Risk factors for heart failure hospitalizations among patients with atrial fibrillation

Lucien Eggimann1,2, Steffen Blum1,2,3, Stefanie Aeschbacher1,2

  • 1Division of Cardiology, Department of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.

Plos One
|February 3, 2018
PubMed

Insights

Predicting heart failure (HF) hospitalizations in atrial fibrillation (AF) patients is crucial. Key predictors include body mass index, chronic kidney disease, diabetes, QTc interval, BNP, diastolic blood pressure, and prior interventions.

Area of Science:

  • Cardiology
  • Internal Medicine

Background:

  • Atrial fibrillation (AF) significantly increases the risk of developing heart failure (HF).
  • Identifying predictors for HF hospitalizations in AF patients is essential for proactive management.

Purpose of the Study:

  • To identify predictors of heart failure (HF) hospitalizations within an unselected population of patients diagnosed with atrial fibrillation (AF).

Main Methods:

  • The study analyzed data from 1193 patients in the Basel Atrial Fibrillation Cohort Study.
  • Clinical data, blood samples, ECGs, and lifestyle information were collected at baseline.
  • Cox regression analyses were employed to determine independent predictors of HF hospitalization.

Main Results:

  • Over a mean follow-up of 3.7 years, 110 patients (2.5 events per 100 person-years) were hospitalized for HF.
  • Independent predictors identified included higher body mass index, chronic kidney disease, diabetes mellitus, and prolonged QTc interval.
  • Elevated brain natriuretic peptide, lower diastolic blood pressure, history of pulmonary vein isolation or electrical cardioversion, and serum chloride levels also predicted HF hospitalizations.

Conclusions:

  • Traditional cardiovascular risk factors and specific arrhythmia interventions are significant predictors of HF hospitalizations in AF patients.
  • These findings suggest potential strategies to reduce HF incidence and hospitalizations in this vulnerable population.
Abstract

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