ArticlePloS one2024
A comparative study of blood cell count in four automated hematology analyzers: An evaluation of the impact of preanalytical factors.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Analytical and Clinical Performance of the Atellica HEMA 580 Haematology Analyzer: A Comparison With the ADVIA 2120i.International journal of laboratory hematology · 2026Article
- Hemocompatibility of Carbosilane Dendrimers as a Therapeutic siRNA Delivery System across Blood-Brain Barrier.ACS applied materials & interfaces · 2026Article
- Time stability of Intensive Care Infection Score (ICIS) as a cellular hematology biomarker for infection in critically ill patients.Scientific reports · 2026Article
- Targeting Monocytes and Their Derivatives in Ovarian Cancer: Opportunities for Innovation in Prognosis and Therapy.Cancers · 2026Review
- Impact of pre-analytical variables - temperature, agitation, storage duration, and blood-to-anticoagulant ratio - on complete blood count test reliability.Medicine and pharmacy reports · 2025Article
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14 authors.
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Abstract
Differential white blood cell counts are frequently used in diagnosis, patient stratification, and treatment selection to optimize therapy responses. Referral laboratories are often used but challenged with use of different hematology platforms, variable blood shipping times and storage conditions, and the different sensitivities of specific cell types. To extend the scientific literature and knowledge on the temporal commutability of blood samples between hematology analyzers, we performed a comparative ex-vivo study using four of the most utilized commercial platforms, focusing on the assessment of eosinophils given its importance in asthma management. Whole blood from healthy volunteers with and without atopy (n = 6+6) and participants with eosinophilic asthma (n = 6) were stored under different conditions (at 4, 20, 30, and 37°C, with or without agitation) and analyzed at different time points (3, 6, 24, 48 and 72h post-sampling) in parallel on the Abbott CELL-DYN Sapphire, Beckman Coulter DxH900, Siemens ADVIA 2120i and Sysmex XN-1000V. In the same blood samples, eosinophil-derived neurotoxin (EDN), eosinophil activation and death markers were analyzed. All platforms gave comparable measurements of cell differentials on fresh blood within the same day of sampling. However, by 24 hours, significant temporal and temperature-dependent differences were observed, most markedly for eosinophils. None of the platforms performed perfectly across all temperatures tested during the 72 hours, showing that handling conditions should be optimized depending on the cell type of interest and the hematology analyzer. Neither disease status (healthy vs. asthma) nor agitation of the sample affected the cell quantification result or EDN release. The eosinophil activation markers measured by flow cytometry increased with time, were influenced by temperature, and were higher in those with asthma versus healthy participants. In conclusion, hematology analyzer, time window from sampling until analysis, and temperature conditions must be considered when analyzing blood cell differentials, particularly for eosinophils, via central labs to obtain counts comparable to the values obtained in freshly sampled blood.
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