The role of red blood cell distribution width in predicting coronary artery lesions in pediatric patients with kawasaki disease

Jianghui Cai; Mi Tang; Shuping Shuai; Rui Zhang; Hongxi Zhang; Yanfeng Yang; MengJun Wu; Hua Liang; Shasha Xing

doi:10.3389/fcvm.2023.1014890

The role of red blood cell distribution width in predicting coronary artery lesions in pediatric patients with kawasaki disease

Front Cardiovasc Med. 2023 Mar 3:10:1014890. doi: 10.3389/fcvm.2023.1014890. eCollection 2023.

Authors

Jianghui Cai¹, Mi Tang², Shuping Shuai¹, Rui Zhang¹, Hongxi Zhang¹, Yanfeng Yang³, MengJun Wu⁴, Hua Liang¹, Shasha Xing²

Affiliations

¹ Department of Pharmacy, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
² Office of Good Clinical Practice, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
³ Department of Pediatric Cardiology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
⁴ Department of Anesthesiology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.

Abstract

Background: Recent studies have shown that red blood cell distribution width (RDW) has emerged as a novel predictor of cardiovascular diseases. We aim to investigate the association between RDW and the risk of coronary artery lesions (CALs) in pediatric patients with Kawasaki disease (KD).

Methods: KD patients were classified as the CALs group (patients with CALs) and non-CALs group (patients without CALs). Differences among the groups were analyzed by Mann-Whitney U-test and Chi-square analysis. The independent risk factors of CALs were identified by multivariate logistic regression analysis, followed by receiver operating characteristic (ROC) curve analysis to calculate the optimal cut-off value.

Results: The red blood cell distribution width (RDW) and C-reactive protein were significantly higher in the CALs group than those in the non-CALs group (p < 0.01). Multivariate logistic regression analysis revealed that RDW (OR = 5.2, 95% CI, 4.064 to 6.654) was independent risk factors of CALs in KD patients (p < 0.01). The subgroup analysis also confirmed that the high level of RDW was an independent risk factor for the development of CALs in patients with complete and incomplete KD. The ROC analysis showed the optimal cut-off value of RDW for predicting CALs was >13.86%, with a sensitivity of 75.79% and specificity of 92.81% (AUC = 0.869, 95% CI = 0.844-0.892; p < 0.0001).

Conclusions: RDW is an independent predictor with high sensitivity and specificity to predict CALs in KD patients. The elevation in RDW level (>13.86%) may be used as novel biomarkers for early predicting CALs in KD patients during the acute phase.

Keywords: KD; cals; coronary artery lesion; kawasaki disease; red blood cell distribution.