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Autoverification-based algorithms to detect preanalytical errors: Two examples.
Wei, Ruhan; Légaré, William; McShane, Adam J.
  • Wei R; Department of Laboratory Medicine, Cleveland Clinic, Cleveland, OH, USA.
  • Légaré W; Department of Laboratory Medicine, Cleveland Clinic, Cleveland, OH, USA.
  • McShane AJ; Department of Laboratory Medicine, Cleveland Clinic, Cleveland, OH, USA. Electronic address: mcshana@ccf.org.
Clin Biochem ; 115: 126-128, 2023 May.
Article en En | MEDLINE | ID: mdl-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.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Algoritmos / Programas Informáticos Límite: Humans Idioma: En Año: 2023 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Algoritmos / Programas Informáticos Límite: Humans Idioma: En Año: 2023 Tipo del documento: Article