Steffen E Petersen

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Queen Mary University of London
Country flagUnited Kingdom

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Recent Grants

Grant: Open

Barts Precision Medicine Academy: Developing academic clinical lecturer posts for medics, nurses and allied professionals

Open Date: 2024-10-01

Close Date: 2028-09-01

Grant: Close

Towards automating cardiac magnetic resonance analysis and interpretation and reducing need for contrast administration in inflammatory cardiomyopathies

Open Date: 2023-10-01

Close Date: 2026-09-01

Grant: Close

Unravelling the environmental determinants of biological aging across the heart-brain axis

Open Date: 2023-08-01

Close Date: 2024-05-01

Grant: Close

Understanding the mechanistic role of obesity and air pollution as common causal agents of heart and brain disease using multiorgan imaging in the UK Biobank

Open Date: 2023-05-01

Close Date: 2025-04-01

Grant: Close

An international multi-centre collaborative for development of healthy reference ranges from cardiovascular magnetic resonance

Open Date: 2023-02-01

Close Date:

Articles (9)

Year:

2023

Year:

2023

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2023

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2023

Year:

2023

Aims Left ventricular systolic dysfunction (LSVD) is a heterogeneous condition with several factors influencing prognosis. Better phenotyping of asymptomatic individuals can inform preventative strategies. This study aims to explore the clinical phenotypes of LVSD in initially asymptomatic subjects and their association with clinical outcomes and cardiovascular abnormalities through multi-dimensional data clustering. Methods and results Clustering analysis was performed on 60 clinically available variables from 1563 UK Biobank participants without pre-existing heart failure (HF) and with left ventricular ejection fraction (LVEF) < 50% on cardiovascular magnetic resonance (CMR) assessment. Risks of developing HF, other cardiovascular events, death, and a composite of major adverse cardiovascular events (MACE) associated with clusters were investigated. Cardiovascular imaging characteristics, not included in the clustering analysis, were also evaluated. Three distinct clusters were identified, differing considerably in lifestyle habits, cardiovascular risk factors, electrocardiographic parameters, and cardiometabolic profiles. A stepwise increase in risk profile was observed from Cluster 1 to Cluster 3, independent of traditional risk factors and LVEF. Compared with Cluster 1, the lowest risk subset, the risk of MACE ranged from 1.42 [95% confidence interval (CI): 1.03–1.96; P < 0.05] for Cluster 2 to 1.72 (95% CI: 1.36–2.35; P < 0.001) for Cluster 3. Cluster 3, the highest risk profile, had features of adverse cardiovascular imaging with the greatest LV re-modelling, myocardial dysfunction, and decrease in arterial compliance. Conclusions Clustering of clinical variables identified three distinct risk profiles and clinical trajectories of LVSD amongst initially asymptomatic subjects. Improved characterization may facilitate tailored interventions based on the LVSD sub-type and improve clinical outcomes.

Year:

2023

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2023

Year:

2023

Year:

2023

Collaborators (8)

Lin Wang

Lecturer

Queen Mary University of London

UNITED KINGDOM
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Stefan Neubauer

University of Oxford

UNITED KINGDOM
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Sanjeev Bhattacharyya

Queen Mary University of London

UNITED KINGDOM
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Liliana Szabo

Queen Mary University of London

UNITED KINGDOM
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Andrew King

King’s College London

UNITED KINGDOM
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Thomas E. Nichols

University of Oxford

UNITED KINGDOM
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Betty Raman

Associate Professor of Cardiovascular Medicine

University of Oxford Radcliffe Department of Medicine

UNITED KINGDOM
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Julia Ramirez

Universidad de Zaragoza

SPAIN
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