Evidence map›Paper›PMID 42149891›Full record

ArticlePLOS digital health2026

Use of UK national health databases for detecting intra-cranial aneurysm rupture in the Risk of Aneurysm Rupture (ROAR) study.

Samuel Hall, Jacqueline Birks, Frederick Ewbank, Benjamin Gaastra, Girjia Agarwal, Harsh Bhatt, Guendalina Bonifacio, Annabel Dainton, Alexander Dando, Mohamed Elmarawany and 19 more

Abstract read
In one paragraph

Article in PLOS digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

29 authors.

Samuel HallDepartment of Neurosurgery, University Hospitals Southampton NHS Foundation Trust, Southampton, Hampshire, United Kingdom.ORCID 0000-0002-7335-6636
Jacqueline BirksCentre for Statistics in Medicine, Medical Sciences Division, University of Oxford, Oxford, Oxfordshire, United Kingdom.
Frederick EwbankDepartment of Neurosurgery, University Hospitals Southampton NHS Foundation Trust, Southampton, Hampshire, United Kingdom.
Benjamin GaastraDepartment of Neurosurgery, University Hospitals Southampton NHS Foundation Trust, Southampton, Hampshire, United Kingdom.
Girjia AgarwalDepartment of Radiology, Imperial College Healthcare NHS Trust, London, United Kingdom.ORCID 0000-0001-8909-6560
Harsh BhattNeurosurgical Department, University Hospital Wales, Cardiff, United Kingdom.
Guendalina BonifacioDepartment of Neurology, University Hospitals Southampton NHS Foundation Trust, Southampton, Hampshire, United Kingdom.
Annabel DaintonDepartment of Neurosurgery, Northern Care Alliance NHS Foundation Trust, Salford, United Kingdom.
Alexander DandoDepartment of ENT surgery, University Hospitals Dorset, Poole, Dorset, United Kingdom.
Mohamed ElmarawanyDepartment of Neurosurgery, North Bristol NHS Trust, Bristol, Avon, United Kingdom.
Cathal HannanDepartment of Neurosurgery, Walton Centre NHS Foundation Trust, Liverpool, Merseyside, United Kingdom.
Lauren HarrisDepartment of Neurosurgery, Barking Havering and Redbridge University Hospitals NHS Trust, London, United Kingdom.
Matthew HarrisDepartment of Neurology, Hampshire Hospitals NHS Foundation Trust, Winchester, Hampshire, United Kingdom.
Josephine JungDepartment of Neurosurgery, King's College Hospital NHS Foundation Trust, London, United Kingdom.
Nida KalyalDepartment of Neurosurgery, University Hospitals Sussex NHS Foundation Trust, Brighton, West Sussex, United Kingdom.
James Jm LoanDepartment of Clinical Neurosciences, NHS Lothian, Edinburgh, Lothian, United Kingdom.ORCID 0000-0002-6451-9448
David LowesNeurosurgical Department, University Hospital Wales, Cardiff, United Kingdom.
Haritha MaripiSouth West Neurosurgery Centre, University Hospitals Plymouth NHS Trust, Plymouth, Devon, United Kingdom.
Mustafa MotiwalaDepartment of Neurosurgery, North Bristol NHS Trust, Bristol, Avon, United Kingdom.ORCID 0000-0002-6416-8553
Matthew MyersDepartment of Neurosurgery, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, Yorkshire, United Kingdom.
Frazer O'BrienDepartment of Neurosurgery, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, Lancashire, United Kingdom.
Ikenna OgbuDepartment of Neurosurgery, University Hospitals of North Midlands NHS Trust, Stoke-on-Trent, Staffordshire, United Kingdom.
William PartonDepartment of Emergency Medicine, Hampshire Hospitals NHS Foundation Trust, Winchester, Hampshire, United Kingdom.
David RowlandDepartment of Neurosurgery, Barts Health NHS Trust, London, United Kingdom.
Fozia SaeedDepartment of Neurosurgery, The Leeds Teaching Hospitals NHS Trust, Leeds, Yorkshire, United Kingdom.
Eleanor TaylorDepartment of Radiology, Imperial College Healthcare NHS Trust, London, United Kingdom.
Sara VenturiniDepartment of Neurosurgery, Cambridge University Hospitals NHS Foundation Trust, Cambridge, Cambridgeshire, United Kingdom.
Diederik BultersDepartment of Neurosurgery, University Hospitals Southampton NHS Foundation Trust, Southampton, Hampshire, United Kingdom.
ROAR Collaborative

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The objective of this study was to determine the sensitivity of national databases for identifying aneurysm rupture events in patients with unruptured intracranial aneurysms and determine their suitability for follow-up for patients in the Risk of Aneurysm Rupture (ROAR) Study. ROAR is a longitudinal cohort study that has recruited 20,000 patients with unruptured intracranial aneurysms with detailed baseline clinical and imaging data collected for each participant. These patients will be followed-up using UK national databases for hospital admissions (HES-APC) and national databases of deaths (CRD) to identify aneurysm rupture events for the purpose of rupture risk prediction. To assess the suitability of national databases for this, a cohort of patients with unruptured intracranial aneurysms was identified at a single neurosurgery centre from records between 2006-2020. Patients were linked to the national databases to identify instances containing intracranial haemorrhage diagnosis codes. All returned hospital admissions underwent case note and CT scan review to confirm the true diagnosis or cause of death. Of 1,544 patients, 74 were identified to have suffered a subsequent aneurysmal rupture. The national databases of hospital admissions and deaths identified 57 hospital admissions for aneurysm rupture. The national database of deaths identified an additional 16 out-of-hospital deaths due to aneurysm rupture of which 11 (68.8%) were confirmed on post-mortem. Local hospital records identified one additional inpatient admission for aneurysm rupture. Based on the observed proportions of admissions missing from the national databases and local hospital records, an estimated 1.03 admissions for rupture were predicted to be missed by both. The estimated sensitivity of a national database search strategy for identifying admissions for aneurysm rupture was 96.6%, and 98.3% if combined with local hospital records. National databases can detect rupture events in patients with unruptured intracranial aneurysms with high sensitivity and are ideally suited to long-term follow-up in large longitudinal cohort studies.

Identifiers

PMID42149891
PMCPMC13183183

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