Archive for the ‘Blood Gas’ Category

The finding that models of the same manufacturer usually differ significantly from each other for two or more analytes (Table 2) initially was surprising to us. However, these model differences are likely due to continuing improvements in analyzer geometry, calibration and flushing techniques, temperature control, electronic signal modification, and other unknown factors. Manufacturers can be […]

With minor quantitative changes, we believe our findings are relevant to clinical and research blood analyses. Because aqueous and FCE proficiency testing materials differ from fresh human blood in viscosity, oxygen capacity and content, oxygen halfsaturation pressure of hemoglobin values, and temperature dependence, they can be expected to differ from blood, but FCE has shown […]

Our initial analysis strategy involved seeking differences in the mean values produced by a number of instruments of a given model across a range of analyte values utilizing ANOVA. However, we found this strategy failed to detect many appreciable differences. Specifically, when two models exhibit a “crossover” pattern of mean model values as a function […]

Table 3 endeavors to illustrate representative variations that might be expected among models for each of three analytes. It can be noted that the range of values (ie, the difference between the model with the highest mean value and the model with the lowest mean value) obtained by these seven models at low, intermediate, and […]

Statistically, none of the six IL models measure all three analytes without statistically significant differences. The closest matches are the 1304, 1306, and 1312 models that are not dissimilar for two analytes. The 1400 and 1420 models are not dissimilar for Po2 and Pco2. The 1620 models differs from the other five models for all […]

For the three manufacturers, statistical comparisons were made comparing each model with other models of that manufacturer. Nine ANOVAs were performed, each revealing statistically significant differences. The subsequent Scheffe tests yielded 53 N grades, 15 D grades, and 85 V grades. Thus, the mean values for nearly two thirds of the paired comparisons revealed a […]

Comparisons Between Manufacturers The three graphs comparing manufacturers with each other for each analyte (Figs 1-3) visually demonstrate the differences between manufacturers along the complete range of intensities. Table 1 indicates the degree of the statistical dissimilarity between manufacturers for each analyte using the three traditional ANOVAs. For the 18 paired analyte comparisons, only the […]

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