Predicting left atrial thrombi in atrial fibrillation

Waldemar E Wysokinski1, Naser Ammash, Folakemi Sobande

  • 1Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN 55905, USA. wysokinski.waldemar@mayo.edu

Insights

The CHADS(2) score predicts left atrial appendage thrombus (LAAT) in atrial fibrillation (AF) patients. A new scoring system incorporating specific clinical and echocardiographic factors offers improved prediction of cardioembolic risk.

Area of Science:

  • Cardiology
  • Medical Diagnostics
  • Thrombosis Research

Background:

  • Stroke prevention in atrial fibrillation (AF) necessitates accurate risk stratification for cardioembolic events.
  • Identifying patients with left atrial appendage thrombus (LAAT) is crucial for guiding antithrombotic therapy.
  • Existing risk scores may not optimally identify patients at high risk for LAAT and cardioembolism.

Purpose of the Study:

  • To evaluate the predictive capability of the CHADS(2) score for LAAT in nonvalvular AF patients.
  • To identify independent predictors of LAAT in nonvalvular AF.
  • To develop and validate a novel scoring system for improved LAAT risk assessment.

Main Methods:

  • Retrospective analysis of nonanticoagulated, nonvalvular AF patients with and without LAAT.
  • Transesophageal echocardiography used to diagnose LAAT.
  • Comparison of clinical characteristics, AF parameters, and CHADS(2) scores between cases and controls.

Main Results:

  • The CHADS(2) score was significantly higher in patients with LAAT.
  • Independent predictors of LAAT included heart failure, prior stroke/TIA, diabetes, permanent AF, AF duration, and spontaneous echocardiographic contrast.
  • A novel scoring system demonstrated superior predictive power (C-index 0.90) compared to the CHADS(2) score (C-index 0.71).

Conclusions:

  • The CHADS(2) score is a predictor of LAAT in AF patients.
  • Specific components of the CHADS(2) score and echocardiographic findings are key predictors of LAAT.
  • A refined scoring system incorporating predictive factors enhances the identification of AF patients at high cardioembolic risk.
Abstract