Evidence map›Paper›PMID 37359198›Full record

ArticleAdvances in laboratory medicine2021

Big data and reference intervals: rationale, current practices, harmonization and standardization prerequisites and future perspectives of indirect determination of reference intervals using routine data.

Luisa Martinez-Sanchez, Fernando Marques-Garcia, Yesim Ozarda, Albert Blanco, Nannette Brouwer, Francesca Canalias, Christa Cobbaert, Marc Thelen, Wendy den Elzen

Abstract read
In one paragraph

Article in Advances in laboratory medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
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

22 citing papers in PubMed.

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  7. Diversity of words and words for diversity.Frontiers in psychiatry · 2026
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  9. Advances in laboratory medicine · 2025
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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

9 authors.

Luisa Martinez-SanchezClinical Biochemistry Department, Vall d'Hebron University Hospital, Barcelona, Spain.ORCID https://orcid.org/0000-0002-3936-0156
Fernando Marques-GarciaDepartment of Clinical Biochemistry, University Hospital of Salamanca, Salamanca, Spain.
Yesim OzardaDepartment of Medical Biochemistry, Uludag University School of Medicine, Bursa, Turkey.
Albert BlancoClinical Biochemistry Department, Vall d'Hebron University Hospital, Barcelona, Spain.
Nannette BrouwerDiagnost-IQ, Expert Centre for Clinical Chemistry, Purmerend, The Netherlands.
Francesca CanaliasLaboratori de Referència d'Enzimologia Clínica, Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Bellaterra, Spain.
Christa CobbaertDepartment of Clinical Chemistry and Laboratory Medicine, Leiden University Medical Centre, Leiden, The Netherlands.
Marc ThelenLaboratory for Clinical Chemistry and Hematology, Amphia, Breda, The Netherlands.
Wendy den ElzenDepartment of Clinical Chemistry and Laboratory Medicine, Leiden University Medical Centre, Leiden, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Reference intervals are commonly used as a decision-making tool. In this review, we provide an overview on "big data" and reference intervals, describing the rationale, current practices including statistical methods, essential prerequisites concerning data quality, including harmonization and standardization, and future perspectives of the indirect determination of reference intervals using routine laboratory data.

Indexed as

big dataindirect methodsreference intervals

Identifiers

PMID37359198
PMCPMC10197285

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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.