Abstract 1978: Multidimensional Factors Associated with Fatigue in Patients with Atrial Fibrillation
Introduction: Atrial fibrillation (AF) is associated with significant morbidity, symptom burden, and decreased quality of life. Little research has focused on symptoms of AF, particularly fatigue and factors influencing fatigue. This descriptive, cross-sectional, correlational study used a multidimensional symptom framework to examine the prevalence, patterns, and severity of fatigue and associated factors in persons with permanent AF.
Methods: A convenience sample of 43 adults with permanent AF was recruited from three tertiary health care centers. Subjects were 69 ± 10 years of age, 79% male, and 65% were taking beta-blockers. Mean duration of AF was 8.4 ± 8.2 years. Left ventricular ejection fraction was 51.6 ± 11.0%. Demographic/clinical data were collected by patient self-report and medical record review. Variables and measures were fatigue (Checklist of Individual Strength; CIS), activity patterns (wrist actigraphy for 72 hours), depressive symptoms and anxiety (Profile of Mood States), sleep disturbances (Pittsburgh Sleep Quality Index; Epworth Sleepiness Scale). Subjects’ heart rate was monitored for 24 hours using a Polar heart rate monitor. Data were analyzed with descriptive statistics and multiple linear regression.
Results: Mean CIS score was 72.5 ± 22.4 (range 22.0–116.0); 42% of the cohort had fatigue severe enough to cause disability. Fatigue did not vary significantly across the day (F (3,11) ± 0.54, p ± 0.667). Multiple regression revealed that higher fatigue scores (F = 3.11, p = 0.007, Adj. R2 = 0.33) were associated with greater numbers of comorbidities (p = 0.008), greater daytime sleepiness (p = 0.028) and nighttime activity (p = 0.058), and female gender (p = 0.070). Interestingly, mean heart rate did not influence fatigue.
Conclusions: Fatigue was highly prevalent in this sample of AF patients. Comorbidities, indicators of sleep problems (daytime sleepiness and nighttime restlessness), and gender were predictive of fatigue. These data suggest that interventions targeted to improve sleep may improve fatigue in AF patients. Careful monitoring and control of comorbid conditions is also essential. Further research regarding the relationship between fatigue and sleep measures is warranted.