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ORIGINAL ARTICLE
Year : 2016  |  Volume : 3  |  Issue : 3  |  Page : 163-165

Correlates and predictors of frequency of blood transfusions among sickle cell anemia patients in a Tertiary hospital in Nigeria


Department of Haematology, Ahmadu Bello University Teaching Hospital, Zaria, Nigeria

Correspondence Address:
Sani Awwalu
Department of Haematology, Ahmadu Bello University Teaching Hospital, Zaria
Nigeria
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DOI: 10.4103/2384-5147.190861

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Context: Blood transfusion is a central modality in the management of sickle cell anemia (SCA) patients. However, blood remains relatively scarce and the provision of safe, adequate, and timely transfusion services is still a challenge in Nigeria. Aims: To determine correlates and predictors of frequency of blood transfusions in SCA patients. Settings and Design: A cross-sectional, descriptive study was conducted. Convenience sampling technique was used to recruit 51 SCA patients attending the sickle cell clinic of ABUTH, Zaria Nigeria. Subjects and Methods: Age, sex, hematocrit, reticulocyte percentage, and 12-month recall of number of blood transfusions, pain episodes, and hospital admissions were assessed. Data were analyzed using SPSS version 20.0. Statistical Analysis Used: Results were summarized as median (interquartile range [IQR]) or mean ± standard deviation (SD). Spearman correlation and multiple regression analyses were carried out. Level of significance was set at P < 0.05. Results: Out of the 51 participants, 40 (78.43%) were females. The median (IQR) for age, number of pain episodes, number of hospital admissions, number of blood transfusions, and reticulocyte percentage was 23.00 (9.00) years, 2.00 (5.00), 0.00 (1.00), 0.00 (1.00), 8.60% (3.10%), respectively. Mean ± SD for hematocrit was 0.23 ± 3.41 L/L. Using frequency of blood transfusions as a reference, Spearman correlation analyses were performed for age (ρ = 0.206, P = 0.148), pain episodes (ρ = 0.270, P = 0.055), hospital admissions (ρ = 0.373, P = 0.007), hematocrit (ρ = 0.055, P = 0.704), and reticulocyte percentage (ρ = 0.122, P = 0.395). Backward multiple regression model to predict frequency of blood transfusions produced: F (2, 48) = 11.780, P < 0.001, adjusted R2 = 0.301. Only number of hospital admissions added statistically significant to the prediction (β = 0.542, P ≤ 0.001). Conclusions: Number of hospital admissions predicted frequency of blood transfusions in SCA patients in this study.


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