A Nomogram Model for Predicting Recurrent Coronary Thrombosis in Kawasaki Disease Patients

Coronary thrombosis is a serious cardiovascular complication of Kawasaki disease (KD), and recurrence of coronary thrombosis increases the short-term risk of myocardial infarction and the long-term risk of coronary artery disease. However, there are currently no studies predicting the recurrence of coronary thrombosis, so the aim of this study was to develop and validate a nomogram to predict recurrent coronary thrombosis in KD patients.

This was a retrospective study of data from 149 KD patients who had a history of previous coronary disease at the Children's Hospital of Chongqing Medical University from 2013 to 2020. Independent risk factors were identified using univariate and multivariate logistic regression analyses, and a nomogram was constructed to predict recurrent coronary thrombosis.

Multivariate analysis showed that large coronary artery aneurysm(CAA) (Odds Ratio [OR] 4.28; 95% Confidence Interval [CI] 1.39-13.12), saccular CAA (OR 5.03; 95% CI 1.55-16.29), first left anterior descending (LAD) thrombosis (OR 3.90; 95% CI 1.20-12.63), and persistent CAA (OR 43.27; 95% CI 12.23-153.12) were independent risk factors for recurrent coronary thrombosis. Based on these variables, a nomogram was constructed. The Area Under the Curve (AUC) of the nomogram was 0.943, and tenfold cross-validation (200 replicates) showed an average AUC of 0.929. Furthermore, the nomogram not only presented a favorable calibration curve but also demonstrated practical clinical utility.

Large CAA, saccular CAA, first LAD thrombosis and persistent CAA were independent risk factors for recurrent coronary thrombosis. The nomogram can visually show these independent risk factors and predict probabilities.