Comment on “Reference Intervals of Hematological Parameters Among Healthy Adults in Northern Sudan: A Community‐Based Cross‐Sectional Study”

We read with great interest the study by Lutfi et al., which represents the first region-specific attempt to establish hematological reference intervals (RIs) in Northern Sudan [1]. The authors' rigorous field-based methodology and stratification by gender within a reasonably powered sample is commendable. However, several analytical, interpretive, and generalizability-related issues warrant attention. First, while the study adhered to the Clinical and Laboratory Standards Institute (CLSI) recommendations for a minimum of 120 participants per subgroup, no power calculation was presented to justify the sufficiency of subgroup-specific sample sizes (e.g., females, n = 112). Considering that the study also conducted gender-wise comparisons for 13 hematological indices, the absence of a Bonferroni correction or other method to adjust for multiple comparisons increases the risk of Type I error [2]. This is particularly concerning, given the borderline significance of several findings (e.g., PDW: p = 0.021; MPV: p = 0.021). Second, the use of the Mann–Whitney U test to compare medians was appropriate due to non-normal data distribution. However, the authors did not explore potential confounding factors that could influence hematological values, such as BMI, marital status, educational attainment, or occupational status [3-5], variables that were collected but not statistically modeled. Multivariable regression or stratified analyses could offer more nuanced insights, particularly given the observed sociodemographic heterogeneity. Third, while the study excluded individuals with chronic illnesses and recent infections, reliance solely on self-report and observational screening without confirmatory laboratory diagnostics (e.g., stool microscopy for helminths, serum ferritin for iron status, and hemoglobin electrophoresis for hemoglobinopathies) raises concerns about subclinical confounders. Given the high endemicity of iron-deficiency anemia and sickle cell trait in Northern Africa [6], the established RIs may have inadvertently incorporated pathological values, thereby underestimating true physiological norms. Fourth, the study's comparison with previous RI studies from other Sudanese regions and neighboring countries offers a useful context but fails to systematically account for methodological heterogeneity. For instance, variations in analyzer types, calibration standards, sample handling time, and altitude-related hypoxia could significantly impact parameters such as hemoglobin and RBC count [7]. Without standardizing these variables, direct cross-country RI comparisons may yield misleading conclusions. Fifth, the inclusion of only one district (Wad Hamid) restricted extrapolation. The authors correctly noted ethnic and environmental diversity across the River Nile, but the study's design did not capture this intra-regional variability. Furthermore, the absence of age-stratified RIs, despite collecting continuous age data, limits its utility for clinical interpretation in older or younger adult subgroups. Finally, although gender differences in hematological parameters were statistically significant, their clinical relevance remained ambiguous. For example, the hemoglobin median for males (14.1 g/dL) and females (12.5 g/dL) is within widely accepted normal ranges, yet the lack of discussion regarding diagnostic thresholds or misclassification risks reduces translational value. In summary, while this study offers foundational regional data, future research should incorporate broader sampling frames, biochemical validation for subclinical conditions, confounder-adjusted modeling, and age-specific RIs. These enhancements could substantially improve the clinical applicability of hematological benchmarks in Northern Sudan and facilitate their integration into national diagnostic protocols. Rachana Mehta: writing – original draft, writing – review and editing. Ranjana Sah: conceptualization, methodology, validation, supervision, project administration, writing – original draft, writing – review and editing. Generative AI tools, including Paperpal and ChatGPT-4o, were utilized solely for language, grammar, and stylistic refinement. These tools had no role in the conceptualization, data analysis, interpretation of results, or substantive content development of this manuscript. All intellectual contributions, data analysis, and scientific interpretations remain the sole work of the authors. The final content was critically reviewed and edited to ensure accuracy and originality. The authors take full responsibility for the accuracy, originality, and integrity of the work presented. Not applicable as no patient data were collected or analyzed in this study. The authors declare no conflicts of interest. Not applicable, as no data were generated or analyzed in this study.