Data Sheet 1_Effect of traditional Chinese medicine non-pharmacological interventions on c

A 2026 systematic review and network meta-analysis of 76 randomized controlled trials involving 4,895 patients with mild cognitive impairment. The study, authored by Zhihao Dong and published on figshare, evaluates the effectiveness of nine types of Traditional Chinese Medicine non-pharmacological interventions on cognitive function scores. It includes results from a Bayesian network meta-analysis performed using R 4.4.3 software.

Use Cases

• Ranking the effectiveness of different Traditional Chinese Medicine therapies based on reported Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) score improvements.
• Conducting subgroup analysis or meta-regression based on intervention duration and patient population characteristics described in the review.
• Comparing the safety profiles of non-pharmacological interventions using the reported adverse event data.
• Validating network meta-analysis methodologies against the Bayesian analysis results presented for 76 trials.

Strengths

• Includes 76 randomized controlled trials, providing a substantial evidence base.
• Analyzes data from 4,895 patients with mild cognitive impairment.
• Compares 9 distinct Traditional Chinese Medicine non-pharmacological interventions.
• Reports specific effect sizes (e.g., MD=2.18 for MMSE, MD=3.31 for MoCA) and ranking statistics (SUCRA values).

Limitations

• The primary data file is a DOCX document; the underlying trial-level data is not provided in a structured, machine-readable format.
• Column-level documentation for any extracted data is absent; field semantics must be inferred from the manuscript text.
• Row count for any potential supplementary data is unknown, which may limit suitability assessment for direct analysis.

Provenance

Source

Zhihao Dong via figshare.

Collection Method

Systematic review and Bayesian network meta-analysis of randomized controlled trials retrieved from 7 databases.

Time Range

Trials from database inception to December 26, 2025.

Freshness

Last updated 2026-04-13 04:35:17.

Geography

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