- Author:
Sohyun KIM
1
;
Lucy Youngmin EUN
Author Information
- Publication Type:Original Article
- Keywords: Iron deficiency anemia; Kawasaki disease; Coronary artery abnormalities
- MeSH: Anemia; Anemia, Iron-Deficiency; Coronary Vessels; Early Intervention (Education); Ferritins; Humans; Iron; Logistic Models; Micronutrients; Mucocutaneous Lymph Node Syndrome; Odds Ratio; Retrospective Studies
- From:Korean Journal of Pediatrics 2019;62(8):301-306
- CountryRepublic of Korea
- Language:English
- Abstract: PURPOSE: Coronary artery abnormalities (CAA) are the most important complications of Kawasaki disease (KD). Iron deficiency anemia (IDA) is a prevalent micronutrient deficiency and its association with KD remains unknown. We hypothesized that presence of IDA could be a predictor of CAA. METHODS: This retrospective study included 173 KD patients, divided into 2 groups according to absence (group 1) and presence (group 2) of CAA. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using a logistic regression model to estimate the association between CAA and other indicators. Due to collinearity between indicators of IDA, each indicator was paired with anemia in 3 models. RESULTS: Serum iron, iron saturation, and ferritin concentration, the 3 indicators of IDA, were significantly higher in group 1 than in group 2. Three sets of models including anemia with iron indicators produced the OR of CAA of 3.513, 3.171, and 2.256, respectively. The 3 indicators of IDA were negatively associated with CAA, by OR of 0.965, 0.914, and 0.944, respectively. The areas under the curve (AUCs) of ferritin concentration, iron saturation, serum iron, anemia, and Kobayashi score were 0.907 (95% CI, 0.851–0.963), 0.729 (95% CI, 0.648–0.810), 0.711 (95% CI, 0.629–0.793), 0.638 (95% CI, 0.545–0.731), and 0.563 (95% CI, 0.489–0.636), respectively. CONCLUSION: Indicators of IDA, especially ferritin, were highly associated with CAA; therefore, they were stronger predictors of CAA than Kobayashi scores. IDA indicators can be used to predict CAA development and to suggest requirements for early interventions.