Key result
ACS revascularization risk research shifts predominantly toward PCI, while annual publication growth slows to ~7%.
Why the study?
Although risk stratification and prognostic prediction are embedded in revascularization practice for acute coronary syndromes, the longitudinal evolution and scientific architecture of this literature remain poorly characterized.
This bibliometric analysis demonstrates that prognostic assessment in acute coronary syndromes has evolved primarily within percutaneous coronary intervention practice, with SYNTAX, TIMI, and GRACE dominating historical literature while machine learning and high bleeding risk concepts rapidly emerge.
Answers are grounded in this paper and cite their sources.
Maps ACS risk stratification literature evolution; extends conceptual architecture analysis and leaves open instrument validation in revascularization practice.
Background/Objectives: Risk stratification and prognostic prediction are embedded in revascularization practice for acute coronary syndromes, but the longitudinal evolution and scientific architecture of this literature remain poorly characterized. We mapped growth, contributors, conceptual structure, and named instruments. Methods: English-language articles and reviews indexed in the Web of Science Core Collection from 1975 to 2025 were retrieved with a three-block Topic search (n = 10,390; 9608 articles, 782 reviews). Bibliometric performance, collaboration, source impact, keyword co-occurrence (validated thesaurus), named instrument and clinical setting terms, and metadata completeness were analyzed with VOSviewer, Bibliometrix/Biblioshiny, and Python. Annual output was modeled by changepoint detection with bootstrap localization. Results: Annual output rose from 8 records in 1988 to 843 in 2025; the principal transition was a slowdown in proportional growth around 2009, from approximately 16.5% to 6.9% annually, reproduced on the 1991–2025 series. The United States led output, citations, and collaboration strength; China ranked second in volume, with the youngest output among the leading countries (median year 2022) and year-normalized citation impact of 0.78 versus 1.43 for the United States (corpus average 1.0). A 92-keyword network formed five clusters centered on percutaneous coronary intervention (PCI). SYNTAX, TIMI, and GRACE were the most frequently named scores, and machine learning terminology grew fastest (53 records in 2025). Records naming ST-segment elevation myocardial infarction alone (33.9%) outnumbered those naming non-ST-elevation presentations alone (13.7%), and 75.7% mentioned PCI without bypass surgery. Conclusions: These patterns suggest that prognostic assessment has developed primarily within revascularization practice rather than as an independent methodological field; machine learning and high bleeding risk terminology are emerging below the keyword map threshold.
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Bogdan et al. (2026) studied Acute coronary syndromes undergoing coronary revascularization (n=10,390). Changepoint-enhanced bibliometric and science-mapping analysis was evaluated on Bibliometric performance, annual output growth transitions, conceptual keyword structure, and named prognostic instruments. Bibliometric analysis of 10,390 ACS revascularization risk records showed annual growth slowed around 2009 from 16.5% to 6.9%, with 75.7% mentioning PCI alone and machine learning growing fastest.
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