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The CHA2DS2-VASc score for predicting atrial fibrillation in patients presenting with ST elevation myocardial

Fatih Aksoy1, Hasan Aydin Baş2, Ali Bağcı2

  • 1MD. Associate Professor, Department of Cardiology, Süleyman Demirel Üniversitesi Tıp Fakültesi, Isparta, Turkey.

Sao Paulo Medical Journal = Revista Paulista De Medicina
|July 25, 2019
PubMed

Insights

The CHADS2 and CHA2DS2-VASc scores effectively predict new atrial fibrillation (AF) in patients experiencing ST-elevation myocardial infarction (STEMI). These scores, along with other clinical factors, aid in identifying high-risk individuals for AF post-STEMI.

Area of Science:

  • Cardiology
  • Clinical Research
  • Arrhythmia Studies

Background:

  • Atrial fibrillation (AF) is a common arrhythmia post-ST-elevation myocardial infarction (STEMI).
  • Existing scores like CHA2DS2-VASc and CHADS2 assess thromboembolic risk in AF patients.
  • The predictive value of these scores for new-onset AF in STEMI patients was previously unknown.

Purpose of the Study:

  • To determine the predictive capability of CHADS2 and CHA2DS2-VASc scores for new-onset AF in STEMI patients.
  • To identify clinical and laboratory predictors of AF following STEMI.

Main Methods:

  • Prospective cohort study of 696 STEMI patients.
  • Development of predictive models using clinical and laboratory parameters.
  • Multivariate regression analysis to identify AF predictors and assess score utility.

Main Results:

  • Higher CHADS2 and CHA2DS2-VASc scores were observed in patients who developed AF (P < 0.001).
  • Predictors of AF included CHA2DS2-VASc score (OR: 1.48), peak creatine kinase-myocardial binding, longer ICU stay, and non-use of renin-angiotensin system blockers.
  • CHA2DS2-VASc scores demonstrated significant predictive value for new AF (C-statistic: 0.698).

Conclusions:

  • CHADS2 and CHA2DS2-VASc scores are valuable predictors of new-onset AF in STEMI patients.
  • These scores can aid in risk stratification for AF development post-STEMI.
  • Further research may refine risk prediction models incorporating these scores.
Abstract

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