A practical nomogram for predicting coronary thrombosis for Kawasaki disease patients with medium or large coronary

Yue Peng1, Zhenli Cheng1, Qijian Yi2

  • 1Department of Cardiovascular Medicine, Children's Hospital of Chongqing Medical University, Chongqing, 400014, People's Republic of China.

Insights

A new model predicts coronary thrombosis in children with Kawasaki disease (KD) and medium to large coronary artery aneurysms (CAA). This tool aids clinicians in managing KD patients at high risk for this serious cardiovascular complication.

Area of Science:

  • Pediatric Cardiology
  • Cardiovascular Research
  • Medical Informatics

Background:

  • Kawasaki disease (KD) is a leading cause of acquired heart disease in children.
  • Coronary thrombosis is a severe complication of KD, impacting long-term outcomes.
  • Predictive models are needed for KD patients with medium or large coronary artery aneurysms (CAA).

Purpose of the Study:

  • To develop and validate a predictive model for coronary thrombosis in KD patients with medium or large CAA.
  • To identify independent risk factors associated with coronary thrombosis in this patient cohort.

Main Methods:

  • Retrospective analysis of 358 KD patients with medium or large CAA.
  • Collection of demographic, clinical, laboratory, and radiological data.
  • Development of a nomogram using logistic regression and validated with tenfold cross-validation.

Main Results:

  • Key predictors identified: male sex, large CAA, no high-dose aspirin pre-IVIG, multi-vessel involvement, elevated fibrinogen, and shorter thrombin time.
  • The developed nomogram demonstrated excellent predictive performance (AUC 0.920, cross-validation AUC 0.902).
  • The nomogram showed good calibration and clinical utility.

Conclusions:

  • A validated nomogram effectively predicts coronary thrombosis in KD patients with medium or large CAA.
  • The model, based on readily available clinical variables, aids clinical decision-making.
  • This tool can improve the management and treatment strategies for high-risk KD patients.

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