Coronary slow flow research: a bibliometric analysis.

BACKGROUND: Studies on coronary slow flow are receiving increasing attention, but objective evaluations are still lacking. The purpose of this study was to visualize the current status and research hotspots of coronary slow flow through bibliometric analysis. METHODS: All relevant publications on coronary slow flow from 2003 to 2022 were extracted from the Web of Science Core Collection database and analyzed by VOSviewer and CiteSpace visualization software. Year of publication, journal, country/region, institution, and first author of each paper, as well as research hotspots were identified. RESULTS: A total of 913 publications were retrieved. The journal with the most publications was Coronary Artery Disease. The country/region with the most publications was Turkey, followed by China and the United States. The institution with the largest publication volume was Turkey Specialized Higher Education Research Hospital. The author with the largest publication volume was Chun-Yan Ma from China. Keyword analysis indicated that "treatment and prognosis", "pathogenesis and risk factors" and "diagnosis" were the clustering centers of coronary slow flow, and the research hotspots gradually changed with time, from pathogenesis to treatment and prognosis. CONCLUSION: Future research will focus on the search for effective and non-invasive detection indicators and treatments of coronary slow flow. Collaboration needs to be enhanced between different institutions or countries/regions, which would improve clinical outcomes for patients with coronary slow flow.

Relationship between quantitative epicardial adipose tissue based on coronary computed tomography angiography and coronary slow flow.

BACKGROUND: The purpose of this study was to explore the relationship between quantitative epicardial adipose tissue (EAT) based on coronary computed tomography angiography (CCTA) and coronary slow flow (CSF). METHODS: A total of 85 patients with < 40% coronary stenosis on diagnostic coronary angiography were included in this retrospective study between January 2020 and December 2021. A semi-automatic method was developed for EAT quantification on CCTA images. According to the thrombolysis in myocardial infarction flow grade, the patients were divided into CSF group (n = 39) and normal coronary flow group (n = 46). Multivariate logistic regression was used to explore the relationship between EAT and CSF. Receiver operating characteristic (ROC) curve was plotted to evaluate the diagnostic value of EAT in CSF. RESULTS: EAT volume in the CSF group was significantly higher than that of the normal coronary flow group (128.83± 21.59 mL vs. 101.87± 18.56 mL, P < 0.001). There was no significant difference in epicardial fat attenuation index between the two groups (P > 0.05). Multivariate logistic regression analysis showed that EAT volume was independently related to CSF [odds ratio (OR) = 4.82, 95% confidence interval (CI): 3.06-7.27, P < 0.001]. The area under ROC curve for EAT volume in identifying CSF was 0.86 (95% CI: 0.77-0.95). The optimal cutoff value of 118.46 mL yielded a sensitivity of 0.80 and a specificity of 0.94. CONCLUSIONS: Increased EAT volume based on CCTA is strongly associated with CSF. This preliminary finding paves the way for future and larger studies aimed to definitively recognize the diagnostic value of EAT in CSF.