https://doi.org/10.65770/IAXI9244
ABSTRACT
Sickle cell disease (SCD) is characterized by chronic hemolysis, persistent inflammatory activation, and recurrent vaso-occlusive events. These pathophysiological processes are reflected in routinely available hematological indices, yet their integrated behavior across clinical states remains incompletely defined. This hospital-based cross-sectional study evaluated platelet count, total white blood cell (WBC) count, and reticulocyte percentage in individuals with confirmed SCD and apparently healthy controls. Patients were further categorized as being in steady state or vaso-occlusive crisis. Comparative analyses were conducted using appropriate parametric or non-parametric tests, with effect sizes and 95% confidence intervals reported. Steady-state SCD patients demonstrated significantly higher platelet counts, WBC counts, and reticulocyte percentages compared with controls (all p < 0.001), with large to very large effect sizes. These parameters were further amplified during crisis, revealing a consistent stepwise gradient from health to steady-state disease and acute exacerbation (overall p < 0.001). Platelet count showed a significant positive correlation with reticulocyte percentage, whereas its association with total WBC count was not statistically significant. The observed hematological gradient supports the conceptualization of SCD as a dynamic thromboinflammatory continuum rather than a static hematologic disorder. Marked reticulocytosis during crisis reflects intensified hemolytic stress, while concurrent leukocytosis and thrombocytosis indicate amplified inflammatory and adhesive activation. Although the crisis subgroup was limited in size, the internal consistency of findings across analytical approaches supports their biological plausibility. These results highlight the potential utility of routine hematological parameters as accessible indicators of disease activity, particularly in resource-constrained settings. Larger longitudinal studies incorporating treatment stratification and expanded biomarker profiling are needed to refine prognostic applications in sickle cell disease.
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