Table 2_A nomogram for predicting the risk of persistent coronary artery aneurysms in children with Kawasaki disease: a retrospective study.xlsx

ObjectiveTo develop and validate a nomogram for the individualized prediction of persistent coronary artery aneurysms (CAAs) in children with Kawasaki disease (KD) who have developed CAAs in the acute phase.
MethodsThis retrospective cohort study enrolled children diagnosed with KD and complicated by CAA between September 2015 and December 2023. The primary outcome was defined as the persistence of CAA 90 days after disease onset. Predictor selection was performed using 1,000 bootstrap resamples combined with LASSO regression for stability. A predictive model was constructed using multivariate logistic regression. The model's discrimination, calibration, and clinical utility were assessed by the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA).
ResultsA total of 135 children were included, of whom 80 (59.3%) had persistent CAAs. Stability selection identified the maximum coronary artery Z-score (ZM), age < 12 months (Age1), and total bile acid (TBA) as key predictors. The parsimonious model (Model B) built on these predictors demonstrated excellent performance, with an optimism-corrected AUC of 0.933 (95% CI: 0.905–0.960). It was well-calibrated, and DCA showed a positive net benefit across a wide threshold probability range of 5%–100%.
ConclusionThis study successfully developed a nomogram based on ZM, Age1, and TBA. This tool can effectively identify KD children at risk of persistent CAAs, providing an intuitive and quantitative decision-making aid for precise risk stratification and optimized long-term management in this high-risk population.