A Visualized Nomogram for Predicting Prognosis in Elderly Patients after Percutaneous Coronary Intervention

Area of Science:

• Cardiovascular Medicine
• Interventional Cardiology
• Geriatric Cardiology

Background:

• Elderly patients (over 65) undergoing revascularization still face adverse cardiovascular events.
• Co-morbid vascular conditions are prevalent in this demographic, necessitating improved prognostic tools.
• Accurate prognosis assessment is crucial for guiding treatment decisions in elderly PCI patients.

Purpose of the Study:

• To develop a comprehensive visual nomogram for predicting outcomes in elderly patients post-percutaneous coronary intervention (PCI).
• To integrate clinical and physiological assessments into a predictive model.
• To specifically forecast 2-year and 5-year target vessel revascularization (TVR) rates.

Main Methods:

• Retrospective analysis of 691 patients undergoing PCI (2016-2017).
• Data split into training (n=483) and validation (n=208) sets.
• Multivariate Cox regression used for variable selection; nomogram performance assessed via ROC curves, calibration, and Kaplan-Meier analysis.

Main Results:

• The nomogram incorporated diabetes mellitus, post-PCI QFR, prior MI, and prior PCI.
• Demonstrated good predictive accuracy with AUCs ranging from 0.742-0.837 across sets.
• Higher nomogram scores correlated with increased 2- and 5-year TVR rates (p < 0.001).

Conclusions:

• A visually intuitive nomogram was developed to predict TVR in elderly PCI patients.
• The tool offers enhanced prognostic guidance for clinicians and patients.
• This model aids in more accurate and comprehensive healthcare decision-making.