Data Sheet 1_Traditional Chinese Medicine for preventing influenza: a systematic review an
by Haowen Huang·Updated 1mo ago
96.6 KB1files
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Description
A 2025 systematic review and meta-analysis by Haowen Huang, aggregating data from 19 studies involving 55,183 healthy participants. The dataset includes results from a search of eight databases up to August 14, 2025, assessing the effectiveness and safety of TCM interventions against influenza. The analysis includes risk ratios for influenza incidence, influenza-like illness, and adverse events.
Use Cases
Conducting a meta-analysis on preventive health interventions based on aggregated study results.
Assessing the methodological quality of clinical trials in traditional medicine based on the described systematic review process.
Evaluating the safety profile of herbal or traditional interventions based on adverse event rate comparisons.
Identifying research gaps for future clinical studies on influenza prevention based on the review's conclusions.
Strengths
Includes data from 55,183 participants across 19 studies, providing a substantial sample size for analysis.
Follows a rigorous systematic review methodology with independent screening and data extraction by two investigators.
Reports specific statistical results, including risk ratios and confidence intervals for key outcomes.
Limitations
The primary data is presented in a 96.6 KB PDF report; underlying tabular data or individual study records are not directly accessible.
The review notes the confidence in conclusions is limited by the methodological limitations of the included studies.
The dataset's scope is limited to the specific research question of TCM for influenza prevention up to August 2025.
Provenance
Source
Haowen Huang via figshare.
Collection Method
Systematic review and meta-analysis of studies from PubMed, EMbase, CENTRAL, Web of Science, CNKI, WanFang, CQVIP, and Sinomed.
Time Range
Studies included up to August 14, 2025.
Freshness
Last updated 2026-04-23 05:28:27.
Data is provided as a PDF document (96.6 KB); extraction of structured data for computational analysis would require manual effort or text parsing.