The significance of the coefficient of variation (CV) as a criterion for choosing an analytical system for immunochemical studies

The relevance of the study. In modern realities, Russian medical laboratories often get into a situation where there is a need to replace the analytical system due to a physical deterioration of the equipment or the analytical characteristics improvement, as well as medical devices out of stock [1]. Problems with delivery schedules and timely maintenance, or lack of finances lead to a situation to choose a new supplier of equipment and reagents. As a rule, the main comparison criterion is the cost of analysis in this case. It isn’t easy to determine the relationship between the analytical characteristics (trueness, accuracy, precision) presented by the manufacturer and risk for patient safety.
Objectives. The purpose of the study is to show the importance of precision in the risk of laboratory error, and also to develop a practical approach to use imprecision as a criterion for choosing an analytical system from the point of view of patient safety.
Materials and methods. The manufacturer’s characteristics of real analytical systems were used in the study. For the risks calculations, a mathematical model was developed that allows one to compare the tests imprecision and the expected number of unreal results in the period from the analytical system defect occurrence to the detection of it in the internal quality control (IQC) procedure.
Results. Mathematical modeling has shown that significant disfunction of the studied analytical systems, with a signal shift of 10 %, can be detected in the first control point after defect occurrence in 10–20 % of cases only. It means that the IQC procedure is able to identify an error with a delay of 1–2 weeks. During this time, unreliable results can be reported. The expected number of unreal results for some tests (FT3, FT4, Testosterone, 25-hydroxyvitamin D) can reach up to 50 % of all reported results.
Conclusions. The mathematical modeling in the analytical systems functionality estimation made it possible to calculate the risk of a laboratory error before their implementation in laboratory practice at the procurement planning stage, for example. Test CV published by the Manufacturer were successfully used as an evaluation criterion. The high imprecision of the tests may compromise the patients’ safety of their use.

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