Evidence map›Paper›PMID 37139140›Full record

ArticleFrontiers in cardiovascular medicine2023

Non-invasive detection of severe PH in lung disease using magnetic resonance imaging.

Dheyaa Alkhanfar, Krit Dwivedi, Faisal Alandejani, Yousef Shahin, Samer Alabed, Chris Johns, Pankaj Garg, A A Roger Thompson, Alexander M K Rothman, Abdul Hameed and 5 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in cardiovascular medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
3.1field-weighted citation impact, top 8% of its field
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

5 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
  2. Sarcoidosis-Associated Pulmonary Hypertension.Journal of clinical medicine · 2024
    Review
  3. Review
  4. Review
  5. 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

15 authors at 3 institutions in 1 country.

Dheyaa AlkhanfarDepartment of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom.
Krit DwivediDepartment of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom.
Faisal AlandejaniDepartment of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom.
Yousef ShahinDepartment of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom.
Samer AlabedDepartment of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom.
Chris JohnsDepartment of Clinical Radiology, Sheffield Teaching Hospitals, Sheffield, United Kingdom.
Pankaj GargSheffield Pulmonary Vascular Disease Unit, Royal Hallamshire Hospital, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, United Kingdom.
A A Roger ThompsonDepartment of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom.
Alexander M K RothmanDepartment of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom.
Abdul HameedSheffield Pulmonary Vascular Disease Unit, Royal Hallamshire Hospital, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, United Kingdom.
Athanasios CharalampopoulosSheffield Pulmonary Vascular Disease Unit, Royal Hallamshire Hospital, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, United Kingdom.
Jim M WildDepartment of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom.
Robin CondliffeSheffield Pulmonary Vascular Disease Unit, Royal Hallamshire Hospital, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, United Kingdom.
David G KielyINSIGNEO, Institute for in Silico Medicine, University of Sheffield, Sheffield, United Kingdom.
Andrew J SwiftDepartment of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom.
University of Sheffield · GBRoyal Hallamshire Hospital · GBSheffield Teaching Hospitals NHS Foundation Trust · GB

Funding

British Heart Foundation FS/18/13/33281Wellcome Trust 205188/Z/16/Z
6 · The paper itself

Abstract

Introduction: Severe pulmonary hypertension (mean pulmonary artery pressure ≥35 mmHg) in chronic lung disease (PH-CLD) is associated with high mortality and morbidity. Data suggesting potential response to vasodilator therapy in patients with PH-CLD is emerging. The current diagnostic strategy utilises transthoracic Echocardiography (TTE), which can be technically challenging in some patients with advanced CLD. The aim of this study was to evaluate the diagnostic role of MRI models to diagnose severe PH in CLD. Methods: 167 patients with CLD referred for suspected PH who underwent baseline cardiac MRI, pulmonary function tests and right heart catheterisation were identified. In a derivation cohort ( Results: The CLD-PH MRI model [= (-13.104) + (13.059 * VMI)-(0.237 * PA RAC) + (0.083 * Systolic Septal Angle)], had high accuracy in the test cohort (area under the ROC curve (0.91) ( Conclusion: The CLD-PH MRI model and Whitfield model have high accuracy to detect severe PH in CLD, and have strong prognostic value.

Indexed as

cardiac MRIchronic lung disease (CLD)COPDILDsevere PH

Identifiers

PMID37139140
PMCPMC10149807
OpenAlexW4366213308

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.