Nomogram for predicting cardiac death and heart transplantation in arrhythmogenic right ventricular cardiomyopathy

Yiju Luo1, Xin Chen1, Yuhua Zhang1

  • 1Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.

ESC Heart Failure
|August 11, 2023
PubMed

Insights

A new nomogram accurately predicts cardiac death and heart transplantation (HT) risk in arrhythmogenic right ventricular cardiomyopathy (ARVC) patients. This tool uses readily available clinical data for personalized prognostic assessment.

Area of Science:

  • Cardiology
  • Medical Diagnostics
  • Predictive Modeling

Background:

  • Arrhythmogenic right ventricular cardiomyopathy (ARVC) poses a significant risk of cardiac death and the need for heart transplantation (HT).
  • Accurate prognostication is crucial for managing ARVC patients and guiding treatment decisions.

Purpose of the Study:

  • To develop and validate a competing risk nomogram for predicting cardiac death and HT in ARVC patients.
  • To identify key clinical predictors for adverse cardiovascular events in ARVC.

Main Methods:

  • Retrospective analysis of 149 ARVC patients diagnosed between 2008 and 2022.
  • Development of a competing risk nomogram using Cox proportional hazards models.
  • Internal validation using AUC, Harrell's C-index, calibration curves, and decision curve analysis.

Main Results:

  • The nomogram demonstrated high predictive accuracy with AUC values up to 0.956 and Harrell's C-index of 0.9273.
  • Key predictors included T-wave inversion, right atrial diameter, and ventricular ejection fractions.
  • The model showed good discriminative ability and clinical utility for risk stratification.

Conclusions:

  • A novel, validated competing risk nomogram can predict cardiac death and HT in ARVC patients.
  • The nomogram utilizes accessible clinical parameters, offering a valuable tool for individualized prognosis.
  • This tool aids in better risk assessment and management strategies for ARVC.
Abstract

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