ArticleAnnals of translational medicine2020
Development and trend in the field of valvular heart disease in China: an analysis based on the National Natural Science Foundation of China.
Article in Annals of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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.
Who cites it
6 citing papers in PubMed.
- Advancements and Perspectives in the Bioprosthetic Heart Valve: A Comprehensive Review on Biomaterial Processing and Emerging Polymeric Materials.Journal of the American Heart Association · 2025Review
- Biomechanical Scaffolds of Decellularized Heart Valves Modified by Electrospun Polylactic Acid.Applied biochemistry and biotechnology · 2024Article
- Soft Biomimetic Approach for the Development of Calcinosis-Resistant Glutaraldehyde-Fixed Biomaterials for Cardiovascular Surgery.Biomimetics (Basel, Switzerland) · 2023Article
- Low-Density Lipoprotein Cholesterol and Mortality Risk in Elderly Patients Undergoing Valve Replacement Surgery: A Propensity Score Matching Analysis.Frontiers in nutrition · 2022Article
- Mechanisms and Drug Therapies of Bioprosthetic Heart Valve Calcification.Frontiers in pharmacology · 2022Review
- Overview of Graves Ophthalmopathy Literature From 1999 to 2019: Bibliometric Analysis.Interactive journal of medical research · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNational Natural Science Foundation of China (NSFC) plays a vital role promoting advancement of science in China. The incidence and mortality rate of valvular heart disease (VHD) increase with aging population. Therefore, it is of significance to discuss the development and trend in the field of VHD and provide references for scholars to carry out further Foundations.
methodsInternet-based Science Information System and other websites were used to search for projects supported by NSFC related to VHD in 2008-2019 and related information of applicants. Publications, citations and impact factors were queried by Google Scholar and InCites Journal Citation Reports 2.0 and analyzed by SPSS for Windows version 24.0. Key words extracted from these project titles were imported into Citespace for analysis.
resultsA total of 117 projects and related information were acquired. Although the annual amount of projects and funding has fluctuated in recent years, they still maintained an upward trend. Institutes were mainly distributed over Hubei Province, Shanghai and Jiangsu Province. Applicants characterized as senior title, male, cardiac surgeon have accounted for a larger proportion of projects, with a greater amount of funding. Through the analysis of keywords and subject distribution, molecular-biology-based mechanism study combined with tissue engineering has become the principal research hot spot and trend in recent years. Annual changes in output in scientific research were consistent with changes in the amount of funding.
conclusionsThis paper collated funding situation supported by NSFC in VHD, analyzed distribution of keywords and summarized the research trend, so as to supply guidance to researchers for advanced researches.
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Registered trials
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.