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Value of baseline characteristics in the risk prediction of atrial fibrillation

Jiacheng He1, Sen Liu1, Cuiwei Yang1,2

  • 1Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai, China.

Frontiers in Cardiovascular Medicine
|February 23, 2023
PubMed

Insights

This study identified key predictors beyond age for atrial fibrillation (AF) risk in elderly Chinese individuals. Incorporating these factors can enhance early detection and management of AF, reducing stroke and mortality.

Area of Science:

  • Cardiology
  • Gerontology
  • Public Health

Background:

  • Atrial fibrillation (AF) significantly increases risks of heart failure and stroke.
  • Current AF screening relies heavily on age, potentially missing high-risk individuals.
  • Early detection and management are crucial for reducing AF-related mortality and morbidity.

Purpose of the Study:

  • To identify and prioritize novel risk predictors for atrial fibrillation beyond chronological age.
  • To explore the combined predictive power of various clinical and electrocardiogram-based characteristics.
  • To inform improved screening strategies for atrial fibrillation in elderly populations.

Main Methods:

  • Analysis of baseline characteristics from 18,738 elderly Chinese individuals (≥60 years).
  • Utilized electrocardiogram (ECG) data and auxiliary physical examination findings.
  • Employed Chi-square tests, Mann-Whitney U tests, Cox regression, and machine learning models with recursive feature elimination.

Main Results:

  • Identified an optimal combination of AF risk predictors: age, atrial premature beats, atrial flutter, left ventricular hypertrophy, hypertension, and heart disease.
  • These predictors, when identified via short-term ECG, indicate a higher likelihood of AF episodes.
  • The incidence of these predictors varies across different age groups, suggesting age-specific management needs.

Conclusions:

  • The identified predictors offer a more comprehensive approach to AF risk assessment.
  • Targeted long-term ECG monitoring or increased screening density is recommended for individuals with these risk factors.
  • Improved AF detection and standardized patient management can mitigate disease progression and associated complications.
Abstract

Keywords:
atrial fibrillationbaseline characteristicselectrocardiogram machinerisk predictionstatistical test

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