Backgrounds: This study aimed to identify risk factors for the progression of coronary artery lesions (CALs) in children with Kawasaki disease (KD) and to develop a nomogram prediction model.
Methods: This is a retrospective case-control study in which the participants were categorized into three groups based on the changes of the maximum Z score (Zmax) of coronary arteries at the 1-month follow-up compared with the baseline Zmax: CALs-progressed, CALs-improved, and CALs-unchanged.
Results: Of total 387 patients, 65 (27%), 319 (73%), and 3 (0.7%) patients were categorized into CALs-progressed group, CALs-improved group, and CALs-unchanged group, respectively. Six independent factors associated with CALs progression were identified, including initial IVIG resistance, baseline Zmax, the number of coronary arteries involved, C-reactive protein, albumin, and soluble interleukin-2 receptor (odds ratio: 7.19, 1.51, 2.32, 1.52, 0.86, and 1.46, respectively; all P-values < 0.01). The nomogram prediction model including these six independent risk factors yielded an area under the curve (AUC) of 0.80 (95% confidence interval, 0.74 to 0.86). The accuracy of this model reached 81.7% after the Monte-Carlo Bootstrapping 1000 repetitions.
Conclusions: The nomogram prediction model can identify children at high risk for the progression of CALs at early stages.
Impact: Six independent factors associated with CALs progression were identified, including initial IVIG resistance, baseline Zmax, the number of coronary arteries involved, CRP, ALB, and sIL-2R. The prediction model we constructed can identify children at high risk for the progression of CALs at early stages and help clinicians make individualized treatment plans. Prospective, multi-centered studies with larger sample sizes are warranted to validate the power of this prediction model in children with KD.
© 2023. The Author(s), under exclusive licence to the International Pediatric Research Foundation, Inc.