Evidence map›Paper›PMID 42882413›Full record

ArticleDiagnostics (Basel, Switzerland)2026

Automated CMR Quantification of Pulmonary Artery Size-Based and Slow-Flow Metrics in Pulmonary Hypertension.

Khalid Alghamdi, Alireza Hokmabadi, Rob van der Geest, Pankaj Garg, Turki Alnasser, Daniel J Taylor, Michael Sharkey, Smitha Rajaram, David G Kiely, Samer Alabed and 1 more

Abstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 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

11 authors.

Khalid AlghamdiSchool of Medicine & Population Health, The University of Sheffield, Sheffield S10 2TN, UK.ORCID 0009-0002-6518-750X
Alireza HokmabadiSchool of Medicine & Population Health, The University of Sheffield, Sheffield S10 2TN, UK.ORCID 0000-0002-1407-4540
Rob van der GeestDivision of Image Processing, Department of Radiology, Leiden University Medical Centre, 2333 Leiden, The Netherlands.ORCID 0000-0002-9084-5597
Pankaj GargNorwich Medical School, Faculty of Medicine and Health Sciences, University of East Anglia, Norwich NR4 7TJ, UK.ORCID 0000-0002-5483-169X
Turki AlnasserSchool of Medicine & Population Health, The University of Sheffield, Sheffield S10 2TN, UK.
Daniel J TaylorSchool of Medicine & Population Health, The University of Sheffield, Sheffield S10 2TN, UK.
Michael SharkeySchool of Medicine & Population Health, The University of Sheffield, Sheffield S10 2TN, UK.ORCID 0000-0001-9851-0014
Smitha RajaramSchool of Medicine & Population Health, The University of Sheffield, Sheffield S10 2TN, UK.
David G KielySchool of Medicine & Population Health, The University of Sheffield, Sheffield S10 2TN, UK.ORCID 0000-0003-0184-6502
Samer AlabedSchool of Medicine & Population Health, The University of Sheffield, Sheffield S10 2TN, UK.ORCID 0000-0002-9960-7587
Andrew J SwiftSchool of Medicine & Population Health, The University of Sheffield, Sheffield S10 2TN, UK.

Funding

British Heart Foundation FS/SCRF/24/32034National Institute for Health and Care Research AI_AWARD01706National Institute for Health and Care Research NIHR203321Wellcome TrustWellcome Trust 223521/Z/21/Z
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

automated quantificationautomated segmentationcardiovascular magnetic resonancedeep learningpulmonary arterypulmonary hypertensionslow-flow

Identifiers

PMID42882413
PMCPMC13664574

What OpenQuestion holds

Textmetadata
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.