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Urine samples are frequently used in the clinical practice. In our study, we aimed to calculate the biological variations (BV) of analytes and analyte/creatinine ratios measured in spot urine. Second-morning spot urine samples were collected from 33 (16 female, 17 male) healthy volunteers once weekly for 10 weeks and analyzed in the Roche Cobas 6,000 instrument. Statistical analyzes were performed using BioVar, an online BV calculation software. The data were evaluated in terms of normality, outliers, steady state, homogeneity of the data, and BV values were obtained by analysis of variance (ANOVA). A strict protocol was established for within-subject (CVI) and between-subject (CVG) estimates for both genders. There was a significant difference between female/male CVI estimates of all analytes except potassium, calcium and magnesium. No difference was found in CVG estimates. When the analytes that had a significant difference in CVI estimates in spot urine analytes were compared to creatinine, it was observed that the significant difference between the genders disappeared. There was no significant difference between female/male CVI and CVG estimates in all spot urine analyte/creatinine ratios. Since the CVI estimates of analyte/creatinine ratios are lower, it would be more reasonable to use them in result reporting. Reference ranges should be used with caution, since II values of almost all parameters are between 0.6 and 1.4. The CVI detection power of our study is 1, which is the highest value. [ABSTRACT FROM AUTHOR]

Background: D-dimer increases during pregnancy and is problematic to use in the diagnosis of venous thromboembolism. Fibrin monomer represents an alternative biomarker for venous thromboembolism. However, to be useful in pregnancy, the fibrin monomer concentration should be stable throughout pregnancy and during postpartum. Methods: To describe the course of fibrin monomer concentration during pregnancy and the postpartum period in healthy pregnant women and to compare their within-subject biological variation (CVI) with non-pregnant women. Blood samples were obtained every fourth week during pregnancy and three samples after delivery in 20 healthy women and every fourth week during a 40-week period in 19 healthy non-pregnant women. Fibrin monomer (STA Liatest FM, Stago) was analysed in duplicates for all samples. Concentrations of fibrin monomer in pregnant and non-pregnant women were compared and the CVI for fibrin monomer was calculated. Results: The median fibrin monomer concentration in pregnant women was 6.2 mg/L (2.5 and 97.5 percentiles 3.7–10.8 mg/L) and in non-pregnant women 4.8 mg/L (3.6–8.2) (P < 0.01). The fibrin monomer concentration was relatively stable during pregnancy, although a few unexplained high fibrin monomer concentrations were found during pregnancy/postpartum. Fibrin monomer CVI in pregnancy and postpartum was 20.6% (95% CI 18.3, 23.5) and in non-pregnant 16.1% (13.7, 18.9). Conclusions: For clinical purposes, fibrin monomer concentration can be considered stable during pregnancy, although it is slightly higher than in non-pregnant women. Pregnant and non-pregnant women have the same CVI. The suitability of fibrin monomer in venous thromboembolism diagnosis in pregnant women should be validated in further studies. [ABSTRACT FROM AUTHOR]

Background The Enhanced Liver Fibrosis score has been recognized as a non-invasive test for liver fibrosis. However, reference intervals, biological variation and analytical performance have not been studied in detail so far. The aim was to acquire data that are essential for correct interpretation. Methods A total of 40 apparently healthy volunteers were evaluated for reference ranges of serum concentration of hyaluronic acid, aminoterminal propeptide of type III collagen, and tissue inhibitor of metalloproteases-1, and calculated ELF score. A subgroup of 20 subjects was evaluated repeatedly for 7 weeks. For all variables, reference intervals, within-subject and between-subject biological variations, reference change values, and the indexes of individuality were assessed. Analytical performance (intermediate precision) and interlaboratory comparison were also evaluated. Results The reference ranges were 5.1–62.7 μg/L for HA, 3.56–12.6 μg/L for PIIINP, 143.6–265.3 μg/L for TIMP-1, and 7.14–9.55 for the ELF score. The within-subject variations were 32.7, 10.6, 4.2, and 3.2% for HA, PIIINP, TIMP-1, and ELF score, respectively. Similarly, the between-subject variations were 59.0, 13.3, 12.8, and 5.2%. For the ELF score, RCV was 10.1% and II was 0.62. The intermediate precisions were <5%, <6%, and <10% for HA, PIIINP, and TIMP-1, respectively. Conclusion The reference range of the ELF score overlap with the area defined as moderate fibrosis by the manufacturer. High biological variation of HA was diminished by the natural logarithm in the calculation of the ELF score. The use of the ELF score has suitable analytical and acceptable biological performance characteristics for clinical practice. However, the transfer of results evaluated in healthy persons to the populations with chronic liver diseases deserves caution. [ABSTRACT FROM AUTHOR]

Background: During monitoring of monthly medians of results from patients undertaken to assess analytical stability in routine laboratory performance, the medians for serum sodium for male and female patients were found to be significantly related. Methods: Daily, weekly and monthly patient medians of serum sodium for both male and female patients were calculated from results obtained on samples from the population >18 years on three analysers in the hospital laboratory. The half-range of medians was applied as an estimate of the maximum bias. Further, the ratios between the two medians were calculated. Results: The medians of both genders demonstrated dispersions over time, but they were closely connected in like patterns, which were confirmed by the half-range of the ratios of medians for males and females that varied from 0.36% for daily, 0.14% for weekly and 0.036% for monthly ratios over all instruments. Conclusions: The tight relationship between the gender medians for serum sodium is only possible when raw laboratory data are used for calculation. The two patient medians can be used to confirm both and are useful as independent estimates of analytical bias during constant calibration periods. In contrast to the gender combined median, the estimate of analytical bias can be confirmed further by calculation of the ratios of medians for males and females. [ABSTRACT FROM AUTHOR]

Background The distributions of within-subject biological variation are usually described as coefficients of variation, as are analytical performance specifications for bias, imprecision and other characteristics. Estimation of specifications required for reference change values is traditionally done using relationship between the batch-related changes during routine performance, described as Δbias, and the coefficients of variation for analytical imprecision (CVA): the original theory is based on standard deviations or coefficients of variation calculated as if distributions were Gaussian. Methods The distribution of between-subject biological variation can generally be described as log-Gaussian. Moreover, recent analyses of within-subject biological variation suggest that many measurands have log-Gaussian distributions. In consequence, we generated a model for the estimation of analytical performance specifications for reference change value, with combination of Δbias and CVA based on log-Gaussian distributions of CVI as natural logarithms. The model was tested using plasma prolactin and glucose as examples. Results Analytical performance specifications for reference change value generated using the new model based on log-Gaussian distributions were practically identical with the traditional model based on Gaussian distributions. Conclusion The traditional and simple to apply model used to generate analytical performance specifications for reference change value, based on the use of coefficients of variation and assuming Gaussian distributions for both CVI and CVA, is generally useful. [ABSTRACT FROM AUTHOR]

In recent decades, the study of biological variation of laboratory analytes has received increased attention. The reasons for this interest are related to the potential practical applications of such knowledge. Biological variation data allow the derivation of important parameters for the interpretation and use of laboratory tests, such as the index of individuality for the evaluation of the utility of population reference intervals for the test interpretation, the estimate of significant change in a timed series of results of an individual, the number of specimens required to obtain an accurate estimate of the homeostatic set point of the analyte and analytical performance specifications that assays should fulfill for their application in the clinical setting. It is, therefore, essential to experimentally derive biological variation information in an accurate and reliable way. Currently, a dated guideline for the biological variation data production and a more recent checklist to assist in the correct preparation of publications related to biological variation studies are available. Here, we update and integrate, with examples, the available guideline for biological variation data production to help researchers to comply with the recommendations of the checklist for drafting manuscripts on biological variation. Particularly, we focus on the distribution of the data, an essential aspect to be considered for the derivation of biological variation data. Indeed, the difficulty in deriving reliable estimates of biological variation for those analytes, the measured concentrations of which are not normally distributed, is more and more evident. [ABSTRACT FROM PUBLISHER]

Background: Most of the factors causing preanalytical and analytical variation in ammonia measurement have been identified. Biological variation data for ammonia is still lacking. We therefore estimated the components of biological variation (within-subject=CVI and between-subject=CVG), reference change value (RCV) and quality specifications for ammonia in a group of healthy individuals using fresh and frozen plasma samples. Methods: Blood samples from 20 healthy subjects were collected in K2EDTA tubes daily over a period of 4 consecutive days from each subject. Each plasma sample was split into two aliquots; one was immediately analyzed as the samples were collected and the other was stored -80 °C until testing at the end of the collection period and analyzed at once in one analytical run. All samples were analyzed in duplicate. Estimations were calculated according to Fraser and Harris methods. Results: CVI value for fresh samples (13.78%) was significantly lower than that in frozen samples (18.91%) (p<0.001). However, there was no statistically significant difference in CVG values between fresh (16.91%) and frozen (18.43%) samples (p=0.570). The index of individuality did not exceed 1.4 for fresh and frozen samples. The estimated RCVs were high for both fresh and frozen samples (43.37% and 56.85%, respectively). Quality specifications were established. Conclusions: The present study for the first time described the components of biological variation for ammonia in healthy individuals. These data regarding biological variation of ammonia could be useful for a better evaluation of ammonia test results in clinical interpretation and for determining quality specifications based on biological variation. [ABSTRACT FROM AUTHOR]

The reference change value, defined as RCV=1.96×2 1/2 ×(s I 2 +s A 2 ) 1/2 , where s I is within-subject biological variation and s A is analytical variation, has been used for many years to take clinical decisions in patient monitoring. Furthermore, the index of individuality was defined as II=(s I 2 +s A 2 ) 1/2 /s G , where s G is the between-subject biological variation. This index has been simplified by later authors to s I /s G and has been used in monitoring situations to determine the utility of population-based reference intervals. Harris stated that when the index of individuality is lower than 0.6, the specific reference interval of the individual – when available – is better than the population-based reference interval. However, if a change within a patient is equivalent to the RCV applied for the significant difference between two measurements, the probability of detecting this change is only 50% (the same probability of missing it). Therefore, to obtain a higher probability of detecting a change by the RCV (e.g., 90%) the interpretation of the index of individuality has to be reconsidered. This contribution compares the power of the RCV to the use of cut-off points and population-based reference intervals. The benefits of the RCV compared to the distance to cut-off point or reference limit are also described in relation to the index of individuality. [ABSTRACT FROM AUTHOR]

Background: For biological variation (BV) data to be safely used, data must be reliable and relevant to the population in which they are applied. We used samples from the European Biological Variation Study (EuBIVAS) to determine BV of coagulation markers by a Bayesian model robust to extreme observations and used the derived within-participant BV estimates [CVP(i)] to assess the applicability of the BV estimates in clinical practice., Method: Plasma samples were drawn from 92 healthy individuals for 10 consecutive weeks at 6 European laboratories and analyzed in duplicate for activated partial thromboplastin time (APTT), prothrombin time (PT), fibrinogen, D-dimer, antithrombin (AT), protein C, protein S free, and factor VIII (FVIII). A Bayesian model with Student t likelihoods for samples and replicates was applied to derive CVP(i) and predicted BV estimates with 95% credibility intervals., Results: For all markers except D-dimer, CVP(i) were homogeneously distributed in the overall study population or in subgroups. Mean within-subject estimates (CVI) were <5% for APTT, PT, AT, and protein S free, <10% for protein C and FVIII, and <12% for fibrinogen. For APTT, protein C, and protein S free, estimates were significantly lower in men than in women ≤50 years., Conclusion: For most coagulation markers, a common CVI estimate for men and women is applicable, whereas for APTT, protein C, and protein S free, sex-specific reference change values should be applied. The use of a Bayesian model to deliver individual CVP(i) allows for improved interpretation and application of the data., (© American Association for Clinical Chemistry 2021.)