Literature DB >> 19072029

Measurement uncertainty in manual differential leukocyte counting.

Xavier Fuentes-Arderiu1, Dolors Dot-Bach.   

Abstract

BACKGROUND: One of the most frequently requested examinations in the clinical laboratory is the differential leukocyte count. Despite many technological improvements, thousands of differential leukocyte counts are made by microscopic examination of a blood smear, counting 100 leukocytes and expressing the fraction of the specific leukocyte types as percentages (rounded to integer values) of the total leukocyte count. Although in the clinical laboratory it is not usual practice to report measurement uncertainties, currently the ISO 15189 standard considers measurement uncertainty as a very helpful element for a comprehensive interpretation of any measurement result.
METHODS: The estimation of the measurement uncertainty of each differential leukocyte count result was carried out according to international guidelines. The sources of standard uncertainty taken into account were: pre-metrological variation, random distribution, between-examiner reproducibility, and rounding to an integer.
RESULTS: In this example, a sample of blood with a concentration number of leukocytes of 3,5x10(9)/L (1)) is taken into consideration. For each differential leukocyte count result, the standard uncertainties corresponding to each source of measurement uncertainty, as well as the combined and the expanded uncertainties, were estimated with information from the literature.
CONCLUSIONS: The procedure presented here to estimate the measurement uncertainty of differential leukocyte count results is appropriate to fulfill the requirements of the ISO 15189 standard related to measurement uncertainty. Knowledge of this uncertainty is helpful in interpreting sequential results obtained in the same patient.

Entities:  

Mesh:

Year:  2009        PMID: 19072029     DOI: 10.1515/CCLM.2009.014

Source DB:  PubMed          Journal:  Clin Chem Lab Med        ISSN: 1434-6621            Impact factor:   3.694


  5 in total

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2.  Improvement of cell counting method for Neubauer counting chamber.

Authors:  Minghao Zhang; Lingui Gu; Peihua Zheng; Zhixin Chen; Xinqi Dou; Qizhong Qin; Xiaozhong Cai
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Journal:  Leukemia       Date:  2021-09-08       Impact factor: 11.528

4.  Highly accurate differentiation of bone marrow cell morphologies using deep neural networks on a large image data set.

Authors:  Christian Matek; Sebastian Krappe; Christian Münzenmayer; Torsten Haferlach; Carsten Marr
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5.  Evaluation of two semi-supervised learning methods and their combination for automatic classification of bone marrow cells.

Authors:  Iori Nakamura; Haruhi Ida; Mayu Yabuta; Wataru Kashiwa; Maho Tsukamoto; Shigeki Sato; Syuichi Ota; Naoki Kobayashi; Hiromi Masauzi; Kazunori Okada; Sanae Kaga; Keiko Miwa; Hiroshi Kanai; Nobuo Masauzi
Journal:  Sci Rep       Date:  2022-10-06       Impact factor: 4.996

  5 in total

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