Objective:

To develop and validate a prediction model for in-stent restenosis (ISR) during antiplatelet therapy after PCI by integrating thromboelastography parameters, coagulation function, and clinical indicators, thereby enhancing risk stratification.

Approach:

Key Findings:

• 34.2% of patients developed ISR.
• Key predictors identified include low ADP inhibition rate, low AA inhibition rate, R-value, and age.
• The nomogram demonstrated good discrimination (AUC = 0.752, 95% CI: 0.702–0.803) and stable performance upon validation.

Interpretation:

The developed prediction model effectively identifies high-risk patients for ISR post-PCI, aiding in personalized antiplatelet therapy and management decisions.

Limitations:

• Retrospective design may introduce selection bias, potentially affecting the reliability of the findings.
• Single-center study limits generalizability.

Conclusion:

The predictive model based on TEG parameters and clinical indicators provides a valuable tool for identifying patients at high risk for ISR after PCI, ultimately aiding in personalized antiplatelet therapy and management decisions.

Attribution Notice

This content is an AI-generated, fully rewritten summary based on a published scholarly article. It does not reproduce the original text and is not a substitute for the original publication. Readers are encouraged to consult the source for full context, data, and methodology.