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Quality control of multichannel hematology analyzers. Bivariate on-line comparison of MCV and MCH values for the
V Kairisto1, T Kouri, A Rajamäki
1Central Laboratory, University Hospital, Turku, Finland.
Volume and hemoglobin content of red blood cells are physiologically interdependent variables but are measured independently in multichannel hematologic analyzers. Therefore correlation of these results to each other can be used as an additional step in internal quality control. To facilitate precise correlation, data were collected from 44,873 consecutive routine determinations of red blood cell parameters. Gaussian distributions were fitted to the original distributions and bivariate elliptical acceptance limits were calculated for simultaneous evaluation of mean corpuscular volume and mean corpuscular hemoglobin results. With the proposed method, rare combinations of the three directly measured red blood cell parameters (hemoglobin, red blood cell count, and mean corpuscular volume) can be identified for the detection of random analytical or preanalytical errors. This mean corpuscular volume-mean corpuscular hemoglobin rule could be added to internal quality-control programs of hematologic analyzers to improve detection of unusual results and possible random errors.
Volume and hemoglobin content of red blood cells are physiologically interdependent variables but are measured independently in multichannel hematologic analyzers. Therefore correlation of these results to each other can be used as an additional step in internal quality control. To facilitate precise correlation, data were collected from 44,873 consecutive routine determinations of red blood cell parameters. Gaussian distributions were fitted to the original distributions and bivariate elliptical acceptance limits were calculated for simultaneous evaluation of mean corpuscular volume and mean corpuscular hemoglobin results. With the proposed method, rare combinations of the three directly measured red blood cell parameters (hemoglobin, red blood cell count, and mean corpuscular volume) can be identified for the detection of random analytical or preanalytical errors. This mean corpuscular volume-mean corpuscular hemoglobin rule could be added to internal quality-control programs of hematologic analyzers to improve detection of unusual results and possible random errors.
