Use of Sysmex XN-10 red blood cell parameters for screening of hereditary red blood cell diseases and iron deficiency anaemia.


Journal

International journal of laboratory hematology
ISSN: 1751-553X
Titre abrégé: Int J Lab Hematol
Pays: England
ID NLM: 101300213

Informations de publication

Date de publication:
Dec 2020
Historique:
received: 27 01 2020
revised: 04 06 2020
accepted: 08 06 2020
pubmed: 9 7 2020
medline: 4 2 2021
entrez: 9 7 2020
Statut: ppublish

Résumé

In daily practice in haematology laboratories, red blood cell (RBC) abnormalities are frequent and their management is a real challenge. The aim of this study is to establish a "decision tree" using RBC and reticulocyte parameters from the SYSMEX XN-10 analyser to distinguish between patients with a hereditary RBC disease from iron deficiency anaemia and other patients. We analysed results of complete RBC counts in a cohort composed of 8217 adults divided into 5 different groups: iron deficiency anaemia (n = 120), heterozygous haemoglobinopathy (n = 92), sickle cell disease syndrome (n = 56), hereditary spherocytosis (n = 18) and other patients (n = 7931). A Classification And Regression Tree (CART) analysis was used to obtain a two-step decision tree in order to predict these previous groups. Five parameters and the calculated RBC score were selected by the CART method: mean corpuscular haemoglobin concentration, percentage of microcytes, distribution width of the RBC histogram, percentage of nucleated red blood cells, immature reticulocytes fraction and finally RBC Score. When applying the tree and recommended flowchart, 158/166 of the RBC hereditary disease patients and 114/120 iron deficiency anaemia patients are detected. Overall, the correct classification rate reached 99.4%. Sensitivity and specificity for RBC disease detection were 95.2% and 99.9%, respectively. These results were confirmed in an independent validation cohort. Based on the XN-10 RBC and reticulocyte parameters, we propose a two-step decision tree delivering a good prediction and classification of hereditary RBC diseases. These results can be used to optimize additional reticulocyte analysis and microscopy review.

Identifiants

pubmed: 32639680
doi: 10.1111/ijlh.13278
pmc: PMC7754411
doi:

Types de publication

Clinical Trial Journal Article Validation Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

697-704

Informations de copyright

© 2020 The Authors. International Journal of Laboratory Hematology published by John Wiley & Sons Ltd.

Références

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Auteurs

Vanessa Nivaggioni (V)

Laboratoire d'Hématologie, Hôpital de la Timone, Assistance Publique - Hôpitaux de Marseille, Marseille, France.

Lakhdar Bouriche (L)

Laboratoire SYNLAB Provence, Marseille, France.

Sylvie Coito (S)

Laboratoire Ketterthill, Belvaux, Luxembourg.

Anne-Sophie Le Floch (AS)

Laboratoire d'Hématologie, Hôpital de la Timone, Assistance Publique - Hôpitaux de Marseille, Marseille, France.

Manal Ibrahim-Kosta (M)

Laboratoire d'Hématologie, Hôpital de la Timone, Assistance Publique - Hôpitaux de Marseille, Marseille, France.

Caroline Leonnet (C)

Laboratoire d'Hématologie, Hôpital de la Timone, Assistance Publique - Hôpitaux de Marseille, Marseille, France.

Isabelle Arnoux (I)

Laboratoire d'Hématologie, Hôpital de la Timone, Assistance Publique - Hôpitaux de Marseille, Marseille, France.

Marie Loosveld (M)

Laboratoire d'Hématologie, Hôpital de la Timone, Assistance Publique - Hôpitaux de Marseille, Marseille, France.
Aix Marseille Univ, CNRS, INSERM, CIML, Marseille, France.

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Classifications MeSH