Antoine Mairesse

This study investigates the impact of sample type on the measurement of 25-OH-vitamin D using the Liaison XL (Diasorin) and Cobas e801 (Roche). This investigation was motivated by the need to optimize sample volume usage, which led us to adopt the use of heparin plasma, an alternative proposed by Diasorin in their specification. Discordant and unexplainable results were observed, prompting us to evaluate the effect of sample type on the accuracy of the 25-OH-vitamin D measurements. We collected 34 different paired samples from a randomly selected patients who had two types of tubes taken simultaneously: serum-gel and lithium-heparin plasma tubes. The 25-OH-vitamin D levels were measured using Cobas e801 and Liaison. Statistical analysis was performed using the Mann-Whitney test to calculate the p-value. Biases were also calculated. When comparing the heparin matrix with the serum matrix on the Liaison XL analyzer, a higher proportion (p < .0001; 79% versus 64%) of patients were classified in the 'normal group', while fewer were classified in the 'insufficiency' or 'deficiency group'. The heparin tubes on the Liaison XL analyzer showed a mean bias of 57.5%) (p-value < .001; 95%CI: 37.6-77.4) compared to the serum tubes. On the other hand, the heparin tubes on the Cobas e801 analyzer showed a mean bias of -0.2% (95%CI: -4.8 to 4.5) compared to the serum tubes. It is imperative for laboratory professionals to be aware of this interference for an accurate measurement of 25-OH-vitamin D levels on the Liaison XL. Further research is needed to understand the mechanism of this interference.

Background Evaluation of an individual's thrombin-generating capacity enables a global assessment of the coagulation cascade and is therefore thought to better reflect the clotting function of blood. However, the lack of standardization still hampers the use in routine clinical practice. Methods Nineteen healthy subjects were sampled once a week for 5 consecutive weeks. Thrombin generation assay (TGA) was performed in duplicate by calibrated automated thrombogram (CAT) on platelet poor plasma with and without thrombomodulin. After exclusion of outliers, a nested analysis of variance (ANOVA) was performed to evaluate the biological variability (BV) results. Analytical variation (CVA), within-individual variation (CVI), between-individual variation (CVG), index of individuality (II), and reference change value (RCV) were calculated. Results All parameters taken together, the CVA, CVI, and CVG without TM, ranged from 2.8% to 6.5%, from 4.1% to 13.3% and from 10.4% to 28.4%, respectively. For TG with TM, CVI and CVG were higher and ranged from 5.0% to 18.1% and from 14.9% to 35.3%, respectively. For endogenous thrombin potential (ETP), a CVI of 4.1% and CVG of 10.4% were obtained without addition of thrombomodulin (TM). With addition of TM, both CVI and CVG were higher: 14.0% and 34.8%, respectively. The II was low and the RCV ranged from 17.2% to 50.4%. Conclusion CAT parameters are highly individualized and population-based reference values could be called into question. The assessment of BV and RCV for thrombin generation assays could optimize interpretation of serial patient results and guide setting of analytical specification goals.

Background: Interpretation of thyroid function tests by means of biological variation (BV) data is essential to identify significant changes between serial measurements at an individual level. Data on thyroid parameters in adults are limited.Objectives: We aimed at determining the BV of four thyroid function test (thyroid‐stimulating hormone (TSH), free thyroxin (FT4), free triiodothyronine (FT3) and thyroglobulin (Tg)) by applying recent recommendations to acquire BV data on a latest generation of immunoassay.Methods: Nineteen healthy volunteers (8 males and 11 females) were drawn every week during 5 consecutive weeks. Samples were analysed in duplicate on the Cobas 602 analyzer (Roche Diagnostics). After normality assessment, outlier exclusion and homogeneity of variance analysis, analytical variation (CV_A), within‐subject biological variation (CV_I) and between‐subject biological variation (CV_G) were determined using nested ANOVA.Results: CV_A, CV_I and CV_G were 0.9%, 19.7% and 37.6% for TSH; 3.6%, 4.6% and 10.8% for FT4; 2.2%, 6.0% and 8.6% for FT3; and 0.9%, 15.4% and 84.9% for Tg. Index of individuality (II) for all parameters was between 0.2 and 0.7. The percentage above which the change between two measures is truly significant (reference change value) was 54.7% for TSH, 16.2% for FT4, 17.7% for FT3 and 42.8% for Tg.Conclusion: Based on recent international recommendations, our study provides updated BV data for four thyroid function tests in European healthy volunteers. Reliable BV characteristics, and especially RCV, can facilitate the interpretation of consecutive thyroid function tests in an individual and therefore have the potential to efficiently support clinical decisions regarding thyroid diseases.

The mid-Holocene (6 kyr BP; thousand years before present) is a key period to study the consistency between model results and proxy-based reconstruction data as it corresponds to a standard test for models and a reasonable number of proxy-based records is available. Taking advantage of this relatively large amount of information, we have compared a compilation of 50 air and sea surface temperature reconstructions with the results of three simulations performed with general circulation models and one carried out with LOVECLIM, a model of intermediate complexity. The conclusions derived from this analysis confirm that models and data agree on the large-scale spatial pattern but the models underestimate the magnitude of some observed changes and that large discrepancies are observed at the local scale. To further investigate the origin of those inconsistencies, we have constrained LOVECLIM to follow the signal recorded by the proxies selected in the compilation using a data-assimilation method based on a particle filter. In one simulation, all the 50 proxy-based records are used while in the other two only the continental or oceanic proxy-based records constrain the model results. As expected, data assimilation leads to improving the consistency between model results and the reconstructions. In particular, this is achieved in a robust way in all the experiments through a strengthening of the westerlies at midlatitude that warms up northern Europe. Furthermore, the comparison of the LOVECLIM simulations with and without data assimilation has also objectively identified 16 proxy-based paleoclimate records whose reconstructed signal is either incompatible with the signal recorded by some other proxy-based records or with model physics.