Drivers of hospitalization for patients with atrial fibrillation: Results from the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation (ORBIT-AF).
BACKGROUND
Atrial fibrillation (AF) is the most common cardiac dysrhythmia and contributes significantly to health care expenditures. We sought to assess the frequency and predictors of hospitalization in patients with AF.


METHODS
The ORBIT-AF registry is a prospective, observational study of outpatients with AF enrolled from June 29, 2010, to August 9, 2011. The current analysis included 9,484 participants with 1-year follow-up. Multivariable, logistic regression was used to identify baseline characteristics that were associated with first cause-specific hospitalization.


RESULTS
Overall, 31% of patients with AF studied (n = 2,963) had 1 or more hospitalizations per year and 10% (n = 983) had 2 or more. The most common hospitalization cause was cardiovascular (20 per 100 patient-years vs 3.3 bleeding vs 17 noncardiovascular, nonbleeding). Compared with those not hospitalized, hospitalized patients were more likely to have concomitant heart failure (42% vs 28%, P < .0001), higher mean CHADS2 (1 point for congestive heart failure, hypertension, age ≥75, or diabetes; 2 points for prior stroke or transient ischemic attack) scores (2.5 vs 2.2, P < .0001), and more symptoms (baseline European Heart Rhythm Association class severe symptoms 18% vs 13%, P < .0001). In multivariable analysis, heart failure (adjusted hazard ratio [HR] 1.57 for New York Heart Association III/IV vs none, P < .0001), heart rate at baseline (adjusted HR 1.11 per 10-beats/min increase >66, P < .0001), and AF symptom class (adjusted HR 1.37 for European Heart Rhythm Association severe vs none, P < .0001) were the major predictors of incident hospitalization.


CONCLUSIONS
Hospitalization is common in outpatients with AF and is independently predicted by heart failure and AF symptoms. Improved symptom control, rate control, and comorbid condition management should be evaluated as strategies to reduce health care use in these patients.
Duke University Medical Center, Durham, NC; Duke Clinical Research Institute, Durham, NC. Electronic address: benjamin.steinberg@duke.edu.
Benjamin A
BA
Steinberg
Duke Clinical Research Institute, Durham, NC.
Sunghee
S
Kim
UCLA Division of Cardiology, Los Angeles, CA. Electronic address: GFonarow@mednet.ucla.edu.
Gregg C
GC
Fonarow
Duke Clinical Research Institute, Durham, NC.
Laine
L
Thomas
New York University School of Medicine, Lenox Hill Hospital, New York, NY. Electronic address: ansellje@gmail.com.
Jack
J
Ansell
Lankenau Institute for Medical Research, Wynnewood, PA. Electronic address: KoweyP@mlhs.org.
Peter R
PR
Kowey
Stanford University School of Medicine, Stanford, CA. Electronic address: Kenneth.mahaffey@stanford.edu.
Kenneth W
KW
Mahaffey
Mayo Clinic, Rochester, MN. Electronic address: gersh.bernard@mayo.edu.
Bernard J
BJ
Gersh
Boston University School of Medicine, Boston, MA. Electronic address: Elaine.Hylek@bmc.org.
Elaine
E
Hylek
Penn State University School of Medicine, Hershey, PA. Electronic address: gnaccarelli@hmc.psu.edu.
Gerald
G
Naccarelli
Kaiser Permanente, Oakland, CA. Electronic address: alan.s.go@kp.org.
Alan S
AS
Go
Columbia University College of Physicians and Surgeons, New York, NY. Electronic address: jar2@columbia.edu.
James
J
Reiffel
Janssen Pharmaceuticals, Inc., Raritan, NJ. Electronic address: PChang9@its.jnj.com.
Paul
P
Chang
Duke University Medical Center, Durham, NC; Duke Clinical Research Institute, Durham, NC.
Eric D
ED
Peterson
Duke University Medical Center, Durham, NC; Duke Clinical Research Institute, Durham, NC.
Jonathan P
JP
Piccini
D000368:Aged; D001281:Atrial Fibrillation / Q000503:physiopathology / Q000628:therapy*; D018450:Disease Progression; D005260:Female; D005500:Follow-Up Studies; D006333:Heart Failure / Q000453:epidemiology / Q000209:etiology* / Q000517:prevention & control; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D015994:Incidence; D008297:Male; D011379:Prognosis; D011446:Prospective Studies; D012042:Registries; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D013997:Time Factors; D014481:United States / Q000453:epidemiology