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Autoverification-based algorithms to detect preanalytical errors: Two examples.

Publication ,  Journal Article
Wei, R; Légaré, W; McShane, AJ
Published in: Clin Biochem
May 2023

The preanalytical phase of testing accounts for the majority of the errors. Software-based quality rules, such as autoverification, can assist in preanalytical error detection; therefore, preventing erroneous results from being reported. Two autoverification rules, turbidity/lipemia, and pseudohypoglycemia/pseudohyperkalemia alarms, are highlighted. Increased sample turbidity may arise from several causes outside of lipemia. Typically, this can be resolved by clarifying the sample with standard centrifugation. Truly lipemic specimens typically require higher centrifugation speeds and greater centrifugation time. At our facility, 96% of direct bilirubin (DBIL), 95% of aspartate transaminase (AST), and 98% of alanine transaminase (ALT) turbidity/lipemia alarms were found to be from sample turbidity versus lipemia. Secondly, a pseudohypoglycemia/pseudohyperkalemia rule was employed for specimens with delayed separation from cellular material. Of the total potassium results >6.0 mmol/L or glucose results <40 mg/dL (2.2 mmol/L), 30% and 50% respectively were noted to have delayed sample separation.

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Published In

Clin Biochem

DOI

EISSN

1873-2933

Publication Date

May 2023

Volume

115

Start / End Page

126 / 128

Location

United States

Related Subject Headings

  • Software
  • Humans
  • General Clinical Medicine
  • Bilirubin
  • Aspartate Aminotransferases
  • Algorithms
  • Alanine Transaminase
  • 3205 Medical biochemistry and metabolomics
  • 3202 Clinical sciences
  • 1103 Clinical Sciences
 

Citation

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ICMJE
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Wei, R., Légaré, W., & McShane, A. J. (2023). Autoverification-based algorithms to detect preanalytical errors: Two examples. Clin Biochem, 115, 126–128. https://doi.org/10.1016/j.clinbiochem.2022.06.010
Wei, Ruhan, William Légaré, and Adam J. McShane. “Autoverification-based algorithms to detect preanalytical errors: Two examples.Clin Biochem 115 (May 2023): 126–28. https://doi.org/10.1016/j.clinbiochem.2022.06.010.
Wei R, Légaré W, McShane AJ. Autoverification-based algorithms to detect preanalytical errors: Two examples. Clin Biochem. 2023 May;115:126–8.
Wei, Ruhan, et al. “Autoverification-based algorithms to detect preanalytical errors: Two examples.Clin Biochem, vol. 115, May 2023, pp. 126–28. Pubmed, doi:10.1016/j.clinbiochem.2022.06.010.
Wei R, Légaré W, McShane AJ. Autoverification-based algorithms to detect preanalytical errors: Two examples. Clin Biochem. 2023 May;115:126–128.
Journal cover image

Published In

Clin Biochem

DOI

EISSN

1873-2933

Publication Date

May 2023

Volume

115

Start / End Page

126 / 128

Location

United States

Related Subject Headings

  • Software
  • Humans
  • General Clinical Medicine
  • Bilirubin
  • Aspartate Aminotransferases
  • Algorithms
  • Alanine Transaminase
  • 3205 Medical biochemistry and metabolomics
  • 3202 Clinical sciences
  • 1103 Clinical Sciences