Evidence map›Paper›PMID 39730195›Full record

Observational studyArchives of disease in childhood. Fetal and neonatal edition2025

Improving outcomes for very preterm babies in England: does place of birth matter? Findings from OPTI-PREM, a national cohort study.

Thillagavathie Pillay, Sarah E Seaton, Miaoqing Yang, Vasiliki Bountziouka, Victor Banda, Helen Campbell, Kelvin Dawson, Bradley N Manktelow, Elizabeth S Draper, Neena Modi and 4 more

Registry-linked trialAbstract readObservational Study
In one paragraph

Observational study in Archives of disease in childhood. Fetal and neonatal edition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02994849 (OPTI-Prem), which is not on this map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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.

NCT02994849 completednot on this map

OPTI-Prem: Optimising Neonatal Service Provision for Preterm Babies Born Between 27 and 31 Weeks of Gestation in England Using National Data, Qualitative Research and Economic Analysis

TypeobservationalSponsorThe Royal Wolverhampton Hospitals NHS TrustRan2017 to 2022Enrolled4,364ConditionsNeonatal Diseases and Abnormalities
3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

14 authors.

Thillagavathie Pillay *Faculty of Science and Engineering, University of Wolverhampton, Wolverhampton, UK tilly.pillay@uhl-tr.nhs.uk.ORCID http://orcid.org/0000-0002-4159-3282
Sarah E SeatonDepartment of Population Health Sciences, University of Leicester College of Life Sciences, Leicester, UK.ORCID http://orcid.org/0000-0001-8711-4817
Miaoqing YangUniversity of Leeds, Leeds, UK.ORCID http://orcid.org/0000-0001-7975-374X
Vasiliki BountzioukaComputer Simulations, Genomics and Data Analysis Laboratory, Department of Food Science and Nutrition, University of the Aegean, Mytilene, Greece.
Victor BandaData, Research, Innovation and Virtual Environment, Great Ormond Street Hospital for Children, London, UK.
Helen CampbellNuffield Department of Population Health, University of Oxford National Perinatal Epidemiology Unit, Oxford, UK.ORCID http://orcid.org/0000-0003-2070-7794
Kelvin DawsonResearch and Development, BLISS, Royal Wolverhampton Hospitals NHS Trust, Wolverhampton, UK.
Bradley N ManktelowDepartment of Population Health Sciences, University of Leicester College of Life Sciences, Leicester, UK.
Elizabeth S DraperDepartment of Population Health Sciences, University of Leicester College of Life Sciences, Leicester, UK.
Neena ModiNeonatal Medicine, School of Public Health, Chelsea and Westminster Hospital Campus, Imperial College London, London, UK.ORCID http://orcid.org/0000-0002-2093-0681
Elaine M BoyleDepartment of Population Health Sciences, University of Leicester College of Life Sciences, Leicester, UK.ORCID http://orcid.org/0000-0002-5038-3148
Oliver Rivero-Arias *Nuffield Department of Population Health, University of Oxford National Perinatal Epidemiology Unit, Oxford, UK.ORCID http://orcid.org/0000-0003-2233-6544
OPTI-PREM study group
Contributing neonatal units and leads

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveBabies born between 27

designRetrospective national cohort study.

settingLNU, NICU, England. PATIENTS: UK National Neonatal Research Database whole population data for births between 27 OUTCOME MEASURES: Death during neonatal care, up to 1 year (infant mortality), surgically treated necrotising enterocolitis, retinopathy of prematurity, severe brain injury (SBI), bronchopulmonary dysplasia.

interventionBirth in NICU versus LNU setting. We used an instrumental variable (maternal excess travel time between the nearest NICU and LNU) estimation approach to determine treatment effect.

resultsOf 18 847 babies (NICU: 10 379; LNU: 8468), 574 died in NICU/LNU care, and 121 postdischarge (infant mortality 3.7%). We found no effect of birth setting on neonatal or infant mortality. Significantly more babies born into LNU settings experienced SBI (mean difference -1.1% (99% CI -2.2% to -0.1%)). This was attenuated after excluding births at 27 weeks, and early postnatal transfers.

conclusionsIn England, LNU teams should use clinical judgement, risk assessing benefits of transfer versus risk of SBI for preterm births at 27 weeks of gestation. 28 weeks of gestation is a safe threshold for preterm birth in either NICU/LNU settings. TRIAL REGISTRATION NUMBER: NCT02994849/ISRCTN74230187.

Indexed as

Infant, Extremely PrematureInfant, Premature, DiseasesIntensive Care Units, NeonatalEnglandFemaleGestational AgeHumansInfantInfant MortalityInfant, NewbornMaleRetrospective StudiesIntensive Care Units, NeonatalMortalityNeonatology

Identifiers

PMID39730195
PMCPMC12418565

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Registered trials

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.