Suppr超能文献

在临床实践中,利用迈瑞BC - 6800plus血液分析仪上的微量红细胞#、巨红细胞%、“血小板聚集?”标志和“血小板异常直方图”标志构建血小板计数光学方法反射测试规则。

Construction of platelet count-optical method reflex test rules using Micro-RBC#, Macro-RBC%, "PLT clumps?" flag, and "PLT abnormal histogram" flag on the Mindray BC-6800plus hematology analyzer in clinical practice.

作者信息

Fei Yang, Xiong Zhi-Gang, Huang Liang, Zhang Chi

机构信息

Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Department of Blood Transfusion, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

出版信息

Clin Chem Lab Med. 2024 Sep 2. doi: 10.1515/cclm-2024-0739.

Abstract

OBJECTIVES

Utilizing RBC or PLT-related parameters to establish rules for the PLT-O reflex test can assist laboratories in quickly identifying specimens with interfered PLT-I that require PLT-O retesting.

METHODS

Prospective PLT-I and PLT-O testing was performed on 6857 EDTA-anticoagulated whole blood samples, split randomly into training and validation cohorts at a 2:3 ratio. Reflex and non-reflex groups were distinguished based on the differences between PLT-I and PLT-O results. By comparing RBC and PLT parameter differences and flags in the training set, we pinpointed factors linked to PLT-O reflex testing. Utilizing Lasso regression, then refining through univariate and multivariate logistic regression, candidate parameters were selected. A predictive nomogram was constructed from these parameters and subsequently validated using the validation set. ROC curves were also plotted.

RESULTS

Significant differences were observed between the reflex and non-reflex groups for 19 parameters including RBC, MCV, MCH, MCHC, RDW-CV, RDW-SD, Micro-RBC#, Micro-RBC%, Macro-RBC#, Macro-RBC%, MPV, PCT, P-LCC, P-LCR, PLR,"PLT clumps?" flag, "PLT abnormal histogram" flag, "IDA Anemia?" flag, and "RBC abnormal histogram" flag. After further analysis, Micro-RBC#, Macro-RBC%,"PLT clumps?", and "PLT abnormal histogram" flag were identified as candidate parameters to develop a nomogram with an AUC of 0.636 (95 %CI: 0.622-0.650), sensitivity of 42.9 % (95 %CI: 37.8-48.1 %), and specificity of 90.5 % (95 %C1: 89.6-91.3 %).

CONCLUSIONS

The established rules may help laboratories improve efficiency and increase accuracy in determining platelet counts as a supplement to ICSH41 guidelines.

摘要

目的

利用红细胞(RBC)或血小板(PLT)相关参数建立血小板光学法复检(PLT-O)的规则,可帮助实验室快速识别血小板阻抗法检测结果(PLT-I)受干扰且需要进行PLT-O复检的标本。

方法

对6857份乙二胺四乙酸(EDTA)抗凝全血样本进行前瞻性PLT-I和PLT-O检测,按2:3的比例随机分为训练组和验证组。根据PLT-I和PLT-O结果的差异区分复检组和非复检组。通过比较训练集中红细胞和血小板参数差异及标记,确定与PLT-O复检相关的因素。利用套索回归,再经单因素和多因素逻辑回归进行优化,选择候选参数。根据这些参数构建预测列线图,随后用验证组进行验证。还绘制了受试者工作特征(ROC)曲线。

结果

在红细胞、平均红细胞体积(MCV)、平均红细胞血红蛋白含量(MCH)、平均红细胞血红蛋白浓度(MCHC)、红细胞分布宽度变异系数(RDW-CV)、红细胞分布宽度标准差(RDW-SD)、小红细胞数量(Micro-RBC#)、小红细胞百分比(Micro-RBC%)、大红细胞数量(Macro-RBC#)、大红细胞百分比(Macro-RBC%)、平均血小板体积(MPV)、血小板压积(PCT)、血小板低荧光强度群(P-LCC)、血小板低荧光强度比率(P-LCR)、血小板比率(PLR)、“血小板聚集?”标记、“血小板异常直方图”标记、“缺铁性贫血?”标记及“红细胞异常直方图”标记等19个参数方面,复检组和非复检组间存在显著差异。进一步分析后,确定小红细胞数量、大红细胞百分比、“血小板聚集?”及“血小板异常直方图”标记为候选参数,用于构建列线图,其曲线下面积(AUC)为0.636(95%置信区间:0.622 - 0.650),灵敏度为42.9%(95%置信区间:37.8 - 48.1%),特异性为90.5%(95%置信区间:89.6 - 91.3%)。

结论

所建立的规则可能有助于实验室提高效率,并在确定血小板计数方面提高准确性,作为对国际血液学标准化委员会(ICSH)41指南的补充。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验