Evidence map›Paper›PMID 32639680›Full record

Trial reportInternational journal of laboratory hematology2020

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

Vanessa Nivaggioni, Lakhdar Bouriche, Sylvie Coito, Anne-Sophie Le Floch, Manal Ibrahim-Kosta, Caroline Leonnet, Isabelle Arnoux, Marie Loosveld

Open access · hybridAbstract readClinical TrialValidation Study
In one paragraph

Trial report in International journal of laboratory hematology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.0field-weighted citation impact, top 25% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 2 countries.

Vanessa NivaggioniLaboratoire d'Hématologie, Hôpital de la Timone, Assistance Publique - Hôpitaux de Marseille, Marseille, France.ORCID https://orcid.org/0000-0003-0631-7669
Lakhdar BouricheLaboratoire SYNLAB Provence, Marseille, France.ORCID https://orcid.org/0000-0002-8731-0073
Sylvie CoitoLaboratoire Ketterthill, Belvaux, Luxembourg.ORCID https://orcid.org/0000-0001-7059-4332
Anne-Sophie Le FlochLaboratoire d'Hématologie, Hôpital de la Timone, Assistance Publique - Hôpitaux de Marseille, Marseille, France.ORCID https://orcid.org/0000-0002-0358-9557
Manal Ibrahim-KostaLaboratoire d'Hématologie, Hôpital de la Timone, Assistance Publique - Hôpitaux de Marseille, Marseille, France.ORCID https://orcid.org/0000-0001-9495-7820
Caroline LeonnetLaboratoire d'Hématologie, Hôpital de la Timone, Assistance Publique - Hôpitaux de Marseille, Marseille, France.ORCID https://orcid.org/0000-0002-8732-7684
Isabelle ArnouxLaboratoire d'Hématologie, Hôpital de la Timone, Assistance Publique - Hôpitaux de Marseille, Marseille, France.ORCID https://orcid.org/0000-0002-9387-4115
Marie LoosveldLaboratoire d'Hématologie, Hôpital de la Timone, Assistance Publique - Hôpitaux de Marseille, Marseille, France.ORCID https://orcid.org/0000-0002-8372-4148
Assistance Publique Hôpitaux de Marseille · FRCentre National de la Recherche Scientifique · FRLuxembourg Institute of Science and Technology · LUSynerlab (France) · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionIn 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.

methodsWe 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.

resultsFive 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.

conclusionBased 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.

Indexed as

AdolescentAdultAgedAged, 80 and overAnemia, Iron-DeficiencyAnemia, Sickle CellErythrocytes, AbnormalFemaleHumansMaleMiddle AgedReticulocyte CountSpherocytosis, HereditaryIron deficiency anaemialaboratory practiceRBC and reticulocyte parametersRBC diseaseSysmex XN-10

Identifiers

PMID32639680
PMCPMC7754411
OpenAlexW3040850716

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.