The influence of coagulation factors on the in-treatment biological variation of international normalized ratio for patients on warfarin.

BACKGROUND: Biological variation is usually estimated in healthy individuals during steady-state conditions. The aim of this study was to estimate the in-treatment biological variation of the International normalised ratio (INR) and to investigate to what extent the different levels of coagulation factors could explain this variation. METHODS: Blood samples were collected from randomly included patients on warfarin treatment. INR was determined on a laboratory instrument (STA Compact(®)) and on three point-of-care instruments (Simple Simon(®)PT, CoaguChek(®)XS and INRatio(™)). The level of fibrinogen, and the activity of coagulation factors II, V, VII and X were determined. RESULTS: The in-treatment within- and between-subject coefficients of variation of INR were dependent on the method and varied between 18 and 24% and 13 and 19%, respectively, and were reduced to 3.9-5.1% and 2.3-5.8%, after correction for coagulation factors which could explain 91-95% of the variance of INR. CONCLUSIONS: The in-treatment biological variation of INR was higher than reported for healthy individuals as well as patients in a steady-state condition, but by correcting for appropriate coagulation factors it was reduced. The association between INR and coagulation factors was different for the different PT methods mainly due to different sensitivity towards FII and FVII.

External quality assessment of point-of-care methods: model for combined assessment of method bias and single-participant performance by the use of native patient samples and noncommutable control materials.

BACKGROUND: An important objective in external quality assessment (EQA) is to evaluate systematic deviations between methods. However, this is not possible when noncommutable control materials are used. The aim of this study was to develop an EQA model that incorporates a method bias evaluation using native patient samples into EQA schemes in which noncommutable materials are used. METHODS: The model was applied twice in a point-of-care (POC) international normalized ratio survey among 1341 and 1578 participants. To estimate bias, about 100 native patient samples for each POC method were analyzed by a selected group of "expert" primary healthcare centers and on a designated comparison method. In addition, the expert centers as well as all the other EQA participants analyzed 2 noncommutable control materials, and method-specific target values were established. Both method bias and the deviation of a single-participant result from the method target value were evaluated against analytical quality specifications, making combined assessment possible. The best-case scenario occurred when both results were within the quality specifications. RESULTS: Two POC methods fulfilled the quality specification for bias, whereas one did not. The best-case scenario was achieved by more than 90% of the participants using the methods with no bias, whereas none of the participants using the method with unacceptable bias achieved this result. CONCLUSIONS: We propose an EQA model for which the bias of POC methods can be evaluated in situations in which commutable control materials are not available.

Discrepancies in international normalized ratio results between instruments: a model to split the variation into subcomponents.

BACKGROUND: Observed differences between results obtained from comparison of instruments used to measure international normalized ratio (INR) have been higher than expected from the imprecision of the instruments. In this study the variation of these differences was divided into subcomponents, and each of the subcomponents was estimated. METHODS: Blood samples were collected at 4 different patient visits from each of 36 outpatients who were receiving warfarin treatment and were included in the study. INR was determined on 1 laboratory instrument (STA Compact®) and 3 point-of-care instruments (Simple Simon®PT, CoaguChek®XS, and INRatio™). All 4 INR instruments were compared in pairs. Linear regression was used to correct for systematic deviations. The remaining variation of the differences was subdivided into between-subject, within-subject, and analytical variation in an ANOVA nested design. RESULTS: The mean difference between instruments varied between 1.0% and 14.3%. Between-subject variation of the differences (expressed as CV) varied between 3.3% and 7.4%, whereas within-subject variation of the differences was approximately 5% for all 6 comparisons. The analytical imprecision of the differences varied between 3.8% and 8.6%. CONCLUSIONS: The differences in INR between instruments were subdivided into calibration differences, between- and within-subject variation, and analytical imprecision. The magnitude of each subcomponent was estimated. Within results for individual patients the difference in INR between 2 instruments varied over time. The reasons for the between- and within-subject variations of the differences can probably be ascribed to different patient-specific effects in the patient plasma. To minimize this variation in a monitoring situation, each site and patient should use results from only 1 type of instrument.

Human serum-induced porcine endothelial cell E-selectin expression is associated with IgG3 and IgM anti-Gal antibodies.

Naturally occurring anti-Galalpha1-3Gal (anti-Gal) antibodies and complement induce hyperacute rejection (HAR) of porcine organs transplanted to primates. If the hyperacute reaction is prevented, an acute vascular rejection (AVR) occurs within hours to few days. Antibodies are important for the development of AVR, whereas the role of complement is still not clarified. AVR is characterized by protein synthesis-dependent endothelial cell (EC) activation. In the present study we investigated the relation between EC activation as measured by E-selectin expression, and the concentrations of anti-Gal antibodies of IgM, IgG and IgG subclasses in sera from 80 healthy blood donors selected on the basis of sex and age. There was a significant correlation between E-selectin expression and the concentration of IgG3 anti-Gal (r=0.39; P=0.019), which was not seen for the other IgG subclasses or for total IgG anti-Gal. A modest, but significant correlation was found between the concentration of IgM anti-Gal and E-selectin expression (r=0.38; P=0.040), but not between IgM and IgG3 anti-Gal. There was a large interindividual variation in anti-Gal antibodies, 50-fold for IgM and 70-fold for IgG. Females had significantly higher concentrations of IgM anti-Gal than males (P=0.0006), which was explained by a substantial increase in IgM anti-Gal concentration in younger women. The concentration of IgG anti-Gal and the degree of E-selectin expression did not differ between sex or age groups. In conclusion, the close correlation between anti-Gal antibodies of the potent complement activating IgG3 subclass and porcine EC activation, may imply that these antibodies play a role in EC activation characteristic of AVR.