Abstract 1437: Identification of Symptom Clusters in Systolic Heart Failure
Background and Significance: The burden of symptoms for heart failure (HF) patients is often debilitating and severely limits quality of life. Because symptoms are generally not considered as clusters, there are gaps in knowledge related to HF symptom clusters and their variation over time.
Purpose: To identify the clusters of symptoms that are present in HF and to describe their trajectory over time utilizing an Internet-based symptom inventory instrument.
Methods: We recruited subjects with systolic HF (N=115) from 2 inner city medical center HF clinics and asked them to rank their experience related to 50 symptoms (0= not present to 4=severe) during the past week utilizing a touch screen computer. We also invited subjects to complete the same survey instrument via the internet or at the clinic at 3 month intervals for 1 year. We used latent class cluster analysis to cluster the symptoms at each time point.
Results: Subjects were primarily African American (83%), male (75%), mean age was 63.5 years (SD=15.08, range 20 –92). Modal NYHA classification was 3 (range 1– 4) and mean ejection fraction (EF) was 29.1 (SD=10.51, range <10%–50%) Four different clusters of symptoms were identified (Wald=14.6348, p=.0022). The most prominent features of all 4 clusters were similar (weight gain, SOB with exertion, decreased urination, swelling in feet or ankles, joint pain and stiffness, leg pain, fatigue, cough at night, difficulty keeping thoughts straight, lower back pain, difficulty falling asleep, and frequent daytime dozing). What differentiated the clusters was the intensity of symptoms. Subjects whose symptoms centered on cluster 4 (N=23) experienced greater intensity of all symptoms while subjects in cluster 3 (N= 37) experienced the least intensity of symptoms. Intensity of symptoms was not related to NYHA classification or EF. In addition, the cluster of symptoms that was experienced varied over time in 38% of subjects which indicates a change in the intensity of symptoms.
Conclusions: Four different clusters of symptoms for HF were identified that differed primarily by intensity of symptoms and varied over time. A more thorough understanding if HF symptom clusters would assist practitioners in being more proactive related to treatment of symptoms.