Outlier removal methods for skewed data: impact on age-specific high-sensitive cardiac troponin T 99th percentiles

Clin Chem Lab Med. 2019 Sep 25;57(10):e244-e247. doi: 10.1515/cclm-2018-1366.

Denis Monneret¹, Martin Gellerstedt², Frédéric Roche^{3

4}, Dominique Bonnefont-Rousselot^{5

6}

¹ Department of Biochemistry and Molecular Biology, South Lyon Hospital Group, Hospices Civils de Lyon (HCL), 165 Chemin du Grand Revoyet, 69495 Pierre-Bénite, France.
² School of Business, Economics and IT, University West, Göteborg, Sweden.
³ Department of Clinical and Exercise Physiology, University Hospital of Saint-Etienne, Saint-Etienne, France.
⁴ EA 4607 SNA-EPIS, PRES Lyon, Saint-Etienne, France.
⁵ Department of Metabolic Biochemistry, La Pitié Salpêtrière-Charles Foix University Hospital (AP-HP), Paris, France.
⁶ CNRS UMR8258 - INSERM U1022, Faculty of Pharmacy, Sorbonne Paris Cité, Paris Descartes University, Paris, France.

No abstract available

Keywords: 99th percentile; high-sensitive cardiac troponin; nonparametric methods; outlier removal.

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