ArticleJournal of thoracic disease2026
Integrating bibliometric analysis and external validation of the SAVE score in VA-ECMO for refractory cardiogenic shock: insights from global trends and the MIMIC-IV database.
Article in Journal of thoracic disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Extracorporeal membrane oxygenation (ECMO) is a crucial intervention for patients with refractory cardiogenic shock, though its management is complex and carries substantial risks such as thromboembolism, hemorrhage, and infection. This study aims to provide a comprehensive overview of global research trends and to assess the clinical utility of established prognostic tools. Methods: A literature search was conducted on the Web of Science Core Collection from 1988 to 2024. The bibliometric tools VOSviewer 1.6.20, CiteSpace 6.3.R1, and the R 4.3.3 were employed to visualize collaboration networks, keyword co-occurrences, and emerging research trends. Additionally, a retrospective cohort of adult patients with refractory cardiogenic shock who received veno-arterial extracorporeal membrane oxygenation (VA-ECMO) was identified from the Medical Information Mart for Intensive Care IV (MIMIC-IV) (v2.2) database. The Survival After Veno-Arterial ECMO (SAVE) score's discrimination and calibration were externally validated in this cohort. Results: The bibliometric analysis showed that the USA led in publications [129], followed by France [96] and China [72], with Assistance Publique Hôpitaux Paris (APHP) and Institut National de la Santé et de la Recherche Médicale (INSERM) among key institutions. Major journals included Conclusions: This study underscores the performance variations of established prognostic tools across different clinical settings, suggesting that tools like the SAVE score require cautious interpretation when applied to localized cohorts. Future ECMO research in cardiogenic shock must refine management strategies, standardize guidelines, and improve prediction models through rigorous multi-center external validation. Leveraging large clinical databases such as MIMIC-IV will be essential for advancing precision medicine and optimizing outcomes in this high-risk population.
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