Does Health-Related Quality of Life Predict Hospitalization or Mortality in Patients with Atrial Fibrillation?

Authors

  • ELEANOR SCHRON R.N., Ph.D., F.A.A.N.,

    Corresponding author
    1. Division of Extramural Research, National Eye Institute/NIH, Bethesda, Maryland
    • Address for correspondence: Eleanor Schron, R.N., Ph.D., F.A.A.N., Director, Clinical Applications, Vision Research Program, Division of Extramural Research, National Eye Institute/NIH, Suite 1300, 5635 Fishers Lane, MSC 9300, Bethesda, MD 20892-9300, USA; 301-451-2020. Fax: +301-402-0528; E-mail: schrone@nei.nih.gov

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  • ERIKA FRIEDMANN Ph.D.,

    1. University of Maryland School of Nursing, Baltimore, Maryland, USA
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  • SUE A. THOMAS R.N., Ph.D., F.A.A.N.

    1. University of Maryland School of Nursing, Baltimore, Maryland, USA
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  • The Atrial Fibrillation Follow-up Investigation of Rhythm Management (AFFIRM) is conducted and supported by the NHLBI in collaboration with the AFFIRM Investigators. This manuscript was prepared using a limited access dataset obtained by the NHLBI and does not necessarily reflect the opinions or views of the AFFIRM Study or the NHLBI.

  • No disclosures.

QOL Predicts Hospitalization and Mortality in AF

Background

Poor health-related quality of life (QOL) is related to morbidity and mortality in coronary heart disease and ventricular arrhythmias as well as to mortality in patients with heart failure (HF) and atrial fibrillation (AF). This study examined the contributions of QOL to the prediction of 1-year hospitalization and mortality in patients with AF, independent of HF.

Methods

This study used the public use dataset from the NHLBI/NIH AFFIRM randomized clinical trial. Patients enrolled in the QOL substudy (N = 693) were randomly assigned to rate or rhythm control. QOL was assessed with the Medical Outcomes Study 36-item Short Form Health Survey (SF-36) and the Quality of Life Index-Cardiac Version (QLI-CV). Data were analyzed with logistic regression to predict 1-year hospitalization and Cox proportional hazards analysis to predict mortality.

Results

In the first year of participation in the study 37% (n = 256) were hospitalized; mortality was 14.3% (n = 93) with mean follow-up of 3.5 years. Patients’ mean age was 69.8 ± 8.2 years, were largely male (62%), and white (93%). Patient histories included 70.8% hypertension, 38.2% coronary artery disease (CAD), and 23.7% HF. History of stroke, HF, rhythm control arm, lower SF-36 mental component scores (MCS), and lower SF-36 physical component scores (PCS) predicted hospitalization (P < 0.001). Diabetes, female gender, older age, CAD, hypertension, and lower PCS predicted mortality (P < 0.001).

Conclusion

QOL adds meaningful information beyond traditional biomedical factors to the prediction of mortality and/or hospitalization of patients with AF. Interventions for improving QOL and helping patients adapt to AF treatments may decrease hospitalization and improve survival.

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