Establishing Ghanaian Adult Reference Intervals For Hematological Parameters Controlling For Latent Anemia And Inflammation

INTERNATIONAL JOURNAL OF LABORATORY HEMATOLOGY(2020)

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摘要
Background In Ghana, diagnostic laboratories rely on reference intervals (RIs) provided by manufacturers of laboratory analyzers which may not be appropriate. This study aimed to establish RIs for hematological parameters in adult Ghanaian population. Methods This cross-sectional study recruited 501 apparently healthy adults from two major urban areas in Ghana based on the protocol by IFCC Committee for Reference Intervals and Decision Limits. Whole blood was tested for complete blood count (CBC) by Sysmex XN-1000 analyzer, sera were tested for iron and ferritin by Beckman-Coulter/AU480, for transferrin, vitamin-B12, and folate was measured by Centaur-XP/Siemen. Partitioning of reference values by sex and age was guided by "effect size" of between-subgroup differences defined as standard deviation ratio (SDR) based on ANOVA. RIs were derived using parametric method with application of latent abnormal values exclusion method (LAVE), a multifaceted method of detecting subjects with abnormal results in related parameters. Results Using SDR >= 0.4 as a threshold, RIs were partitioned by sex for platelet, erythrocyte parameters except mean corpuscular constants, and iron markers. Application of LAVE had prominent effect on RIs for majority of erythrocyte and iron parameters. Global comparison of Ghanaian RIs revealed lower-side shift of RIs for leukocyte and neutrophil counts, female hemoglobin and male platelet count, especially compared to non-African countries. Conclusion The LAVE effect on many hematological RIs indicates the need for deliberate secondary exclusion for proper derivation of RIs. Obvious differences in Ghanaian RIs compared to other countries underscore the importance of country-specific RIs for improved clinical decision-making.
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关键词
complete blood counts, iron markers, latent abnormal values exclusion method, latent anemia, multiple regression analysis, parametric method, SD-ratio
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