检验医学 ›› 2015, Vol. 30 ›› Issue (3): 243-246.DOI: 10.3969/j.issn.1673-8640.2015.03.010

• 临床应用研究·论著 • 上一篇    下一篇

迈瑞CAL 8000血液分析流水线自动审核规则的制定与评价

魏坚, 王剑飚, 宋卫星, 陈骊婷, 石厚荣, 董淑贞, 陆盈   

  1. 上海交通大学医学院附属瑞金医院检验科,上海 200025
  • 收稿日期:2014-11-11 出版日期:2015-03-30 发布日期:2015-04-16
  • 作者简介:null

    作者简介:魏 坚,男,1980年生,主管技师,主要从事血细胞形态学检查。

Automatic verification procedure and evaluation of Mindray CAL 8000 auto sample processing line

WEI Jian, WANG Jianbiao, SONG Weixing, CHEN Liting, SHI Hourong, DONG Shuzhen, LU Ying   

  1. Department of Clinical Laboratory, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
  • Received:2014-11-11 Online:2015-03-30 Published:2015-04-16

摘要: 目的

制定深圳迈瑞CAL 8000血液分析流水线(简称CAL8000)自动审核规则,并对自动审核系统进行验证。

方法

选取1 025份乙二胺四乙酸二钾(EDTA-K2)抗凝的静脉全血标本,在CAL 8000上进行检测并对所有标本进行人工镜检,根据仪器检测结果及人工镜检结果对自动审核规则草案进行评估,另选取40 198份标本结果使用自动审核软件(LabXpert)进行样本审核,统计自动审核通过率及没有通过自动审核的样本构成;对比1 000份样本采用自动审核软件对样本审核与全部采用人工审核的报告时间。

结果

通过检测1 025份标本,其0.78%的假阴性低于国际血液学复检专家组要求的5%的最大允许范围。其假阴性主要集中于红细胞形态、血小板聚集及中性粒细胞中毒颗粒3个项目。用自动审核软件对40 198份标本结果进行分析,自动审核通过的标本占65.3%,需人工审核确认的占34.7%,需人工审核确认的样本主要包括:血小板(PLT)超范围、白细胞(WBC)超范围、血液科患者、未成熟粒细胞报警提示、红细胞(RBC)及平均RBC体积(MCV)超范围、原始细胞报警提示及血红蛋白(Hb)超范围等情况。

结论

采用自动审核软件对样本审核可以保证较低的假阴性率,减少差错,大大提高检验医生的工作效率,也可以大大缩短报告时间,提高了患者的满意度。

关键词: 血液细胞分析流水线, 自动审核, 规则

Abstract: Objective

To establish the automatic verification rules and validate the automatic verification system of Mindray CAL 8000 auto sample processing line.

Methods

1 025 EDTA-K2 anti-coagulated venous whole-blood samples were collected from Ruijin Hospital(including outpatient and inpatient samples). Each sample was both analyzed on the analyzer in CAL 8000 auto sample processing line and performed manual differential. The analysis results and microscopic results were used to evaluate the drafted automatic verification rules. Furthermore, 40198 outpatient and inpatient sample results obtained from March to May in 2014 were used as experimental data by Mindray automatic verification software(LabXpert), where the percentage of samples passing the automatic verification was obtained and the samples failing in the verification were categorized. A comparison of verification time using the software and in manual way was also performed.

Results

The false negative percentage of 1 025 samples tested was 0.78%, lower than the 5% required by the International Hematology Consensus Group. The false negative items mainly included erythrocyte morphology, platelet clump and toxic granules of neutrophils. By analysis of the 40 198 samples using the automatic verification software, 65.3% samples need automatic verification, and 34.7% need manual verification. Samples requiring manual verification included: PLT out-of-range samples, WBC out-of-range samples, samples from hematology department, samples with immature granulocyte flag, RBC and MCV out-of-range samples, samples with blast cell flag, HGB out-of-range samples, etc.

Conclusions

Using the automatic verification software increases clinical work efficiency, decreases false negative ratio, saves the report time and improves the patients' satisfaction.

Key words: Auto sample processing line, Automatic verification, Rule

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