Prediction of Coronary Artery Lesions in Patients With Recurrent Kawasaki Disease

作者全名："Yang, Penghui; Zhang, Jing; Liu, Yihao; Feng, Siqi; Yi, Qijian"

作者地址："[Yang, Penghui; Zhang, Jing; Liu, Yihao; Feng, Siqi; Yi, Qijian] Chongqing Med Univ, Dept Cardiovasc Med, Chongqing, Peoples R China; [Yang, Penghui; Zhang, Jing; Liu, Yihao; Feng, Siqi; Yi, Qijian] Chongqing Med Univ, Minist Educ Key Lab Child Dev & Disorders, Chongqing, Peoples R China; [Yang, Penghui; Zhang, Jing; Liu, Yihao; Feng, Siqi; Yi, Qijian] Chongqing Med Univ, Natl Clin Res Ctr Child Hlth & Disorders, Chongqing, Peoples R China; [Yang, Penghui; Zhang, Jing; Liu, Yihao; Feng, Siqi; Yi, Qijian] Chongqing Med Univ, China Int Sci & Technol Cooperat Base Child Dev &, Chongqing, Peoples R China; [Yang, Penghui; Zhang, Jing; Liu, Yihao; Feng, Siqi; Yi, Qijian] Chongqing Med Univ, Chongqing Key Lab Pediat, Childrens Hosp, Chongqing, Peoples R China; [Feng, Siqi; Yi, Qijian] Chongqing Med Univ, Childrens Hosp, Dept Cardiovasc Med, Chongqing 400014, Peoples R China"

通信作者："Feng, SQ; Yi, QJ (通讯作者)，Chongqing Med Univ, Childrens Hosp, Dept Cardiovasc Med, Chongqing 400014, Peoples R China."

来源：PEDIATRIC INFECTIOUS DISEASE JOURNAL

ESI学科分类：IMMUNOLOGY

WOS号：WOS:001145838900015

JCR分区：Q1

影响因子：2.9

年份：2024

卷号：43

期号：2

开始页：101

结束页：108

文献类型：Article

关键词：recurrent Kawasaki disease; coronary artery lesions; nomogram; prediction model

摘要："Background:A subset of patients with Kawasaki disease (KD) will suffer recurrence. However, there is still a lack of accurate prediction models for coronary artery lesions (CAL) in recurrent KD patients. It is necessary to establish a new nomogram model for predicting CAL in patients with recurrent KD.Data from patients with recurrent KD between 2015 and 2021 were retrospectively reviewed. After splitting the patients into training and validation cohorts, the least absolute shrinkage and selection operator was used to select the predictors of CAL and multivariate logistic regression was used to construct a nomogram based on the selected predictors. The application of area under the receiver operating characteristic curve (AUC), calibration curves, Hosmer-Lemeshow test, Brier score and decision curve analysis were used to assess the model performance.A total of 159 recurrent KD patients were enrolled, 66 (41.5%) of whom had CAL. Hemoglobin levels, CAL at the first episode, and intravenous immunoglobulin resistance at recurrence were identified by the least absolute shrinkage and selection operator regression analysis as significant predictors. The model incorporating these predictors showed good discrimination (AUC, 0.777) and calibration capacities (Hosmer-Lemeshow P value, 0.418; Brier score, 0.190) in the training cohort. Application of the model to the validation cohort yielded an AUC of 0.741, a Hosmer-Lemeshow P value of 0.623 and a Brier score of 0.190. The decision curve analysis demonstrated that the nomogram model was clinically useful.The proposed nomogram model could help clinicians assess the risk of CAL in patients with recurrent KD.Background:A subset of patients with Kawasaki disease (KD) will suffer recurrence. However, there is still a lack of accurate prediction models for coronary artery lesions (CAL) in recurrent KD patients. It is necessary to establish a new nomogram model for predicting CAL in patients with recurrent KD.Data from patients with recurrent KD between 2015 and 2021 were retrospectively reviewed. After splitting the patients into training and validation cohorts, the least absolute shrinkage and selection operator was used to select the predictors of CAL and multivariate logistic regression was used to construct a nomogram based on the selected predictors. The application of area under the receiver operating characteristic curve (AUC), calibration curves, Hosmer-Lemeshow test, Brier score and decision curve analysis were used to assess the model performance.A total of 159 recurrent KD patients were enrolled, 66 (41.5%) of whom had CAL. Hemoglobin levels, CAL at the first episode, and intravenous immunoglobulin resistance at recurrence were identified by the least absolute shrinkage and selection operator regression analysis as significant predictors. The model incorporating these predictors showed good discrimination (AUC, 0.777) and calibration capacities (Hosmer-Lemeshow P value, 0.418; Brier score, 0.190) in the training cohort. Application of the model to the validation cohort yielded an AUC of 0.741, a Hosmer-Lemeshow P value of 0.623 and a Brier score of 0.190. The decision curve analysis demonstrated that the nomogram model was clinically useful.The proposed nomogram model could help clinicians assess the risk of CAL in patients with recurrent KD.Background:A subset of patients with Kawasaki disease (KD) will suffer recurrence. However, there is still a lack of accurate prediction models for coronary artery lesions (CAL) in recurrent KD patients. It is necessary to establish a new nomogram model for predicting CAL in patients with recurrent KD.Data from patients with recurrent KD between 2015 and 2021 were retrospectively reviewed. After splitting the patients into training and validation cohorts, the least absolute shrinkage and selection operator was used to select the predictors of CAL and multivariate logistic regression was used to construct a nomogram based on the selected predictors. The application of area under the receiver operating characteristic curve (AUC), calibration curves, Hosmer-Lemeshow test, Brier score and decision curve analysis were used to assess the model performance.A total of 159 recurrent KD patients were enrolled, 66 (41.5%) of whom had CAL. Hemoglobin levels, CAL at the first episode, and intravenous immunoglobulin resistance at recurrence were identified by the least absolute shrinkage and selection operator regression analysis as significant predictors. The model incorporating these predictors showed good discrimination (AUC, 0.777) and calibration capacities (Hosmer-Lemeshow P value, 0.418; Brier score, 0.190) in the training cohort. Application of the model to the validation cohort yielded an AUC of 0.741, a Hosmer-Lemeshow P value of 0.623 and a Brier score of 0.190. The decision curve analysis demonstrated that the nomogram model was clinically useful.The proposed nomogram model could help clinicians assess the risk of CAL in patients with recurrent KD.Background:A subset of patients with Kawasaki disease (KD) will suffer recurrence. However, there is still a lack of accurate prediction models for coronary artery lesions (CAL) in recurrent KD patients. It is necessary to establish a new nomogram model for predicting CAL in patients with recurrent KD.Data from patients with recurrent KD between 2015 and 2021 were retrospectively reviewed. After splitting the patients into training and validation cohorts, the least absolute shrinkage and selection operator was used to select the predictors of CAL and multivariate logistic regression was used to construct a nomogram based on the selected predictors. The application of area under the receiver operating characteristic curve (AUC), calibration curves, Hosmer-Lemeshow test, Brier score and decision curve analysis were used to assess the model performance.A total of 159 recurrent KD patients were enrolled, 66 (41.5%) of whom had CAL. Hemoglobin levels, CAL at the first episode, and intravenous immunoglobulin resistance at recurrence were identified by the least absolute shrinkage and selection operator regression analysis as significant predictors. The model incorporating these predictors showed good discrimination (AUC, 0.777) and calibration capacities (Hosmer-Lemeshow P value, 0.418; Brier score, 0.190) in the training cohort. Application of the model to the validation cohort yielded an AUC of 0.741, a Hosmer-Lemeshow P value of 0.623 and a Brier score of 0.190. The decision curve analysis demonstrated that the nomogram model was clinically useful.The proposed nomogram model could help clinicians assess the risk of CAL in patients with recurrent KD."

基金机构：General Project of the National Clinical Research Center for Child Health and Diseases

基金资助正文：No Statement Available