Evidence map›Paper›PMID 40877031›Full record

ArticleHeart (British Cardiac Society)2026

Analysis and prediction of cardiovascular research hotspots, trends and interdisciplinarity.

Zeye Liu, Ziping Li, Hong Jiang, Guangyu Pan, Wenchao Li, Fengwen Zhang, Wen-Bin Ou-Yang, Shouzheng Wang, Cheng Wang, Xuanqi An and 7 more

Abstract read
In one paragraph

Article in Heart (British Cardiac Society), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

17 authors.

Zeye Liu *Department of Cardiac Surgery, Peking University People's Hospital, Peking University, Beijing, China.
Ziping Li *Department of Structural Heart Disease, National Center for Cardiovascular Disease, China & Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Hong Jiang *Department of Structural Heart Disease, National Center for Cardiovascular Disease, China & Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Guangyu Pan *Department of Cardiac Surgery, Peking University People's Hospital, Peking University, Beijing, China.
Wenchao LiZhengzhou University People's Hospital, Zhengzhou, Henan, China.
Fengwen ZhangDepartment of Structural Heart Disease, National Center for Cardiovascular Disease, China & Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Wen-Bin Ou-YangDepartment of Structural Heart Disease, National Center for Cardiovascular Disease, China & Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Shouzheng WangDepartment of Structural Heart Disease, National Center for Cardiovascular Disease, China & Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Cheng WangDepartment of Structural Heart Disease, National Center for Cardiovascular Disease, China & Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Xuanqi AnDepartment of Structural Heart Disease, National Center for Cardiovascular Disease, China & Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Anlin DaiNational Engineering Research Center for Medical Big Data Application Technology, Chinese PLA General Hospital, Beijing, China.
Ruibing XiaUniversity Hospital Munich Department of Cardiology - Medical Clinic and Polyclinic I, Munich, Germany.
Yakun LiAcademic Medical Centre, Amsterdam, The Netherlands.
Xiaochun SunNational Engineering Research Center for Medical Big Data Application Technology, Chinese PLA General Hospital, Beijing, China chengliangyin@163.com panxiangbin@fuwaihospital.org shiyi1088@126.com sunxc20@163.com.
Yi ShiDepartment of Cardiac Surgery, Peking University People's Hospital, Peking University, Beijing, China chengliangyin@163.com panxiangbin@fuwaihospital.org shiyi1088@126.com sunxc20@163.com.
Chengliang YinNational Engineering Research Center for Medical Big Data Application Technology, Chinese PLA General Hospital, Beijing, China chengliangyin@163.com panxiangbin@fuwaihospital.org shiyi1088@126.com sunxc20@163.com.ORCID 0000-0001-8262-5749
Xiang-Bin PanDepartment of Structural Heart Disease, National Center for Cardiovascular Disease, China & Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China chengliangyin@163.com panxiangbin@fuwaihospital.org shiyi1088@126.com sunxc20@163.com.ORCID 0000-0003-2746-4481

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveComprehensive data and analyses on cardiovascular research could clarify recent research trends for the academic community and facilitate policy development. We examined publications and reference data to identify research topics, trends and interdisciplinarity for cardiovascular disease (CVD).

methodsWe extracted and clustered text fragments from the titles and abstracts of 2 512 445 publications using artificial intelligence techniques, including natural language processing (NLP) for semantic analysis. Cardiovascular experts identified topics and document clusters based on the output of those semiautomatic methods. We also applied machine learning algorithms to predict the trends over the next 5 years in each field. We examined the crossover between the two cluster groups using citation relationships in the documents.

resultsResearch in clinical studies showed the most notable increase; that was followed by research in population and basic studies. The research hotspots were minimally invasive treatments for valve disease, circulatory haemodynamics, and prevention and control of hypertension. The fastest-growing topics were health monitoring, evidence-based medicine and immunotherapy. We found extensive crossover relationships among document clusters for the periods of 2017-2018 and 2020-2021.

conclusionsThis study provides valuable insights into the research hotspots for cardiovascular research, including an increasing emphasis on early disease detection and prevention, exploration of minimally invasive treatments and assessment of risk factors. The research landscape demonstrates signs of interdisciplinarity and integration as reflected in citation relationships. These findings suggest practical implications for optimising resource allocation in healthcare systems, guiding clinical guideline updates and informing policy-making to prioritise high-impact research areas aligned with evolving CVD challenges. Given the evolving global burden of CVD, continuous research and innovation are imperative, with interdisciplinary collaboration assuming a pivotal role in advancing scientific knowledge.

Indexed as

Biomedical ResearchCardiologyCardiovascular DiseasesInterdisciplinary ResearchHumansInterdisciplinary CommunicationNatural Language ProcessingCardiovascular DiseasesEducation, MedicalResearch Design

Identifiers

PMID40877031
PMCPMC13018832

What OpenQuestion 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 OpenQuestion graph.