The Medication Patterns of Traditional Chinese Medicine In Treating Long COVID with Cardiovascular Complications - A Bibliometrics Study
Year: 2025
Type: article
Abstract: Introduction: COVID-19 spread with cardiovascular complications, showing high incidence and mortality links. Traditional Chinese medicine (TCM) syndrome differentiation and holistic approach offer advantages in treating epidemics and heart diseases. This study explores TCM medication patterns for post-COVID cardiovascular complications via bibliometrics. Methods: From Oct 2019 to Nov 2023, 16 TCM prescriptions were collected using keywords from CNKI, Wanfang Database, and national/provincial treatment plans. Data were organized in Excel 2019, analyzed via Excel, SPSS Modeler 18.0, Gephi, and SPSS Statistics 27. Results: Totally, 13 formulas involving 87 drugs were included. Top drugs (frequency ≥4) were sweet/pungent/bitter/warm, targeting heart/lung/spleen/stomach meridians; tonifying deficiency medicines were most used. Six core combinations, including Licorice-Poria, support 37.5%, confidence 83.8% were found. 14 key drugs clustered into 4 groups, including nourishing yin/Blood circulation, clearing heat/dampness, harmonizing middle/strengthening spleen/benefiting Qi, and tonifying Qi/Blood circulation. Discussion: This study highlights TCM's advantages in addressing post-COVID cardiovascular complications via syndrome differentiation. Core herb pair Licorice-Poria, combined with four clustered drug groups, offers individualized, effective treatment strategies, providing valuable clinical references for future TCM prescriptions. Conclusion: TCM has unique advantages in post-COVID cardiovascular care, and this study provides clinical references for TCM syndrome differentiation and medication.
Source: Current Traditional Medicine
Authors: Yongwen Tan, Qingping Deng, Xing Zeng, Xiaoya Li, Qing Liu, Rongyuan Yang
Language: English
Subfield: Complementary and alternative medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4416944481