Preanalytical variation

In the theory on uncertainty, a distinction between type A and B uncertainties is made. Type A uncertainties are frequency-based estimates of standard deviations (e.g, an SD of the imprecision). Type B uncertainties are uncertainty components for which frequency-based SDs are not available. Instead, the uncertainty is estimated by other approaches or by the opinion of experts. Finally the total uncertainty is derived from a combination of all sources of uncertainty. In this context, it is practical to operate with standard uncertainties (w t), which are equivalent to standard deviations. By multiplication of a standard uncertainty with a coverage factor (k), the uncertainty corresponding to a specified probability level is derived. For example, multiplication with a coverage factor of two yields a probability level of 95% given a normal distribution. When considering the total uncertainty of an analytical result obtained by a routine method, the preanalytical variation, method imprecision, random matrix-related interferences, and uncertainty related to calibration and bias corrections (traceability) should be taken into account. Expressing the uncertainty components as standard uncertainties, we have the general relation ... 

SDp — Standard deviation of preanalytical variation SDa = Standard deviation of analytical variation SDj = Standard deviation of within individual biological variation... 

It is possible to substitute the coefficient of variation for the standard deviation in the above equation. If the conditions of patient preparation, sample collection, and sample handling are standardized, preanalytical variation is minimized and the total variation is then determined by the combined influence of the analytical and intraindividual variations, thus ... 

Antonsen S. The estimation of biological and preanalytical variations of inflammation markers. Scand J Clin Lab Invest Suppl 1994 219 55-60. 

Influence of analytical quality and preanalytical variations on measurements of cholesterol in screening programmes. Scand J Clin Lab Invest Suppl 1990 198 66-72. 

Templeton, D.M. (1993). Measurement of total nickel in body fluids Electrochemical atomic absorption methods and sources of preanalytic variation. Pure Appl. Chem. (In Press). 

Recommendations are that preanalytical conditions should be standardized, in order to minimize preanalytical variation... 

The human body is composed of many different compounds and elements the concentration or activities of these analytes are a reflection of the individual s health or pathophysiological state. However, both preanalytical variables and biological variation affect the concentration or activities of these analytes. ... 

Inherent in any reported laboratory test results on patients are influences of (1) biological variation, (2) inherent analytical error, (3) preanalytical and postanalytical sources of variation, and (4) possible pathophysiological alterations. When repeated measurements are made over time in one individual, even under standardized conditions, there is a considerable variability in the test results. The variability within the individual is attributable to both analytical and intraindividual factors but the intraindividual (within-subject) variability is typically less than the variability among a group of individuals. This means that when ana-... 

To determine what confidence should be placed in a test result it is useful to evaluate the variability of test values. The factors influencing a test value are preanalytical, analytical, and within an individual. As the sources of variation (squares of the standard deviations) are additive, the total variation (SDt) for any one laboratory result is... 

Statland BE, Winkel P. Effects of preanalytical factors on the intraindividual variation of analytes in the blood of healthy subjects Consideration of preparation of the subject and time of venipuncture. CRC Crit Rev Clin Lab Sci 1977 8 105-44. 

Agreement Between First and Second Measures Figure 26-30 With in-person variability comparison of hsCRP with total cholesterol (Ledue and Rifai 2003). (From Ledue TB, Rifai N. Preanalytic and analytic sources of variations in C-reactive protein measurement implications for cardiovascular disease risk assessment Clin Chem 2003 49 1258-71.)... 

Ledue T B, Rifai N. Preanalytic and analytic sources of variations in C-reactive protein measurement implications for cardiovascular disease risk assessment. Clin Chem 2003 49 1258-71. 

Introduction to Principles of Laboratory Analyses and Safety Introduction to Principles of Laboratory Analyses and Safety Appendix Specimen Collection and Processing Preanalytical Variables and Biological Variation... 

A number of preanalytical factors, including anesthetics, stress, dietary intakes, fluid intake, diurnal variation, and dark and light illumination cycles, are known to affect the electrolyte and related hormone measurement determinations. Therefore, these factors should be considered when interpreting these data. Plasma calcium and phosphate are subject to diurnal variation and may increase after feeding. 

Aktas, M., D. Auguste, P. Corcordet, P. Vinclair, H. Lefebvre, and P. L. Toutain. 1994. Creatine kinase in dog plasma Preanalytical factors of variations, reference values and diagnostic significance. Research in Veterinary Science 56 30-36. 

In general, the variations due to analytical components in clinical chemistry measurements usually are much less than variations due to the preanalytical factors. The... 

Variation in urinary iodine excretion is important because it influences the study of iodine nutrition. Urinary iodine excretion exhibits large variations. The components of variation include preanalytical, analytical and biological variations. Biological variation consists of between- and within-individual variations, and can be broken down into chronobiological variation, i.e., diurnal and seasonal variations, and variations related to dilution, dietary peculiarities and supplement use. This is important for the evaluation and planning of studies of iodine nutrition, and it can be calculated that 500 urine samples depict population iodine nutrition level within 5%, while 125 urine samples are required for a value of 10%. Estimating 24h urinary iodine excretion lowers variation, and consequently the number of urine samples needed is reduced by around 20%. Similarly, it can be calculated that less than 10—15 urine samples from an individual may be misleading. 

Variation will be lower with standardized preanalytical conditions, as found for urinary iodine in a slightly standardized study (Busnardo et ai, 2006) compared with the variation in nonstandardized urine collections (Rasmussen et al, 1999 Andersen et al, 2001). 

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