ArticleFrontiers in cardiovascular medicine2025
A study on the global patterns in the design and development of ventricular assist devices: a visualization approach.
Article in Frontiers in cardiovascular medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Ventricular assist devices (VADs) are lifesavers for people with advanced heart failure. The design of these devices has undergone drastic changes over time with the latest designs being far more efficient, small, lightweight, and more user-friendly. This study aims to analyze publications using bibliometric analysis and see the progress and identify key themes, trends, and collaboration networks. Method: Data relevant to this study were obtained from Scopus and Web of Science databases from 1990 to 2023. Data analysis was done using Biblioshiny which is an R-based software and is part of RStudio and Microsoft Excel to analyze collaboration between countries, authors, keyword analysis, trend topics, and evolution of various themes related to this study. Results: A total of 489 published documents were analyzed, and these documents were from 158 different sources and 1,753 authors. The top contributing journals were Discussion: The latest technological advancements in VAD design are making them a more suitable choice for a large number of patients. This bibliometric work will aid in identifying the newest trends and developments in this field and highlight the areas where more research is needed. These data are crucial for driving innovation in this field and for improving the lives of patients who depend on VADs. Future studies can be conducted to explore the use of artificial intelligence and machine learning that can learn from data about patients and then adapt as per the requirements of the patients.
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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.