Table 1_Mining personalized core traditional Chinese medicine prescriptions for rheumatoid arthritis and elucidating their mechanisms via frequent closed Itemset compression and multilevel network pharmacology.docx

Five representative core Traditional Chinese Medicine prescriptions were identified from the analysis of inpatient electronic medical records of 614 eligible rheumatoid arthritis patients. The study links these prescriptions to clinical outcomes via C-reactive protein levels and to molecular mechanisms through network pharmacology and molecular docking analyses.

Use Cases

• Analyze the association between identified core TCM prescriptions and longitudinal changes in C-reactive protein levels across 614 patients.
• Investigate the overlap between prescription-specific molecular targets and known rheumatoid arthritis-associated genes using network pharmacology results.
• Validate structural interactions, such as between quercetin and TNF-α, using the molecular docking data presented in the study.

Strengths

• Clinical validation based on 614 eligible patients showing significant post-treatment reductions in C-reactive protein.
• Mechanistic analysis linking five core prescriptions to 65–115 molecular targets each via network pharmacology.
• Integrative approach combining real-world clinical data, systems-level network analysis, and structural molecular docking.

Limitations

• Dataset scope is limited to a 25.0 KB document file, containing summarized research findings rather than raw patient-level data.
• Clinical data is retrospective and sourced from only two tertiary hospitals in China, limiting generalizability.
• Molecular docking results are computational predictions requiring experimental validation.

Provenance

Source

figshare, authored by Xu Chen.

Collection Method

Analysis of large-scale inpatient electronic medical records from two tertiary hospitals, combined with computational systems pharmacology.

Freshness

Last updated March 23, 2026.

Geography

China (hospitals unspecified).