Bayesian Network Meta-Analysis of Antidiabetic Drugs and Dementia Risk

28 articles involving 4,382,897 patients were analyzed to evaluate the impact of antidiabetic drugs on dementia risk. The study, authored by Yang Yu and uploaded to figshare in April 2026, used a Bayesian network meta-analysis model to compare drug efficacy. Results indicate insulin had the most pronounced effect in reducing dementia incidence risk compared to placebo.

Use Cases

• Compare the relative efficacy of different antidiabetic drugs on dementia risk based on the reported odds ratios.
• Validate or inform clinical study design for diabetes and cognitive impairment based on the aggregated evidence from 28 studies.
• Serve as a reference dataset for secondary statistical analyses or systematic reviews in neuropharmacology.

Strengths

• Analysis is based on a large patient pool of 4,382,897 individuals.
• Results include specific odds ratios and credible intervals for multiple drug comparisons.
• The study protocol is registered with a PROSPERO identifier, suggesting a structured methodology.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The data is presented in a DOCX file, which may require extraction to a structured format for analysis.

Provenance

Source

Yang Yu via figshare.

Collection Method

Systematic review and Bayesian network meta-analysis of randomized controlled trials, cohort studies, and case-control studies.

Time Range

Publications searched up to September 5,我们发现2025.

Freshness

Last updated 2026-04-15 04:37:14; freshness should be verified.

Geography

Global (studies from databases like PubMed, Embase, Cochrane Library).