Evidence map›Paper›PMID 40303482›Full record

ArticleInternational journal of population data science2024

Mother and Infant Research Electronic Data Analysis (MIREDA): A protocol for creating a common data model for federated analysis of UK birth cohorts and the life course.

Mike Seaborne, Hope Jones, Neil Cockburn, Stevo Durbaba, Arturo González-Izquierdo, Amy Hough, Dan Mason, Carlos Sánchez-Soriano, Chris Orton, Armando Méndez-Villalon and 8 more

Abstract read
In one paragraph

Article in International journal of population data science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

18 authors.

Mike SeaborneNational Centre for Population Health and Wellbeing Research, Swansea University Medical School, Swansea, UK.
Hope JonesNational Centre for Population Health and Wellbeing Research, Swansea University Medical School, Swansea, UK.
Neil CockburnInstitute of Applied Health Research, University of Birmingham, Birmingham, UK.
Stevo DurbabaeLIXIR, Born in South London, King's College London, Strand, London, UK.
Arturo González-IzquierdoInstitute of Applied Health Research, University of Birmingham, Birmingham, UK.
Amy HoughBorn in Bradford, Bradford Institute for Health Research, Bradford Royal Infirmary, Bradford, UK.
Dan MasonBorn in Bradford, Bradford Institute for Health Research, Bradford Royal Infirmary, Bradford, UK.
Carlos Sánchez-SorianoBorn in Scotland, Centre for Cardiovascular Science, University of Edinburgh, Queen's Medical Research Institute, Edinburgh, UK.
Chris OrtonHealth Data Science, Swansea University, Swansea, UK.
Armando Méndez-VillalonDigital Research Service, University of Nottingham, Nottingham, UK.
Tom GilesDigital Research Service, University of Nottingham, Nottingham, UK.
David FordHealth Data Science, Swansea University, Swansea, UK.
Phillip QuinlanDigital Research Service, University of Nottingham, Nottingham, UK.
Krish NirantharakumarInstitute of Applied Health Research, University of Birmingham, Birmingham, UK.
Lucilla PostoneLIXIR, Born in South London, King's College London, Strand, London, UK.
Rebecca ReynoldsBorn in Scotland, Centre for Cardiovascular Science, University of Edinburgh, Queen's Medical Research Institute, Edinburgh, UK.
Gillian SantorelliBorn in Bradford, Bradford Institute for Health Research, Bradford Royal Infirmary, Bradford, UK.
Sinead BrophyNational Centre for Population Health and Wellbeing Research, Swansea University Medical School, Swansea, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Birth cohorts are valuable resources for studying early life, the determinants of health, disease, and development. They are essential for studying life course. Dynamic longitudinal electronic cohorts use routinely collected data, are live, and can reduce selection bias specifically associated with direct recruitment in traditional birth cohorts. However, they are limited to health and administrative data and may lack contextual information.The MIREDA (Mother and Infant Research Electronic Data Analysis) partnership creates a UK-wide birth cohort by aligning existing electronic birth cohorts to have the same structure, content, and vocabularies, enabling UK-wide federated analyses. Objectives: Create a core dynamic, live UK-wide electronic birth cohort with approximately 500,000 new births per year using a common data model (CDM).Provide data linkage and automation for long-term follow up of births from the Clinical Practice Research Datalink (CPRD), MuM-PreDiCT and the 'Born in' initiatives of Bradford, Wales, Scotland, and South London for comparable analyses. Methods: We will establish core data content and collate linkable data. A suite of extraction, transformation, and load (ETL) tools will be used to transform data for each birth cohort into the CDM. Transformed datasets will remain within each cohort's trusted research environment (TRE). Metadata will be uploaded for the public to the Health Data Research (HDRUK) Innovation Gateway. We will develop a single online data access request for researchers. A cohort profile will be developed for researchers to reference the resource. Ethics: Each cohort has approval from their TRE through compliance with their project application processes and information governance. Dissemination: We will engage with researchers in the field to promote our resource through partnership networking, publication, research collaborations, conferences, social media, and marketing communications strategies.

Indexed as

Birth CohortData AnalysisElectronic Health RecordsFemaleHumansInfantInfant, NewbornMothersUnited Kingdombirth cohortdata linkagedata sciencelife coursepopulation dataroutinely collected health dataunified medical language system

Identifiers

PMID40303482
PMCPMC12039474

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.