Evidence map›Paper›PMID 40708380›Full record

ArticlePaediatric and perinatal epidemiology2025

Phenotyping Neurodisability in Hospital Records in England: A National Birth Cohort Using Linked Administrative Data.

Ania Zylbersztejn, Philippa Rees, Rashmi D'Souza, Stuart Logan, Ayana Cant, Laura Gimeno, Vincent Nguyen, Jugnoo Rahi, Ruth Gilbert, Katie Harron and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Paediatric and perinatal epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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.

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

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

  1. Pooled it
  2. Article
  3. Article
  4. 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

11 authors.

Ania ZylbersztejnGreat Ormond Street Institute of Child Health, University College London, London, UK.ORCID https://orcid.org/0000-0003-1035-1448
Philippa ReesGreat Ormond Street Institute of Child Health, University College London, London, UK.
Rashmi D'SouzaGreat Ormond Street Institute of Child Health, University College London, London, UK.
Stuart LoganNIHR Applied Research Collaboration for the Southwest, University of Exeter Medical School, Exeter, UK.
Ayana CantGreat Ormond Street Institute of Child Health, University College London, London, UK.ORCID https://orcid.org/0009-0001-4034-4153
Laura GimenoGreat Ormond Street Institute of Child Health, University College London, London, UK.ORCID https://orcid.org/0000-0001-5456-1936
Vincent NguyenGreat Ormond Street Institute of Child Health, University College London, London, UK.
Jugnoo RahiGreat Ormond Street Institute of Child Health, University College London, London, UK.
Ruth GilbertGreat Ormond Street Institute of Child Health, University College London, London, UK.
Katie HarronGreat Ormond Street Institute of Child Health, University College London, London, UK.ORCID https://orcid.org/0000-0002-3418-2856
HOPE Study

Funding

Administrative Data Research UK ES/V000977/1Administrative Data Research UK ES/X000427/1Administrative Data Research UK ES/X003663/1National Institute for Health and Care Research NIHR202025
6 · The paper itself

Abstract

backgroundChildren with neurodisability often have complex healthcare and educational needs. Evidence from linked administrative health and education data could improve joint working between services.

objectiveTo develop a diagnostic code list to identify neurodisability in hospital admission records; to assess the representativeness of this phenotype by characterising children with hospital-recorded neurodisability and their outcomes.

methodsWe developed a national cohort of singletons born in England between 2003 and 2009, including a nested cohort of children enrolled in primary school, using linked health and education data from the Education and Child Health Insights from Linked Data (ECHILD) database. With expert clinicians, we developed an algorithm based on diagnostic information from hospital records to phenotype children with hospital-recorded neurodisability. We described rates of mortality, planned/unplanned admissions up to 11 years old, and school-recorded special educational needs (SEN) provision, as proxy measures of the complexity of a child's needs, overall and for over 40 neurodisability subgroups.

resultsOf 3,580,225 children in the birth cohort, 3.6% had hospital-recorded neurodisability by age 11. The most frequent subgroups included developmental disorders, autism, epilepsy, perinatal brain injury, and cerebral palsy. Children with hospital-recorded neurodisability had higher mortality and planned/unplanned admission rates compared with their peers, and they accounted for 26% of all planned and 14% of all unplanned hospital admissions before age 11. The nested primary school cohort included 2,956,299 pupils (82.6% of all births), 3.7% of whom had hospital-recorded neurodisability. 75% of children with hospital-recorded neurodisability had any school-recorded SEN provision, and 39% had a record of more intensive provision (compared to 30% and 2.4%, respectively, for their peers).

conclusionsWe derived a phenotype for hospital-recorded neurodisability, which affects 1 in 28 primary school children in England, with high rates of hospital admissions and SEN provision. This phenotype and its subgroups can be used by service providers and researchers to examine inequalities and inform resource and service provision.

Indexed as

Hospital RecordsNervous System DiseasesBirth CohortChildChild, PreschoolCohort StudiesEducation, SpecialEnglandFemaleHospitalizationHumansInfantMalePhenotypeadministrative datadata linkageelectronic health recordsneurodisabilityspecial educational needs

Identifiers

PMID40708380
PMCPMC12658309

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.