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Icteric human samples: Icterus index and method of estimating an interference-free value for 16 biochemical analyses

Authors :
Guy Gomez
Anne-Marie Lorec
Alain Nicolay
Henri Portugal
Nutriments Lipidiques et Prévention des Maladies Métaboliques
Université de la Méditerranée - Aix-Marseille 2-Institut National de la Recherche Agronomique (INRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Nutrition, obésité et risque thrombotique (NORT)
Aix Marseille Université (AMU)-Institut National de la Recherche Agronomique (INRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Centre recherche en CardioVasculaire et Nutrition (C2VN)
Institut National de la Recherche Agronomique (INRA)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Centre recherche en CardioVasculaire et Nutrition = Center for CardioVascular and Nutrition research (C2VN)
Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de la Recherche Agronomique (INRA)-Université de la Méditerranée - Aix-Marseille 2
Source :
Journal of Clinical Laboratory Analysis, Journal of Clinical Laboratory Analysis, 2018, 32 (2), ⟨10.1002/jcla.22229⟩
Publication Year :
2018
Publisher :
HAL CCSD, 2018.

Abstract

BACKGROUND: Hemolysis, Icterus, and Lipemia constituting the HIL index, are the most common causes of interference with accurate measurement in biochemistry. This study focuses on bilirubin interference, aiming to identify the analyses impacted and proposing a way to predict nominal interference‐free analyte concentrations, based on both analyte level and Icterus Index (I (ict)). METHODS: Sixteen common analytes were studied: alanine aminotransferase (ALT), albumin (ALB), alkaline phosphatase (ALP), amylase (AMY), aspartate aminotransferase (AST), total cholesterol (CHOLT), creatinine (CREA, enzymatic method), fructosamine (FRUC), gamma‐glutamyl transferase (GGT), HDL cholesterol (HDLc), total iron (Iron), lipase (LIP), inorganic phosphorus (Phos), total protein (PROT), triglycerides (TG), and uric acid (UA). Both the traditional 10% change in concentrations from baseline and the Total Change Level (TCL) were taken as acceptance limits. Nineteen pools of sera covering a wide range of values were tested on the Cobas® 6000 (Roche Diagnostics). I (ict) ranged from 0 to 60. RESULTS: Eight analytes increased (FRUC and Phos) or decreased (CHOLT, CREA, HDLc, PROT, TG, and UA) significantly when I (ict) increased. FRUC, HDLc, PROT, and UA showed a linear relationship when I (ict) increased. A non‐linear relationship was found for TG, CREA, and for CHOLT; this also depended on analyte levels. Others were not impacted, even at high I (ict). CONCLUSIONS: A method of estimating an interference‐free value for FRUC, HDLc, PROT, Phos, UA, TG, and CREA, and for CHOLT in cases of cholestasis, is proposed. I (ict) levels are identified based on analytical performance goals, and equations to recalculate interference‐free values are also proposed.

Details

Language :
English
Database :
OpenAIRE
Journal :
Journal of Clinical Laboratory Analysis, Journal of Clinical Laboratory Analysis, 2018, 32 (2), ⟨10.1002/jcla.22229⟩
Accession number :
edsair.doi.dedup.....806fe22e59c39140f6f12e03cd45354f
Full Text :
https://doi.org/10.1002/jcla.22229⟩