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

Qin Chen1,2,3, Yuxiang Chen1,2,3, Ruijin Hong1,2,3

  • 1Fujian Key Laboratory of Vascular Aging (Fujian Medical University), Department of Cardiology, Fujian Medical University Union Hospital, 350001 Fuzhou, Fujian, China.

Insights

A new nomogram predicts target vessel revascularization (TVR) in elderly patients after percutaneous coronary intervention (PCI). This tool aids clinicians in assessing prognosis for older individuals with cardiovascular conditions.

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.
Abstract