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

作者信息

Wei Ruhan, Légaré William, McShane Adam J

机构信息

Department of Laboratory Medicine, Cleveland Clinic, Cleveland, OH, USA.

Department of Laboratory Medicine, Cleveland Clinic, Cleveland, OH, USA.

出版信息

Clin Biochem. 2023 May;115:126-128. doi: 10.1016/j.clinbiochem.2022.06.010. Epub 2022 Jun 30.

DOI:10.1016/j.clinbiochem.2022.06.010
PMID:35779575
Abstract

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.

摘要

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