Evidence map›Paper›PMID 38943084›Full record

ArticleBMC cardiovascular disorders2024

Pulmonary transit time is a predictor of outcomes in heart failure: a cardiovascular magnetic resonance first-pass perfusion study.

Jonathan Farley, Louise Ae Brown, Pankaj Garg, Ali Wahab, Joel Rl Klassen, Nicholas Jex, Sharmaine Thirunavukarasu, Amrit Chowdhary, Noor Sharrack, Miroslawa Gorecka and 8 more

Abstract read
In one paragraph

Article in BMC cardiovascular disorders, 2024. 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
–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

5 citing papers in PubMed.

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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

18 authors.

Jonathan FarleyMultidisciplinary Cardiovascular Research Centre, Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9JT, UK.
Louise Ae BrownMultidisciplinary Cardiovascular Research Centre, Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9JT, UK.
Pankaj GargNorwich Medical School, University of East Anglia, Norfolk, UK.
Ali WahabMultidisciplinary Cardiovascular Research Centre, Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9JT, UK.
Joel Rl KlassenMultidisciplinary Cardiovascular Research Centre, Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9JT, UK.
Nicholas JexMultidisciplinary Cardiovascular Research Centre, Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9JT, UK.
Sharmaine ThirunavukarasuMultidisciplinary Cardiovascular Research Centre, Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9JT, UK.
Amrit ChowdharyMultidisciplinary Cardiovascular Research Centre, Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9JT, UK.
Noor SharrackMultidisciplinary Cardiovascular Research Centre, Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9JT, UK.
Miroslawa GoreckaMultidisciplinary Cardiovascular Research Centre, Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9JT, UK.
Hui XueNational Institutes for Health, National Heart, Lung, and Blood Institute, Bethesda, USA.
Nigel ArtisDepartment of Cardiology, Mid Yorkshire Hospitals NHS Trust, Wakefield, UK.
Eylem LeveltMultidisciplinary Cardiovascular Research Centre, Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9JT, UK.
Erica Dall'ArmellinaMultidisciplinary Cardiovascular Research Centre, Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9JT, UK.
Peter KellmanNational Institutes for Health, National Heart, Lung, and Blood Institute, Bethesda, USA.
John P GreenwoodMultidisciplinary Cardiovascular Research Centre, Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9JT, UK.
Sven PleinMultidisciplinary Cardiovascular Research Centre, Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9JT, UK.
Peter P SwobodaMultidisciplinary Cardiovascular Research Centre, Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9JT, UK. p.swoboda@leeds.ac.uk.

Funding

Gadgetron Global Network and Intelligence Computing: Clinical Imaging Application Development and Software InfrastructureZIAHL006214 · NHLBI · NATIONAL HEART, LUNG, AND BLOOD INSTITUTE · PI KELLMAN, PETER · 2016 to 2025
$7.3M
6 · The paper itself

Abstract

backgroundPulmonary transit time (PTT) can be measured automatically from arterial input function (AIF) images of dual sequence first-pass perfusion imaging. PTT has been validated against invasive cardiac catheterisation correlating with both cardiac output and left ventricular filling pressure (both important prognostic markers in heart failure). We hypothesized that prolonged PTT is associated with clinical outcomes in patients with heart failure.

methodsWe recruited outpatients with a recent diagnosis of non-ischaemic heart failure with left ventricular ejection fraction (LVEF) < 50% on referral echocardiogram. Patients were followed up by a review of medical records for major adverse cardiovascular events (MACE) defined as all-cause mortality, heart failure hospitalization, ventricular arrhythmia, stroke or myocardial infarction. PTT was measured automatically from low-resolution AIF dynamic series of both the LV and RV during rest perfusion imaging, and the PTT was measured as the time (in seconds) between the centroid of the left (LV) and right ventricle (RV) indicator dilution curves.

resultsPatients (N = 294) were followed-up for median 2.0 years during which 37 patients (12.6%) had at least one MACE event. On univariate Cox regression analysis there was a significant association between PTT and MACE (Hazard ratio (HR) 1.16, 95% confidence interval (CI) 1.08-1.25, P = 0.0001). There was also significant association between PTT and heart failure hospitalisation (HR 1.15, 95% CI 1.02-1.29, P = 0.02) and moderate correlation between PTT and N-terminal pro B-type natriuretic peptide (NT-proBNP, r = 0.51, P < 0.001). PTT remained predictive of MACE after adjustment for clinical and imaging factors but was no longer significant once adjusted for NT-proBNP.

conclusionsPTT measured automatically during CMR perfusion imaging in patients with recent onset non-ischaemic heart failure is predictive of MACE and in particular heart failure hospitalisation. PTT derived in this way may be a non-invasive marker of haemodynamic congestion in heart failure and future studies are required to establish if prolonged PTT identifies those who may warrant closer follow-up or medicine optimisation to reduce the risk of future adverse events.

Indexed as

Heart FailureMyocardial Perfusion ImagingPredictive Value of TestsStroke VolumeVentricular Function, LeftAgedFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedNatriuretic Peptide, BrainPeptide FragmentsPrognosisPulmonary ArteryPulmonary CirculationNatriuretic Peptide, BrainPeptide Fragmentspro-brain natriuretic peptide (1-76)Heart failureMachine learningPerfusion imagingPulmonary transit time

Identifiers

PMID38943084
PMCPMC11212156

What Socratic holds

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LicenceCC BY
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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 Socratic graph.