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ORIGINAL ARTICLE
Year : 2020  |  Volume : 11  |  Issue : 1  |  Page : 61-67

The use of antithrombin as a predictive tool in determining the development of stroke in patients with sickle cell anemia based on transcranial doppler ultrasound risk group


1 Department of Haematology and Blood Transfusion, College of Medicine, University of Lagos, Lagos, Nigeria
2 Department of Haematology and Blood Transfusion, Lagos State University College of Medicine, Lagos, Nigeria
3 Department of Chemical Pathology, College of Medicine, University of Lagos, Lagos, Nigeria
4 Department of Physiotherapy, College of Medicine, University of Lagos, Lagos, Nigeria

Correspondence Address:
Dr. Ebele Uche
Department of Haematology and Blood Transfusion, Lagos State University College of Medicine, Lagos
Nigeria
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/atp.atp_38_19

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Background: Stroke affects up to 10% of individuals with sickle cell anemia (SCA), and its development has been linked to excessive intravascular hemolysis and arterial thrombosis Increased intracerebral blood flow (CBF) velocity as measured by the transcranial Doppler ultrasonography (TCD) identifies children with SCA with an increased risk of development of stroke. This study measured antithrombin (AT) levels among SCA patients as a predictor of TCD risk groups for the development of stroke. Materials and Methods: A total of 180 participants consisting of 135 SCA patients and 45 age-matched hemoglobin phenotype AA (HbAA) controls were enrolled into the study. CBF velocity was measured with TCD and results were used to classify the SCA group into standard risk, conditional risk, and high risk. AT functional activity, prothrombin time (PT), and activated partial thromboplastin time (APTT) of all participants were measured. Statistical tools including independent t-test, analysis of variance, Pearson's correlation, hierarchical multiple regression, and forward liner regression were used to analyze all continuous variables. P <0.05 was considered statistically significant. Results: The AT levels were 83.01 ± 15.40% and 106.12 ± 14.79% in HbAA and SCA participants, respectively, with t = −7.294 and P = 0.001. The PT and APTT of the SCA and control groups were 15.51 ± 1.22 s, 13.78 ± 0.94 s, and 35.98 ± 3.24, 33.62 ± 2.49 s, respectively. Using ANOVA, there was a statistical difference (P = 0.001) in the AT levels of the standard-risk (89.07 ± 14.26%) and high-risk groups (73.10 ± 12.35%). Using Pearson's correlation, there was a significant negative correlation between AT levels and CBF (r = −0.405). With the use of multiple regression, AT showed the highest predictive value for CBF (R2 = 0.155; P ≤ 0.001; F = 17.677). Conclusion: AT functional activity levels were reduced in the SCA group compared with the HbAA-matched controls.


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