Bennett S T, Connelly D P, Eckfeldt J H
Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis 55455.
Clin Chem. 1991 Apr;37(4):497-503.
We developed a computer model to study the use of patients' specimens to assess compliance of cholesterol measurement performance with the 1992 goals of the Laboratory Standardization Panel of the National Cholesterol Education Program. The model uses Monte Carlo techniques to simulate cholesterol measurements that are subject to both systematic and random error. Split-sample measurements by a clinical laboratory and by a reference laboratory are compared by using linear regression to estimate clinical laboratory bias and imprecision; subsequently, according to specified decision limits, the performance of the clinical laboratory is classified as acceptable or deficient. We have quantified the influence of the bias and imprecision of the clinical laboratory, the imprecision of the reference laboratory, the number of split samples compared, and the decision limits on the accuracy of the classification of clinical laboratory performance. Unless the decision limits are carefully selected and a sufficient number of split samples are used, clinical laboratory performance will be frequently misclassified.
我们开发了一种计算机模型，以研究使用患者标本评估胆固醇测量性能是否符合国家胆固醇教育计划实验室标准化小组1992年目标的情况。该模型采用蒙特卡罗技术模拟受系统误差和随机误差影响的胆固醇测量。通过使用线性回归来估计临床实验室的偏差和不精密度，比较临床实验室和参考实验室的分样测量结果；随后，根据指定的决策限，将临床实验室的性能分类为可接受或不足。我们已经量化了临床实验室的偏差和不精密度、参考实验室的不精密度、所比较的分样数量以及决策限对临床实验室性能分类准确性的影响。除非仔细选择决策限并使用足够数量的分样，否则临床实验室性能将经常被错误分类。
