens Hosp, Wuhan Maternal & Child Healthcare Hosp, Tongji Med Coll,Dept Cardiol, Wuhan 430016, Peoples R China
[2] Huazhong Univ Sci & Technol, Wuhan Childrens Hosp, Wuhan Maternal & Child Healthcare Hosp, Tongji Med Coll,Dept Rheumatol, Wuhan 430016, Peoples R China
关键词
Kawasaki disease; Coronary artery lesions; Predictive modeling; Columnar mapping; Intravenous immunoglobulin nonresponse; Children; INTRAVENOUS IMMUNOGLOBULIN; EPIDEMIOLOGIC FEATURES; RESISTANCE; ABNORMALITIES; JAPAN; RISK;
D O I
10.1016/j.cmpb.2025.108588
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Background and Objective: Predicting potential risk factors for the occurrence of coronary artery lesions (CAL) in children with Kawasaki disease (KD) is critical for subsequent treatment. The aim of our study was to establish and validate a nomograph-based model for identifying children with KD at risk for CAL. Methods: Hospitalized children with KD attending Wuhan Children's Hospital from Jan 2011 to Dec 2023 were included in the study and were grouped into a training set (4793 cases) and a validation set (2054 cases) using a simple random sampling method in a 7:3 ratio. The analysis was performed using RStudio software, which first used LASSO regression analysis to screen for the best predictors, and then analyzed the screened predictors using logistic regression analysis to derive independent predictors and construct a nomogram model to predict CAL risk. The receiver operating characteristic (ROC) and calibration curves were employed to evaluate the discrimination and calibration of the model. Finally, decision curve analysis (DCA) was utilized to validate the clinical applicability of the models assessed in the data. Results: Of the 6847 eligible children with KD included, 845 (12 %) were ultimately diagnosed with CAL, of whom 619 were boys (73 %) with a median age of 1.81 (0.74, 3.51) years. Six significant independent predictors were identified, including sex, intravenous immunoglobulin nonresponse, peripheral blood hemoglobin, platelet distribution width, platelet count, and serum albumin. Our model has acceptable discriminative power, with areas under the curve at 0.671 and 0.703 in the training and validation sets, respectively. DCA analysis showed that the prediction model had great clinical utility when the threshold probability interval was between 0.1 and 0.5. Conclusions: We constructed and internally validated a nomograph-based predictive model based on six variables consisting of sex, intravenous immunoglobulin nonresponse, peripheral blood hemoglobin, platelet distribution width, platelet count, and serum albumin, which may be useful for earlier identification of children with KD who may have CAL.
引用
收藏
页数:11
相关论文
共 50 条
  • [1] Establishment and validation of a nomogram for coronary artery lesions in children with Kawasaki disease
    Hu, Chong
    Yan, Xiao
    Song, Henglian
    Dong, Qin
    Yi, Changying
    Li, Jianzhi
    Lv, Xin
    FRONTIERS IN CARDIOVASCULAR MEDICINE, 2025, 11
  • [2] Development and Validation of a Nomogram-Based Prognostic Model to Predict High Blood Pressure in Children and Adolescents-Findings From 342,736 Individuals in China
    Liang, Jing-Hong
    Zhao, Yu
    Chen, Yi-Can
    Huang, Shan
    Zhang, Shu-Xin
    Jiang, Nan
    Kakaer, Aerziguli
    Chen, Ya-Jun
    FRONTIERS IN CARDIOVASCULAR MEDICINE, 2022, 9
  • [3] Development and Validation of a Nomogram-Based Prognostic Evaluation Model for Sarcomatoid Hepatocellular Carcinoma
    Dazhuang Ge
    Zhiwen Luo
    Rui Mao
    Hong Zhao
    Xueyan Lv
    Jianjun Zhao
    Jianguo Zhou
    Zhen Huang
    Yefan Zhang
    Zhiyu Li
    Xinyu Bi
    Jianqiang Cai
    Advances in Therapy, 2020, 37 : 3185 - 3205
  • [4] Development and Validation of a Nomogram-Based Prognostic Evaluation Model for Sarcomatoid Hepatocellular Carcinoma
    Ge, Dazhuang
    Luo, Zhiwen
    Mao, Rui
    Zhao, Hong
    Lv, Xueyan
    Zhao, Jianjun
    Zhou, Jianguo
    Huang, Zhen
    Zhang, Yefan
    Li, Zhiyu
    Bi, Xinyu
    Cai, Jianqiang
    ADVANCES IN THERAPY, 2020, 37 (07) : 3185 - 3205
  • [5] A nomogram for predicting coronary artery lesions in patients with Kawasaki disease
    Xuan, Wenjie
    Yao, Yinping
    Wang, Yayun
    Chen, Xiaohong
    Yao, Huanying
    MEDICINE, 2024, 103 (44)
  • [6] Nomogram for predicting coronary artery lesions in patients with Kawasaki disease
    Chen, Jie
    Li, Jing
    Yue, Yang-hua
    Liu, Yu
    Xie, Tian
    Peng, Jian-qiao
    Deng, Zhong-hua
    Cao, You-de
    CLINICAL CARDIOLOGY, 2023, 46 (11) : 1434 - 1441
  • [7] A Nomogram to Predict Patients with Obstructive Coronary Artery Disease: Development and Validation
    Han, Zesen
    Lai, Lihong
    Pu, Zhaokun
    Yang, Lan
    CARDIOVASCULAR INNOVATIONS AND APPLICATIONS, 2021, 5 (04) : 245 - 255
  • [8] Development of a prediction model for progression of coronary artery lesions in Kawasaki disease
    Dan Xu
    Ye-Shi Chen
    Chen-Hui Feng
    Ai-Mei Cao
    Xiao-Hui Li
    Pediatric Research, 2024, 95 : 1041 - 1050
  • [9] Development of a prediction model for progression of coronary artery lesions in Kawasaki disease
    Xu, Dan
    Chen, Ye-Shi
    Feng, Chen-Hui
    Cao, Ai-Mei
    Li, Xiao-Hui
    PEDIATRIC RESEARCH, 2024, 95 (04) : 1041 - 1050
  • [10] Development and Validation of KCPREDICT: A Deep Learning Model for Early Detection of Coronary Artery Lesions in Kawasaki Disease Patients
    Yang, Lei
    Shen, Xiaoyu
    Liu, Yiman
    Chen, Jiangang
    Zou, Yuwen
    Xu, Lihao
    Ji, Wei
    Zhang, Yuqi
    Liu, Tingliang
    Cao, Qing
    PEDIATRIC CARDIOLOGY, 2025,