解释来自同一个人的一个分析物的两个测试结果,使用双变量参考值
Arne Åsberg1, Gunhild Garmo Hov1,2, Gustav Mikkelsen1,2
1Department of Clinical Chemistry, St. Olav's Hospital, Trondheim, Norway.
概括
通过使用双变量参考限值,可以改进对联患者测试结果 (x1,x2) 的解释. 这种新的方法提供了一个更准确的患者健康状况的评估与传统的单变参考限值 (RLs) 和参考变化值 (RCVs) 相比.
科学领域:
- 临床化学 临床化学
- 生物统计学 生物统计学
- 医学诊断 医学诊断 医学诊断
背景情况:
- 医生经常解释同一患者的连续测试结果,将其与无变参考限值 (RL) 和参考变化值 (RCV) 进行比较.
- 当前的方法可能无法完全捕捉几天或几周间隔的对测量 (x1,x2) 之间的关系.
研究的目的:
- 引入和评估一种新的双变量方法,用于解释患者对联分析物测量 (x1,x2).
- 为了比较双变百分位数与传统单变参考限值和参考变化值的有效性.
主要方法:
- 模拟的双变量参考值 (x1,x2) 使用RLs,个体内生物变量和分析变量的数据.
- 在模拟的参考分布中使用Mahalanobis距离 (MDs) 估计的双变百分位数.
- 对比了双变百分位数的覆盖率,其中95%的RL和95%的RCV相结合.
主要成果:
- 95%的RL和95%的RCV的组合未能包含超过第95个双变百分点的参考值.
- 这种传统方法只包含了92%到93%的基准值,低于双变的第95百分位数.
- 两变百分位数可以从对测量的可用数据中得出.
结论:
- 双变百分位为解释对患者测试结果 (x1,x2) 提供了更准确的方法.
- 这种从健康的参考人群中得出的方法,可以改善连续实验室发现的报告和解释.
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