Evidence map›Paper›PMID 37647348›Full record

ArticlePloS one2023

Creating a population-based cohort of children born with and without congenital anomalies using birth data matched to hospital discharge databases in 11 European regions: Assessment of linkage success and data quality.

Maria Loane, Joanne E Given, Joachim Tan, Ingeborg Barišić, Laia Barrachina-Bonet, Clara Cavero-Carbonell, Alessio Coi, James Densem, Ester Garne, Mika Gissler and 12 more

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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

22 authors.

Maria LoaneFaculty of Life and Health Sciences, Ulster University, Belfast, Northern Ireland, United Kingdom.ORCID 0000-0002-1206-3637
Joanne E GivenFaculty of Life and Health Sciences, Ulster University, Belfast, Northern Ireland, United Kingdom.
Joachim TanPopulation Health Research Institute, St George's University of London, London, United Kingdom.
Ingeborg BarišićChildren's Hospital Zagreb, Centre of Excellence for Reproductive and Regenerative Medicine, Medical School University of Zagreb, Zagreb, Croatia.
Laia Barrachina-BonetRare Diseases Research Unit, Foundation for the Promotion of Health and Biomedical Research in the Valencian Region, Valencia, Spain.ORCID 0000-0002-5272-265X
Clara Cavero-CarbonellRare Diseases Research Unit, Foundation for the Promotion of Health and Biomedical Research in the Valencian Region, Valencia, Spain.ORCID 0000-0002-4858-6456
Alessio CoiUnit of Epidemiology of Rare Diseases and Congenital Anomalies, Institute of Clinical Physiology, National Research Council, Pisa, Italy.ORCID 0000-0002-9816-3144
James DensemBiomedical Computing Limited, Battle, United Kingdom.
Ester GarneDepartment of Paediatrics and Adolescent Medicine, Lillebaelt Hospital, University Hospital of Southern Denmark, Kolding, Denmark.
Mika GisslerDepartment of Knowledge Brokers, THL Finnish Institute for Health and Welfare, Helsinki, Finland.
Anna HeinoDepartment of Knowledge Brokers, THL Finnish Institute for Health and Welfare, Helsinki, Finland.
Sue JordanFaculty of Medicine, Health and Life Sciences, Swansea University, Swansea, Wales, United Kingdom.
Renee LutkeDepartment of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.ORCID 0000-0002-8470-7606
Amanda J NevilleEmilia Romagna Registry of Birth Defects, Center for Clinical and Epidemiological Research, University of Ferrara, Azienda Ospedaliero- Universitaria di Ferrara, Ferrara, Italy.
Ljubica OdakChildren's Hospital Zagreb, Centre of Excellence for Reproductive and Regenerative Medicine, Medical School University of Zagreb, Zagreb, Croatia.ORCID 0000-0001-9023-5142
Aurora PucciniTerritorial Care Service, Emilia Romagna Health Authority Bologna, Bologna, Italy.
Michele SantoroUnit of Epidemiology of Rare Diseases and Congenital Anomalies, Institute of Clinical Physiology, National Research Council, Pisa, Italy.
Ieuan ScanlonPublic Health Wales, Swansea, United Kingdom.
Stine K UrhojSection of Epidemiology, University of Copenhagen, Copenhagen, Denmark.ORCID 0000-0002-2069-9723
Hermien E K de WalleDepartment of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Diana WellesleyWessex Clinical Genetics Service, Princess Anne Hospital, Southampton, United Kingdom.
Joan K MorrisPopulation Health Research Institute, St George's University of London, London, United Kingdom.ORCID 0000-0002-7164-612X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Linking routinely collected healthcare administrative data is a valuable method for conducting research on morbidity outcomes, but linkage quality and accuracy needs to be assessed for bias as the data were not collected for research. The aim of this study was to describe the rates of linking data on children with and without congenital anomalies to regional or national hospital discharge databases and to evaluate the quality of the matched data. Eleven population-based EUROCAT registries participated in a EUROlinkCAT study linking data on children with a congenital anomaly and children without congenital anomalies (reference children) born between 1995 and 2014 to administrative databases including hospital discharge records. Odds ratios (OR), adjusted by region, were estimated to assess the association of maternal and child characteristics on the likelihood of being matched. Data on 102,654 children with congenital anomalies were extracted from 11 EUROCAT registries and 2,199,379 reference children from birth registers in seven regions. Overall, 97% of children with congenital anomalies and 95% of reference children were successfully matched to administrative databases. Information on maternal age, multiple birth status, sex, gestational age and birthweight were >95% complete in the linked datasets for most regions. Compared with children born at term, those born at ≤27 weeks and 28-31 weeks were less likely to be matched (adjusted OR 0.23, 95% CI 0.21-0.25 and adjusted OR 0.75, 95% CI 0.70-0.81 respectively). For children born 32-36 weeks, those with congenital anomalies were less likely to be matched (adjusted OR 0.78, 95% CI 0.71-0.85) while reference children were more likely to be matched (adjusted OR 1.28, 95% CI 1.24-1.32). Children born to teenage mothers and mothers ≥35 years were less likely to be matched compared with mothers aged 20-34 years (adjusted ORs 0.92, 95% CI 0.88-0.96; and 0.87, 95% CI 0.86-0.89 respectively). The accuracy of linkage and the quality of the matched data suggest that these data are suitable for researching morbidity outcomes in most regions/countries. However, children born preterm and those born to mothers aged <20 and ≥35 years are less likely to be matched. While linkage to administrative databases enables identification of a reference group and long-term outcomes to be investigated, efforts are needed to improve linkages to population groups that are less likely to be linked.

Indexed as

Data AccuracyPatient DischargeAdolescentChildFemaleHospitalsHumansInfant, NewbornMothersParturitionPregnancy

Identifiers

PMID37647348
PMCPMC10468043

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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.