Red Blood Cell Distribution Width Value as a Predictor for Mortality in Stroke Patients
1Department of Emergency, Emergency Medicine Research Team, Imam Reza Hospital, Tabriz University of Medical Sciences, Tabriz, Iran
2Cardiovascular Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
3Department of Pathology, Azad University Faculty of Medicine, Tabriz, Iran
4Medical Student, Azad University Faculty of Medicine, Tabriz, Iran
5Medical Philosophy and History Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
J Clin Pract Res 2020; 42(3): 317-321 DOI: 10.14744/etd.2020.37929
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Abstract

Objective: Acute ischemic stroke (AIS) is a clinical condition that generally arises from non-traumatic brain vascular disorders. In this regard, red blood cell width distribution (RDW) is considered as a biochemical factor that could be used for stroke diagnosis. The main purpose of this study is regarding the use of red cell width distribution (RDW) in predicting of stroke patients for optimal use of facilities.
Materials and Methods: In the current study, about 500 patients were included with a definitive diagnosis of cerebrovascular events that were referred to the emergency department of Emam-Reza hospital in 2015. Patients were randomly selected in the morning, evening and night shifts. The related analyses were performed according to the prepared checklist, including patient demographic information, outcomes and routine laboratory tests.
Results: Based on our results, there is not a significant difference between RDW and gender, stroke type and diabetes occurrence, while a direct relationship between patient clinical appearance, age and numbers of WBC was observed. In fact, the mean of WBC count was 8331 in patients with complete remission, 9736 in partial remission and 9640 in expired subjects (p=0.001). We also found that RDW changed according to patients’ outcomes.
Conclusion: Together, we conclude that WBC and age are able to affect the RDW significantly, which correlated with the outcome and mortality of stroke patients. By measuring these parameters early in stroke patients, further outcomes and disabilities in stroke patients can be predicted by on time interventions to prevent stroke-related complications and mortality.