1. Red Blood Cell Distribution Width as a Predictive Marker for Coronary Artery Lesions in Patients with Kawasaki Disease
- Author
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Hui-ling Cao, Qiushu Li, Gengsheng Yu, and Li Ming
- Subjects
medicine.medical_specialty ,Coefficient of variation ,030204 cardiovascular system & hematology ,Logistic regression ,Gastroenterology ,03 medical and health sciences ,0302 clinical medicine ,Coronary artery lesion ,Internal medicine ,medicine ,Red blood cell distribution ,Predictive marker ,Kawasaki disease ,Receiver operating characteristic ,business.industry ,Area under the curve ,Red blood cell distribution width ,medicine.disease ,humanities ,Confidence interval ,stomatognathic diseases ,030220 oncology & carcinogenesis ,Pediatrics, Perinatology and Child Health ,Original Article ,Cardiology and Cardiovascular Medicine ,business - 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.
- Published
- 2021
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