Evidence map›Paper›PMID 39111972›Full record

ArticleJournal of the American College of Cardiology2024

Myocardial Strain Measured by Cardiac Magnetic Resonance Predicts Cardiovascular Morbidity and Death.

Sucharitha Chadalavada, Kenneth Fung, Elisa Rauseo, Aaron M Lee, Mohammed Y Khanji, Alborz Amir-Khalili, Jose Paiva, Hafiz Naderi, Shantanu Banik, Mihaela Chirvasa and 3 more

Abstract read
In one paragraph

Article in Journal of the American College of Cardiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

32 citing papers in PubMed.

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  5. Genetic analysis of imaging-derived phenotypes.Nature reviews. Genetics · 2026
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  14. Unsupervised Cardiac Video Translation Via Motion Feature Guided Diffusion Model.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2026
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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

13 authors.

Sucharitha ChadalavadaWilliam Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, United Kingdom.
Kenneth FungWilliam Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, United Kingdom.
Elisa RauseoWilliam Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, United Kingdom.
Aaron M LeeWilliam Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, United Kingdom.
Mohammed Y KhanjiWilliam Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, United Kingdom.
Alborz Amir-KhaliliCircle Cardiovascular Imaging Inc, Calgary, Alberta, Canada.
Jose PaivaWilliam Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, United Kingdom.
Hafiz NaderiWilliam Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, United Kingdom.
Shantanu BanikCircle Cardiovascular Imaging Inc, Calgary, Alberta, Canada.
Mihaela ChirvasaCircle Cardiovascular Imaging Inc, Calgary, Alberta, Canada.
Magnus T JensenSteno Diabetes Center Copenhagen, Copenhagen, Denmark.
Nay AungWilliam Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, United Kingdom.
Steffen E PetersenWilliam Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, United Kingdom; Health Data Research UK, London, United Kingdom; Alan Turing Institute, The British Library, John Dodson House, London, United Kingdom. Electronic address: s.e.petersen@qmul.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMyocardial strain using cardiac magnetic resonance (CMR) is a sensitive marker for predicting adverse outcomes in many cardiac disease states, but the prognostic value in the general population has not been studied conclusively.

objectivesThe goal of this study was to assess the independent prognostic value of CMR feature tracking (FT)-derived LV global longitudinal (GLS), circumferential (GCS), and radial strain (GRS) metrics in predicting adverse outcomes (heart failure, myocardial infarction, stroke, and death).

methodsParticipants from the UK Biobank population imaging study were included. Univariable and multivariable Cox models were used for each outcome and each strain marker (GLS, GCS, GRS) separately. The multivariable models were tested with adjustment for prognostically important clinical features and conventional global LV imaging markers relevant for each outcome.

resultsOverall, 45,700 participants were included in the study (average age 65 ± 8 years), with a median follow-up period of 3 years. All univariable and multivariable models demonstrated that lower absolute GLS, GCS, and GRS were associated with increased incidence of heart failure, myocardial infarction, stroke, and death. All strain markers were independent predictors (incrementally above some respective conventional LV imaging markers) for the morbidity outcomes, but only GLS predicted death independently: (HR: 1.18; 95% CI: 1.07-1.30).

conclusionsIn the general population, LV strain metrics derived using CMR-FT in radial, circumferential, and longitudinal directions are strongly and independently predictive of heart failure, myocardial infarction, and stroke, but only GLS is independently predictive of death in an adult population cohort.

Indexed as

Magnetic Resonance Imaging, CineAgedCardiovascular DiseasesFemaleHumansMaleMiddle AgedPredictive Value of TestsPrognosisUnited Kingdomcardiac magnetic resonancecircumferential strainlongitudinal strainradial strainsurvival analysis

Identifiers

PMID39111972
PMCPMC11320766

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Registered trials

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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.