Sysmex XN 系列血液分析仪上的微红细胞、碎红细胞、血小板分布宽度、平均血小板体积和血小板-大细胞比可用于临床实践中的阻抗血小板计数反射测试。

IF 3.7 3区 医学 Q2 MEDICAL LABORATORY TECHNOLOGY Archives of pathology & laboratory medicine Pub Date : 2024-01-01 DOI:10.5858/arpa.2022-0030-OA
Si Chen, Zhigang Mao, Shuang Wang, Jiamin Deng, Hongyan Liao, Qin Zheng
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引用次数: 0

摘要

背景:血小板(PLT)阻抗计数法(PLT-I)被广泛使用,但特异性较低。Sysmex XN 系列测试的荧光血小板计数法(PLT-F)具有很高的特异性,可以作为 PLT-I 的补充方法:确定作为 PLT-I 潜在影响因素的红细胞(RBC)和 PLT 相关参数,并建立 PLT-F 的 PLT 反射检验规则:我们对所有 3480 份样本中的 PLT-I 和 PLT-F 进行了前瞻性测试。在 3000 份样本的开发数据集中,比较了反射组和非反射组之间的差异,并通过逻辑回归确定了 PLT-I 的影响因素。通过 ROC 曲线分析得出接收者操作特征曲线下面积和临界值。对剩余的 480 份样本(验证数据集)进行了验证:PLT-F与免疫血小板计数结果相当。在逻辑回归中,微小红细胞绝对计数(micro-RBC#)、碎小红细胞绝对计数(FRC#)、PLT 分布宽度(PDW)、PLT 平均体积(MPV)、PLT-大细胞比值(P-LCR)和未成熟 PLT 部分绝对计数(IPF#)的增加是 PLT-I 的影响因素。在 ROC 曲线分析中,micro-RBC#、FRC#、PDW、MPV 和 P-LCR 的临界值分别为 0.64 × 106/μL、0.082 × 106/μL、15.40 fL、11.15 fL 和 33.95%。微量 RBC# 和 FRC# 的 ROC 曲线下面积分别为 0.77 和 0.79:结论:微RBC#、FRC#、PDW、MPV、P-LCR和IPF#是影响PLT-I的因素。其中,微RBC#和FRC#是影响最大的因素。从我们的研究结果来看,在临床工作中,微RBC#、FRC#、MPV、PDW和P-LCR可用于建立PLT计数的反射测试规则。
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Micro-Red Blood Cell, Fragmented Red Blood Cell, Platelet Distribution Width, Mean Platelet Volume, and Platelet-Large Cell Ratio on Sysmex XN Series Hematology Analyzers Can Be Used for the Reflex Test of Impedance Platelet Count in Clinical Practice.

Context.—: Platelet (PLT) counting with impedance (PLT-I) is widely used but has low specificity. PLT counting with fluorescence (PLT-F), tested by the Sysmex XN series with high specificity, can be a complementary method to PLT-I.

Objective.—: To identify red blood cell (RBC)- and PLT-related parameters as potential influencing factors for PLT-I and establish PLT reflex test rules with PLT-F.

Design.—: We prospectively tested both PLT-I and PLT-F in all 3480 samples. In a development data set of 3000 samples, differences between the reflex and nonreflex groups were compared and influencing factors for PLT-I were identified by logistic regression. The area under the receiver operating characteristic (ROC) curve and cutoff values were obtained by ROC curve analysis. Validation was conducted in the remaining 480 samples (validation data set).

Results.—: PLT-F showed comparable results with immunoplatelet counting. In logistic regression, increased micro-RBC absolute count (micro-RBC#), fragmented RBC absolute count (FRC#), PLT distribution width (PDW), mean PLT volume (MPV), PLT-large cell ratio (P-LCR), and immature PLT fraction absolute count (IPF#) were influencing factors for PLT-I. In ROC curve analysis, the cutoff values of micro-RBC#, FRC#, PDW, MPV, and P-LCR were 0.64 × 106/μL, 0.082 × 106/μL, 15.40 fL, 11.15 fL, and 33.95%, respectively. The areas under the ROC curve of micro-RBC# and FRC# were 0.77 and 0.79, respectively.

Conclusions.—: Micro-RBC#, FRC#, PDW, MPV, P-LCR, and IPF# were factors affecting PLT-I. Among them, micro-RBC# and FRC# were the most impactful factors. From our study results, micro-RBC#, FRC#, MPV, PDW, and P-LCR can be used to establish reflex test rules for PLT counting in clinical work.

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来源期刊
CiteScore
9.20
自引率
2.20%
发文量
369
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期刊介绍: Welcome to the website of the Archives of Pathology & Laboratory Medicine (APLM). This monthly, peer-reviewed journal of the College of American Pathologists offers global reach and highest measured readership among pathology journals. Published since 1926, ARCHIVES was voted in 2009 the only pathology journal among the top 100 most influential journals of the past 100 years by the BioMedical and Life Sciences Division of the Special Libraries Association. Online access to the full-text and PDF files of APLM articles is free.
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