Impact of T-AMYLO Risk Score and Red Flag Findings on Cardiovascular Outcomes in Patients with Cardiac Conduction

Hidayet Ozan Arabaci1, Sukru Arslan2, Cem Kurt2

  • 1Department of Cardiology, Gaziosmanpasa Training and Research Hospital, Istanbul 34255, Türkiye.

Insights

Cardiac amyloidosis is often missed in patients with unexplained conduction defects. The T-AMYLO score and specific red flags can help identify this condition and predict adverse outcomes.

Area of Science:

  • Cardiology
  • Medical Diagnostics
  • Cardiac Electrophysiology

Background:

  • Cardiac amyloidosis is increasingly recognized, affecting up to 15% of patients with aortic stenosis or heart failure with preserved ejection fraction.
  • Pacemaker implantation is common in these patients, but the role of cardiac amyloidosis in unexplained cardiac conduction defects is not well understood.

Purpose of the Study:

  • To assess the prevalence and prognostic value of cardiac amyloidosis in patients with unexplained cardiac conduction defects.
  • To evaluate the T-AMYLO score and associated red flag findings for risk stratification.

Main Methods:

  • Retrospective cohort study of 1107 patients undergoing intracardiac device implantation for unexplained cardiac conduction defects.
  • Exclusion of patients with secondary conduction defects or known cardiomyopathy.
  • Assessment of the T-AMYLO score and red flags against a composite endpoint of mortality, myocardial infarction, and stroke.

Main Results:

  • Higher event rates were observed in older males, those with atrioventricular block, and patients receiving single-lead ventricular devices.
  • Elevated T-AMYLO score, aortic valve disease, and atrioventricular block were independent predictors of mortality.
  • A stepwise decline in prognosis was associated with increasing T-AMYLO risk group and red flag burden.

Conclusions:

  • The T-AMYLO score and red flag assessment are crucial for detecting cardiac amyloidosis in patients with conduction defects.
  • These tools aid in improving early diagnosis and guiding risk stratification for better patient outcomes.
Abstract