检验医学 ›› 2021, Vol. 36 ›› Issue (6): 667-673.DOI: 10.3969/j.issn.1673-8640.2021.06.019

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相对变化值参考区间新算法的建立及应用评价

岳波, 李丹杰, 唐大海(), 刘曼娇, 贺嘉蕾, 蒋梦洁, 韦晓强   

  1. 上海长海医院虹口院区检验科,上海 200081
  • 收稿日期:2020-07-06 出版日期:2021-06-30 发布日期:2021-06-30
  • 通讯作者: 唐大海
  • 作者简介:唐大海,E-mail:tdh863@163.com
    岳 波,男,1984年生,主管技师,主要从事疾病的筛查与智能诊断研究。
  • 基金资助:
    上海市卫生和计划生育委员会资助项目(20164Y0246)

Establishment of a new algorithm for the reference interval of relative change values and application evaluation

YUE Bo, LI Danjie, TANG Dahai(), LIU Manjiao, HE Jialei, JIANG Mengjie, WEI Xiaoqiang   

  1. Department of Clinical Laboratory,Hongkou Hospital of Changhai Hospital of Shanghai,Shanghai 200081,China
  • Received:2020-07-06 Online:2021-06-30 Published:2021-06-30
  • Contact: TANG Dahai

摘要:

目的 建立相对变化值参考区间(RCV)的新算法,并评价其应用价值。方法 利用相对变化值(ΔR)与波动性(λ)之间的关系,基于蒙特卡洛法,通过Excel 2007软件建立相关大数据模型,分析λ、ΔR的分布特点及其与变异系数(CV)的关系,最后建立RCV的新算法。采用新算法重新计算既往文献报道中RCV应用实例的数据,比较新算法与传统算法的计算结果。结果 λ呈正偏态分布,取对数后呈中心对称分布,当CV≤9.5%时,λ近似呈对数正态分布;ΔR分布的形状与λ相同,位置相对于λ向左平移“1”;RCV可由CV经新算法得出;当CV较大时,新算法与传统算法之间差异显著。结论 建立了RCV新算法,比传统算法更具科学性,有助于RCV的临床应用;剖析了波动性参考区间、RCV、CV三者之间的相互关系,通过新算法,三者可以相互转换。

关键词: 参考变化值, 变异系数, 波动性, 参考区间

Abstract:

Objective To establish and apply a new algorithm for the reference interval of relative change values(RCV). Methods Based on the relationship between the relative change values(ΔR) and the fluctuation(λ),a related big datum model was established by Excel 2007,and the distribution characteristics of λ and ΔR and the relationship with coefficient of variation(CV) were analyzed. Finally,the algorithm of RCV was established. RCV data in previous literature reports were recalculated using this algorithm and compared with traditional algorithms. Results λ was positively skewed,and its logarithm was center-symmetrically distributed. When CV≤9.5%,λ was approximately log-normally distributed. The shape of ΔR distribution was the same as that of λ,and the position was shifted "1" to the left relative to λ. RCV could be derived from CV through this algorithm. Compared with traditional algorithms,when CV was larger,the difference between the 2 algorithms was significant. Conclusions This study establishes a new algorithm for RCV. Compared with traditional algorithms,this algorithm is more scientific and helpful for the clinical popularization and the application of RCV. This study analyzes the relationship between the fluctuation reference interval,RCV and CV through the algorithm,and these 3 factors could be converted to each other.

Key words: Reference change value, Coefficient of variation, Fluctuation, Reference interval

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