Evidence map›Paper›PMID 42707874›Full record

ArticleBMJ neurology open2026

DIAGnosis using NOvel technology for Subtypes In Stroke (DIAGNOSIS study): performance evaluation protocol.

Ibrahim Alghamdi, Mohammed Almubayyidh, Edoardo Gaude, David A Jenkins, Adrian R Parry-Jones

Abstract read
In one paragraph

Article in BMJ neurology open, 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

5 authors.

Ibrahim AlghamdiDivision of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.ORCID https://orcid.org/0009-0002-9695-8549
Mohammed AlmubayyidhDivision of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.ORCID https://orcid.org/0000-0003-3266-1236
Edoardo GaudeUpfront Diagnostics, Pockit Diagnostics Ltd, Cambridge, UK.
David A JenkinsDivision of Informatics Imaging and Data Science, The University of Manchester, Manchester, UK.
Adrian R Parry-JonesDivision of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Timely and accurate identification of stroke subtypes, particularly intracerebral haemorrhage (ICH) and large vessel occlusion (LVO), is essential for improving stroke outcomes. Biomarkers have shown potential in identifying these subtypes. Glial fibrillary acidic protein (GFAP), which is elevated in ICH, and D-dimer, which is associated with LVO, are promising for rapid, point-of-care identification. This study evaluates whether combining GFAP and D-dimer with clinical features improves the diagnostic accuracy for ICH and LVO. Methods and analysis: This is a multicentre, observational diagnostic accuracy study recruiting a minimum of 257 patients with suspected stroke within 6 hours of symptom onset from two UK hyperacute stroke centres. The study will integrate clinical features and point-of-care biomarker results using the LVOne test (GFAP and D-dimer) to develop diagnostic models that differentiate ICH and LVO from other stroke presentations. Patients will be identified on hospital arrival, and clinical variables and blood samples collected immediately, with the final diagnosis recorded prior to discharge. Statistical analyses will assess discrimination, calibration and clinical utility, with sensitivity, specificity and predictive values reported. Model development and reporting will follow the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis+Artificial Intelligence and the Standards for Reporting of Diagnostic Accuracy Studies guidelines. Ethics and dissemination: The study is registered with ISRCTN (ISRCTN35174477). Ethical approval has been obtained from the Yorkshire & The Humber - Leeds West Research Ethics Committee (25/YH/0102) and the Health Research Authority. Results will be disseminated via open-access peer-reviewed journals, presentations at national and international conferences and summaries for patient and public contributors.

Indexed as

NEUROPATHOLOGYNEUROPATHYNEUROUROLOGYSTROKE

Identifiers

PMID42707874
PMCPMC13548213

What OpenQuestion holds

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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.