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Updated: Jan 11, 2026

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
Published on: February 13, 2021
Heart failure with preserved ejection fraction and exercise: a review based on bibliometric analysis from 2010 to
Qianyu Chen1, Sikun Yin1, Zujie Xu1
1School of Physical Education and Health Engineering, Taiyuan University of Technology, 030024, Taiyuan, Shanxi, China.
Background:
Heart failure with preserved ejection fraction (HFpEF) affects over half of heart failure cases, leading to high mortality and exercise intolerance, significantly impacting elderly patients' daily life. Consequently, exercise tolerance in HFpEF patients is a key research focus.
Objectives And Methods:
Using CiteSpace 6.3.R1, this study analyzed Web of Science Core Collection literature, examining publication volume, journals, countries, institutions, authors, keywords, and co-citation timelines to summarize hotspots, trends, and frontiers in HFpEF and exercise research.
Results And Conclusions:
1. A total of 2438 papers were included, with publication volume rising over the past 15 years. 2. In HFpEF and exercise research, the USA leads via a "high-yield platform-academic leader" model, with institutions like Mayo Clinic and scholars such as Borlaug Barry A. Germany's dual-core institutions (German Centre for Cardiovascular Research and the Berlin Institute of Health) drive European mechanistic studies. Imperial College London engages in regional collaboration with France's APHP. Asia, with key researchers such as Lam Carolyn SP from Singapore, sees growing influence from China, Japan, and South Korea, forming a "North American dominance, European collaboration, Asian rise" landscape. 3. Since 2010, HFpEF research has expanded beyond single lesions, forming "pathology-assessment-comorbidity" and "imaging-intervention-metabolism" themes. 4. Future focus: (1) Multi-omics-based HFpEF subtypes and personalized exercise algorithms; (2) Drug and non-drug strategies focused on exercise and nutrition; (3) Cross-regulation of inflammatory-metabolic pathways and interdisciplinary diagnosis; (4) A transcontinental database for racial metabolic differences, long-term follow-up, and AI-driven upgrades to evidence-based exercise; (5) Digital quantification for closed-loop health management.
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