评估无宿主细胞(UGC):一种自动血细胞反衍生的新型红细胞研究参数,用于临床应用和诊断各种病理条件。

Anita Giri, Praveen Sharma, Dikshat Gopal Gupta, Minakshi Gupta, Pulkit Rastogi, Srinivasan Peyam, Aashima Arora, Alka Rani Khadwal, Elena Sukacheva, Prashant Sharma, Reena Das
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引用次数: 0

摘要

导言:自动化血液学分析仪对潜在细胞的自动估计仍然具有挑战性。据报道,Beckman Coulter UniCel DxH 800分析仪中的无宿主细胞(UGC)参数与靶细胞和其他红细胞渗透阻力增加的情况相关,如小细胞增多/低色素血症、镰状细胞和脾切除术后。我们在一个专业血液学实验室评估了UGCs的参考范围和潜在的临床应用。材料和方法:我们前瞻性地招募了520名参与者,包括健康个体(n = 45)、β-地中海贫血特征(n = 196)、血红蛋白病(n = 104)、缺铁性贫血(n = 88)、肝脏疾病(n = 46)、球形红细胞增生(n = 18)和新生儿脐带血样本(n = 23)。分析外周血EDTA样本。UGC数据与外周涂片结果相关。此外,我们还比较了包括UGC在内的红细胞参数,以区分β-地中海贫血性状(βTT)与缺铁。结果:UGCs在健康个体中检测不到或存在极低数量(范围为0%-0.01%)。它们与外周涂片上的人工靶细胞计数呈显著正相关(相关系数,r = 0.64, p)。结论:UGC%代表了一种创新的、自动化的血液学红细胞研究参数,能够筛选靶细胞并对其进行量化。UGC在以靶细胞为特征的各种疾病的临床诊断应用中显示出巨大的潜力,促进了临床实践中的鉴别诊断。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating Unghosted Cells (UGC): An Automated Blood Cell Counter-Derived Novel Red Cell Research Parameter for Its Clinical Utility and Diagnostic Implications Across a Spectrum of Pathological Conditions.

Introduction: Automated estimation of poikilocytes by automated hematology analyzers remains challenging. The unghosted cells (UGC) parameter in Beckman Coulter UniCel DxH 800 analyzers has been reported to correlate with target cells and other conditions with increased erythrocytic osmotic resistance like microcytosis/hypochromia, sickle cells, and post splenectomy. We assessed UGCs' reference range and potential clinical utility in a specialist hematology laboratory.

Materials and methods: We prospectively enrolled 520 participants, encompassing healthy individuals (n = 45), β-thalassemia trait (n = 196), hemoglobinopathies (n = 104), iron deficiency anemia (n = 88), liver disease (n = 46), spherocytosis (n = 18), and neonatal cord blood samples (n = 23). Peripheral blood EDTA samples were analyzed. UGC data were correlated with peripheral smear findings. In addition, red cell parameters including UGC were compared to differentiate β-thalassemia trait (βTT) from iron deficiency.

Results: UGCs were undetectable or present in very low numbers in healthy individuals (range 0%-0.01%). They demonstrated a significant positive correlation with manual target cell counts on peripheral smear (correlation coefficient, r = 0.64, p < 0.001). The highest UGC levels were observed in those with liver disease, with a median value of 0.395% (range: 0%-8.23%). All non-control subgroups, except for spherocytosis, showed significantly increased UGC% (p < 0.0001) vis-à-vis healthy individuals. A novel formula at a cut-off of 0.77 demonstrated 86.22% sensitivity and 93.10% specificity in differentiating βTT and IDA.

Conclusions: UGC% represents an innovative, automated hematological red cell research parameter capable of screening target cells and quantifying them. UGC shows significant potential for clinical diagnostic applications across a wide range of disorders characterized by target cells, facilitating differential diagnoses in clinical practice.

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