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BACKGROUNDIt is important for a laboratory to know the stability of performance of laboratory tests over time. The aim of this study was to adapt from the field of clinical chemistry a method to assess the long-term analytical performance of hemostasis field methods.METHODSThe linear regression model was used to compare the laboratory results with the consensus mean value of a survey. This model was applied to plasma antithrombin activity using the data for 82 laboratories, collected between 1996 and 1999 in the European Concerted Action on Thrombosis (ECAT) external quality assessment program. The long-term total, random, and systematic error were calculated. The variables introduced to define the long-term performance in this model were the long-term analytical CV (LCV(a)) and the analytical critical difference (ACD), which indicates the minimum difference necessary between two samples measured on a long-term time-scale to consider them statistically significantly different.RESULTSThe systematic error (bias) ranged from 4.5 to 103 units/L. The random error ranged from 24.4 to 242 units/L. For the majority of the laboratories, random error was the main component (>75%) of the total error. The LCV(a), after adjustment for the contribution of the bias, ranged from 2.8% to 48%. The ACD ranged from 78 to 1290 units/L with a median value of 190 units/L. No statistically significant differences were observed for either LCV(a) or ACD between the two different measurement principles for antithrombin activity based on the inhibition of either thrombin or factor Xa.CONCLUSIONSThis linear regression model is useful for assessing the total error, random error, and bias for hemostasis field methods. The LCV(a) and ACD for measurement on a long-term time-scale appear to be useful for assessing the long-term analytical performance.

clinical chemistry

Long-Term Analytical Performance of Hemostasis Field Methods as Assessed by Evaluation of the Results of an External Quality Assessment Program for Antithrombin