Clinical Data on Coronary Stenosis Severity, Inflammation, and Insulin Resistance

A retrospective cross-sectional study of 1,019 coronary artery disease patients. The dataset likely contains clinical measurements used to explore associations between systemic inflammation (SIRI), insulin resistance (TyG index), and coronary artery stenosis severity (Gensini score). The study was authored by Yazhao Sun and posted on figshare.

Use Cases

• Training logistic regression models to predict severe stenosis based on SIRI and TyG index values.
• Analyzing the additive interaction between inflammatory and metabolic biomarkers for coronary artery disease.
• Evaluating the predictive performance improvement of new biomarkers (SIRI, TyG) over traditional risk models.
• Conducting mediation analysis to understand indirect statistical associations between biomarkers and disease severity.

Strengths

• Dataset includes 1,019 patient records, providing a substantial sample size for analysis.
• Analysis includes specific statistical results, such as odds ratios (OR: 4.912) and correlation coefficients (ρ = 0.435), indicating a detailed study.
• The dataset is licensed under CC-BY-4.0, allowing for open reuse.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The study is a single-center retrospective analysis; data may reflect geographic and methodological bias inherent to its source.

Provenance

Source

figshare

Collection Method

Retrospective cross-sectional study conducted at a single center.

Freshness

Last updated 2026-05-18 04:17:03; freshness should be verified.