Abstract
This study aimed to investigate the association between red blood cell distribution width (RDW) and the risk of coronary artery lesions (CALs) in patients with Kawasaki disease (KD). A total of 1355 patients who met the diagnostic criteria for KD were reviewed between January 2018 and December 2019, including 636 patients with CALs and 719 patients without CALs. Blood samples for RDW were obtained at admission (before intravenous immunoglobulin treatment). A logistic regression analysis was performed, and a receiver operating characteristic curve was constructed to determine the prognostic value of RDW standard deviation (RDW-SD) and RDW coefficient of variation (RDW-CV). The study was registered at www.chictr.org.cn, No.: ChiCTR 2000040980. The results showed that RDW-SD increased in patients with complete KD and CALs compared with patients with complete KD without CALs (39 fL vs. 38 fL, respectively; p = 0.000). RDW-CV in patients with complete KD and CALs was significantly higher compared with patients with completed KD without CALs (p = 0.000). Further multivariate logistic regression analysis revealed that RDW-SD was an independent marker of CALs in patients with complete KD (p = 0.001), but no association was found between RDW-CV and CALs. The area under the curve of RDW-SD for predicting CALs in patients with complete KD was 0.606 (95% confidence interval 0.572–0.640; p = 0.000) with a sensitivity and specificity of 61% and 55%, respectively, when the optimal cut-off value of RDW-SD was 38.5 fL. RDW-CV increased in patients with incomplete KD and CALs compared with patients without CALs (13.55% vs 13.3%, respectively; p = 0.004), and multivariate logistic regression analysis revealed that RDW-CV was an independent marker of CALs in patients with incomplete KD (p = 0.021). The area under the curve of RDW-CV for predicting CALs in patients with incomplete KD was 0.597 (95% confidence interval 0.532–0.661; p = 0.004) with a sensitivity and specificity of 40% and 77%, respectively, when the optimal cut-off value of RDW-SD was 13.85%. Conclusion: RDW can be used as an independent predictive marker of CALs in patients with KD, but the type of KD should be considered. RDW-SD was an independent marker of CALs in patients with complete KD, while RDW-CV was a predictor of incomplete KD.
Highlights
Kawasaki disease (KD), which is an acute systemic vasculitis of unknown cause, usually occurs in children < 5 years of age [1]
In patients with complete KD, a high red blood cell distribution width (RDW)-standard deviation (SD) was associated with coronary artery lesions (CALs) after adjusting for age, sex, hemoglobin, glutamyltranspeptidase, procalcitonin, AST/ALT, albumin, serum sodium, RDW coefficient of variation (RDW-CV) and intravenous immunoglobulin (IVIG) resistance [odds ratio 1.115 (95% confidence interval 1.046–1.188); p = 0.001] (Table 3)
After adjusting for age, sex, mean erythrocyte volume and total bilirubin, the high RDW-CV levels was an independent risk factor for the development of CALs in patients with incomplete KD [odds ratio 1.428 (95% confidence interval 1.056–1.930); p = 0.021] (Table 3)
Summary
Kawasaki disease (KD), which is an acute systemic vasculitis of unknown cause, usually occurs in children < 5 years of age [1]. The prevalence of CALs can be minimized if treatment with intravenous immunoglobulin (IVIG) is administered before the 10th day of disease [2]. Approximately 10–15% of patients with KD are IVIG resistant and are at an increased risk of developing CALs [3, 4]. CALs may persist and progress to obstruction or stenosis, leading to ischemia and even sudden death. KD is the leading cause of acquired heart disease in developed countries [5, 6]. The prognosis, follow up, and long-term management of patients with KD depend mainly on the severity of CALs. Clinicians tend to treat patients with KD who are at a high risk of CALs more aggressively to block the inflammatory response and minimize progression to CALs. risk factors for CALs have been studied extensively, no specific biological markers for predicting CALs in clinical practice have been established far
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