Table 3_Association of systemic inflammation response index and triglyceride-glucose index

A retrospective cross-sectional study of 1,019 patients with coronary artery disease (CAD) explores the relationship between inflammatory and metabolic markers and stenosis severity. The dataset includes results from logistic regression, interaction, and mediation analyses linking the Systemic Inflammation Response Index (SIRI) and Triglyceride-Glucose Index (TyG) to Gensini scores. The study was authored by Yazhao Sun and shared under a CC-BY-4.0 license on figshare in 2026.

Use Cases

• Predicting severe coronary artery stenosis based on SIRI and TyG index values.
• Analyzing the additive interaction between systemic inflammation and insulin resistance metrics for cardiovascular risk assessment.
• Validating the incremental predictive value of SIRI and TyG over traditional risk models using Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI) metrics.
• Investigating the mediating relationship between SIRI and TyG indices in the context of coronary artery disease severity.

Strengths

• Study includes a cohort of 1,019 patients with coronary artery disease.
• Analysis provides specific odds ratios (e.g., OR: 4.912 for high SIRI + high TyG group) and correlation coefficients (e.g., ρ=0.435 for SIRI).
• Multiple statistical methods were employed, including logistic regression, ROC curve analysis, Spearman correlation, and mediation analysis.

Limitations

• The dataset is a 12.3 KB DOCX file, suggesting it likely contains summary results and analysis text rather than raw patient-level data.
• Row count and column-level documentation are unknown, limiting suitability assessment for direct machine learning applications.
• The single-center, retrospective cross-sectional design may limit generalizability.

Provenance

Source

figshare

Collection Method

Retrospective cross-sectional study conducted at a single center.

Freshness

Last updated 2026-05-18 04:17:02.