Background: Cardiac electrophysiology research has expanded rapidly, yet its global distribution, collaborative dynamics, and thematic evolution have never been quantified across the full history of the field. Mapping these patterns is crucial for guiding funding and designing impactful studies.
Methods: A scientometrics analysis was conducted on articles indexed in Scopus, Web of Science, and PubMed (1959– 2025). After screening, 3766 peer-reviewed papers were analyzed. Publication trends, citation-based indicators (h-index, which reflects productivity and impact; g-index, which highlights highly cited work; and m-index, which adjusts for time), journal quartiles, World Bank income-levels, and WHO regions were quantified. Co-authorship networks mapped institutional and national partnerships, while text-mining tracked keyword trajectories to identify emerging research fronts.
Results: Annual publications increased from 3 in 1959 to 268 in 2021. Articles averaged six co-authors, with 25% showing international collaboration. High-income countries produced 86.7% of output and dominated journals’ impact (mean h-index = 155). In contrast, lower-middle-income nations contributed only 1.9%. The University of California and the United States were central collaboration hubs, while Africa and Latin America remained peripheral. Keyword analysis showed a shift from pharmacology and in-vitro biophysics to newer areas such as implantable devices, artificial intelligence–guided risk scoring, and stem cell–based models. Emerging concepts such as Bayes theorem (for probabilistic modeling) and quantitative trait locus (for linking genetics to arrhythmia risk) are beginning to appear, though still scarcely represented. Cross-continental papers received the highest citation density.
Conclusion: Cardiac electrophysiology knowledge is concentrated in high-income regions and in teams with strong collaboration. This map highlights geographic blind spots and emerging themes, offering a practical guide for building north–south consortia, focusing on neglected pathologies, and investing in artificial intelligence and stem-cell–based strategies likely to drive the next breakthroughs.
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