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Red Blood Cell Distribution Width as a Predictive Marker for Coronary Artery Lesions in Patients with Kawasaki
Li Ming1, Hui-Ling Cao2, Qiushu Li1
1Chongqing Key Laboratory of Pediatrics, China International Science and Technology Cooperation Base of Child Development and Critical Disorders, Department of Heart Centre, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Children's Hospital of Chongqing Medical University, Chongqing, 400014, China.
Insights
Red blood cell distribution width (RDW) can predict coronary artery lesions (CALs) in Kawasaki disease (KD). RDW standard deviation (RDW-SD) indicates CALs in complete KD, while RDW coefficient of variation (RDW-CV) predicts CALs in incomplete KD.
Area of Science:
- Cardiology
- Pediatrics
- Hematology
Background:
- Kawasaki disease (KD) is a critical pediatric illness leading to coronary artery lesions (CALs).
- Early detection of CALs risk is vital for timely intervention in KD patients.
- Red blood cell distribution width (RDW) is a readily available hematological parameter reflecting red blood cell size variability.
Purpose of the Study:
- To investigate the association between RDW and the risk of developing CALs in patients diagnosed with KD.
- To evaluate the prognostic value of RDW standard deviation (RDW-SD) and RDW coefficient of variation (RDW-CV) in predicting CALs.
- To determine if RDW can serve as an independent predictive marker for CALs in different KD classifications.
Main Methods:
- A retrospective study involving 1355 KD patients (January 2018-December 2019), categorized by the presence (636) or absence (719) of CALs.
- RDW measurements (RDW-SD and RDW-CV) were obtained at admission before treatment.
- Logistic regression analysis and receiver operating characteristic (ROC) curve analysis were employed to assess RDW's predictive value.
Main Results:
- RDW-SD was significantly higher in complete KD patients with CALs compared to those without (39 fL vs. 38 fL, p=0.000).
- RDW-CV was also significantly elevated in complete KD patients with CALs (p=0.000).
- Multivariate analysis identified RDW-SD as an independent predictor of CALs in complete KD (p=0.001), with an AUC of 0.606.
- RDW-CV was found to be an independent predictor of CALs in incomplete KD (p=0.021), with an AUC of 0.597.
Conclusions:
- RDW serves as an independent predictive marker for CALs in Kawasaki disease.
- RDW-SD is a valuable indicator for predicting CALs in complete KD.
- RDW-CV is a significant predictor for CALs in incomplete KD, highlighting the importance of considering KD classification.
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.
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