AI Article Synopsis
- The study aimed to identify patterns and combinations of herbs recommended for COVID-19 treatment using network analysis techniques.
- The analysis involved 142 herbal formulae with 416 herbs, examining their pairings and how frequently they were used at each disease stage.
- Findings highlighted specific herb pairings that are effective and suggested that a scoring system could optimize herb combinations in treatment, offering potential future directions for clinical research.
Article Abstract
Purpose: In this study, we aimed to identify the pattern and combination of herbs used in the formulae recommended for treating different stages of COVID-19 using a network analysis approach.
Methods: The herbal formulae recommended by official guidelines for the treatment of COVID-19 are included in the present analysis. To describe the tendency of herbs to form a "herb pair", we computed the mutual information (MI) value and distance-based mutual information model (DMIM) score. We also performed modularity, degree, betweenness, and closeness centrality analysis. Network analyses were performed and visualized for each disease stage.
Results: A total of 142 herbal formulae comprising 416 herbs were analyzed. All possible herbal pairs were examined, and the top frequently used herbal pairs were identified for each disease stage. The herb is only identified in one herb pair, even though this herb is identified as one of the herbs with high frequency of use for every disease stage. This suggests that the DMIM score could be used to identify the optimal combination rule of herbal formulae by achieving a balance among the herbs' frequency and relative distance in herbal formulae.
Conclusion: Our results presented the prescription patterns and herbal combinations of the herbal formulae recommended for the treatment of COVID-19. This study may provide new insights and ideas for clinical research in the future.
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Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8140903 | PMC |
| http://dx.doi.org/10.2147/IDR.S305176 | DOI Listing |
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