Using nomogram scores to predict the early regression of coronary artery aneurysms of Kawasaki disease

Abstract

Abstract Background: Coronary artery aneurysms have been considered the most serious complication of Kawasaki disease. However, some coronary artery aneurysms do regress. Therefore, the ability to predict the expected time of coronary artery aneurysm regression is critical. Herein, we have created a nomogram prediction system to determine the early regression (<1 month) among patients with small to medium coronary artery aneurysms. Methods: Seventy-six Kawasaki disease patients identified with coronary artery aneurysms during the acute or subacute phase were included. All the patients who met inclusion criteria demonstrated regression of coronary artery aneurysms within the first-year post Kawasaki disease diagnosis. The clinical and laboratory parameters were compared between the groups of coronary artery aneurysms regression duration within and beyond 1 month. Multivariate logistic regression analysis was used to identify the independent parameters for early regression based on the results from the univariable analysis. Then nomogram prediction systems were established with associated receiver operating characteristic curves. Results: Among the 76 included patients, 40 cases recovered within 1 month. Haemoglobin, globulin, activated partial thromboplastin time, the number of lesions, location of the aneurysm, and coronary artery aneurysm size were identified as independent factors for early regression of coronary artery aneurysms in Kawasaki disease patients. The predictive nomogram models revealed a high efficacy in predicting early regression of coronary artery aneurysms. Conclusion: The size of coronary artery aneurysms, the number of lesions, and the location of aneurysms presented better predictive value for predicting coronary artery aneurysms regression. The nomogram system created from the identified risk factors successfully predicted early coronary artery aneurysm regression.