Associated diseases and diuretic dosage to predict mortality in transthyretin amyloid cardiomyopathy

Vincent Algalarrondo1, Olivier Lairez2, Marion Narbeburu3

  • 1Referral Center for Cardiac Amyloidosis CERAMIC-Cardio, AP-HP Bichat Hospital, Université Paris-Cité, 75018 Paris, France.

PubMed

Insights

Diuretic dosage is a key predictor of mortality in transthyretin amyloid cardiomyopathy (ATTR-CM) patients, alongside other comorbidities. Comprehensive management of associated diseases is crucial for improving outcomes in ATTR-CM.

Area of Science:

  • Cardiology
  • Internal Medicine
  • Pharmacology

Background:

  • Transthyretin amyloidosis (ATTR) can progress to transthyretin amyloid cardiomyopathy (ATTR-CM), a serious form of heart failure.
  • ATTR-CM is associated with a high burden of cardiac and extracardiac comorbidities.

Purpose of the Study:

  • To determine the prevalence of co-existing conditions in ATTR-CM patients.
  • To identify predictors of mortality in ATTR-CM, with a specific focus on diuretic dosage.

Main Methods:

  • Utilized the French National Health Database to identify patients diagnosed with ATTR-CM between 2011 and 2019.
  • Categorized diuretic (furosemide) doses into four distinct levels for analysis.
  • Examined various medical characteristics and their association with mortality.

Main Results:

  • Over 7800 ATTR-CM patients were analyzed, with significant proportions on different diuretic dose levels at diagnosis.
  • Common extracardiac conditions included kidney disease (37.0%), diabetes (29.5%), and neurologic disorders (17.9%).
  • Multivariable analysis identified age, male sex, diuretic dose, heart failure, arrhythmia, kidney disease, gastrointestinal disorders, and diabetes as significant mortality predictors.

Conclusions:

  • ATTR-CM patients present with a substantial number of comorbidities necessitating integrated management strategies.
  • Diuretic dosage is a critical prognostic factor in ATTR-CM, highlighting its importance in patient care and outcome prediction.
Abstract

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