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首页> 外文期刊>Clinical Chemistry: Journal of the American Association for Clinical Chemists >Some Theory of Reference Values. I. Stratified (Categorized) Normal Ranges and a Method for Following an Individual's Clinical Laboratory Values
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Some Theory of Reference Values. I. Stratified (Categorized) Normal Ranges and a Method for Following an Individual's Clinical Laboratory Values

机译:参考价值的一些理论。 I.分层(分类)正常范围和遵循个人临床实验室值的方法

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The conventional population-based normal range has recently been shown to be a generally defective reference criterion for assessing individual laboratory test results. Applying a previously derived formula to published data, we find that the use of age-, sex-specific normal ranges may fail to produce a substantial improvement in sensitivity over nonspecific ranges, even when age-sex differences in mean values are statistically significant. This occurs when the difference in means is not accompanied by a sufficient reduction in the variation among individuals within a given class. Turning therefore to comparison of an individual's current measurement with his own previous value(s), I suggest a simple statistical model that leads to sequential testing of each new observation against an exponentially weighted moving average of previous results. Estimates of biological and analytical components of variance are required. The ability of this method to detect trends in very short series is explored with the aid of computer-simulated laboratory data. A sample of these data is also used to illustrate the application of these estimation and testing procedures by means of a graph.
机译:最近已经显示,常规的基于人群的正常范围是评估单个实验室测试结果的普遍有缺陷的参考标准。将先前导出的公式应用于已发布的数据,我们发现使用年龄,性别特定的正常范围可能无法在非特定范围内产生灵敏度上的显着提高,即使年龄性别平均值的平均值具有统计学意义。当均值差异没有伴随着给定类别内个体之间差异的充分减少时,就会发生这种情况。因此,将个人当前测量值与自己先前的值进行比较时,我建议使用一个简单的统计模型,该模型可以针对每个新观察结果与先前结果的指数加权移动平均值进行顺序测试。需要估算方差的生物学和分析成分。借助计算机模拟的实验室数据,探索了这种方法在非常短的序列中检测趋势的能力。这些数据的样本还用于通过图表说明这些估计和测试过程的应用。

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