质量控制规则的诊断准确性 质量控制规则的诊断准确性
Arne Åsberg1, Bjørn Johan Bolann2,3
1Department of Clinical Chemistry, St. Olav's Hospital, Trondheim, Norway.
概括
临床化学的质量控制规则可以使用ROC曲线进行优化. 使用N=2的平均规则优于Westgard规则,减少虚假报警并改善错误检测,以提高患者安全.
科学领域:
- 临床化学 临床化学
- 实验室质量控制和控制
- 统计过程控制 统计过程控制
背景情况:
- 临床化学实验室的内部质量控制 (IQC) 依赖于控制材料来监测分析性能.
- 质量控制规则用于解释控制结果和检测系统错误,旨在实现高错误检测概率 (Ped) 和低错误拒绝概率 (Pfr).
研究的目的:
- 通过改变控制极限,将质量控制规则表示为接收器操作特征 (ROC) 曲线上的点.
- 引入一种新的方法来选择最佳控制极限,类似于诊断测试ROC分析.
- 使用ROC曲线分析,将平均值规则与Westgard规则的性能进行比较.
主要方法:
- 使用ROC曲线分析质量控制规则,绘制Ped与Pfr的图形,控制限制有所变化.
- 提出了一个最佳控制限值选择的决策框架,考虑了预测错误概率,检测益处和错误报警成本.
- 对N=2的平均值规则和Westgard规则之间的性能比较是通过ROC曲线分析和Max E (NUF) 的评估进行的.
主要成果:
- ROC曲线分析表明,平均规则 (N=2) 优于Westgard规则,因为它们的ROC曲线位于Westgard规则的上方.
- 与可比的Westgard规则相比,平均规则在失控条件下 (Max E(NUF)) 显示了不可接受的患者结果的最大预期增加较低.
结论:
- ROC曲线分析为评估和优化临床化学质量控制规则提供了强大的框架.
- 使用N=2的平均规则在错误检测和最小化失控事件对患者结果的影响方面,比Westgard规则提供更高的性能.
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