Evidence map›Paper›PMID 41436645›Full record

ArticleCommunications medicine2025

Methods to establish a Pregnancy Register in the QResearch Database.

Andrew Jhl Snelling, Emma Copland, Winnie X Mei, Wema M Mtika, Tom Ranger, Carol Coupland, QResearch Pregnancy Consortium, Aziz Sheikh, Julia Hippisley-Cox, Jennifer A Hirst

Abstract read
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Article in Communications medicine, 2025. 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. 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

10 authors.

Andrew Jhl SnellingWolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.ORCID http://orcid.org/0000-0002-2882-2079
Emma CoplandWolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.ORCID http://orcid.org/0000-0001-9280-5241
Winnie X MeiNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Wema M MtikaNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID http://orcid.org/0009-0007-1242-4889
Tom RangerNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Carol CouplandWolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
QResearch Pregnancy Consortium
Aziz SheikhNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Julia Hippisley-CoxWolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.ORCID http://orcid.org/0000-0002-2479-7283
Jennifer A HirstNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK. jennifer.hirst@phc.ox.ac.uk.ORCID http://orcid.org/0000-0002-8416-2159

Funding

CSP VA 591
6 · The paper itself

Abstract

backgroundElectronic health records are increasingly used to conduct pregnancy-related research as pregnant women are under-represented in research. Creating a register of pregnancies by combining data from primary and secondary care will further facilitate research in pregnancy. This work describes the construction of an algorithm to create a unified pregnancy cohort in the QResearch database during the emergency phase of the COVID-19 pandemic.

methodsNational primary care records in the QResearch® database were linked to patient-level data from Hospital Episode Statistics (HES) datasets. Females aged 15-50 years with a pregnancy outcome recorded between 30 December 2020 and 30 September 2022 were included. Pregnancy (delivery/loss) episodes were identified and cohort demographics reported using a three-stage algorithm. Pregnancy start dates were derived using a combination of HES and primary care data, or individually estimated where no corresponding date could be identified.

results266,758 women with 279,027 pregnancies are captured in the register. 232,673 pregnancies (83.4%) are deliveries (99.5% livebirths and 0.5% stillbirths) and 46,354 (16.6%) pregnancies are pregnancy losses. Pregnancy losses are highest amongst those of Caribbean (23.1%; n = 781) ethnicity and lowest in those of Pakistani ethnicity (13.9%, n = 1,579). 82.4% of pregnancies are derived from HES maternity records, 10.6% from primary care records, 3.4% from HES Admissions, and 3.6% from HES Procedures.

conclusionThe construction of a pregnancy register in QResearch® offers a valuable resource for future research. Its methodology can be adapted to construct new cohorts over any period, providing a comprehensive resource on pregnancy outcomes and events.

Identifiers

PMID41436645
PMCPMC12727747

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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.