Ming-Fen Tsai1, Shiow-Li Hwang2, Shiow-Luan Tsay2, Chun-Li Wang3, Feng-Chun Tsai3, Chun-Chi Chen3, Tsuey-Yuan Huang4. 1. Chang Gung University of Science and Technology, Taoyuan & School of Nursing, National Taipei University of Nursing and Health; 2. National Taipei University of Nursing and Health, Taipei; 3. Chang Gung Memorial Hospital; 4. Chang Gung University of Science and Technology, Taoyuan, Taiwan.
Abstract
BACKGROUND: Dyspnea and fatigue are distressing symptoms commonly seen in heart failure (HF) patients, and are closely related to patients' disease trajectory of contributes. Identifying the effect of symptom trends on disease outcomes is important to develop effective symptom management interventions in HF patients. METHODS: One hundred and twenty-two patients were recruited. Dyspnea, fatigue, clinical characteristics, and disease outcomes were measured at the baseline assessment, three months, and 12 months. Latent class growth model and Kaplan-Meier survival analysis were used on dyspnea and fatigue to examine the relationship of disease trajectories and effects on disease outcomes. RESULTS: A total of 122 patients were examined (mean age 62.8 ± 13.0 yrs; 79% male; 39% NYHA III/IV; 48% preserved systolic function HF). Three groups based on HF patients' dyspnea-fatigue trends were identified as "constant good," "recovery," and "getting worse." The cumulative incidence of a first cardiac event in both dyspnea and fatigue groups yielded similar results. The quality of life score for the getting worse group was significantly higher than that of the constant good and recovery groups. The result of the log-rank test was significant (χ(2) = 8.11, p = 0.017). Post hoc comparison showed that the prognosis status of the constant good group was better than that of the getting worse (p = 0.046) and recovery groups (p = 0.020), while getting worse and recovery groups did not differ in prognosis status (p = 0.30). CONCLUSIONS: The results demonstrate the value of tracking symptoms over time to determine symptom trajectories as well as severe baseline (even with improvements at follow-ups) or increased fatigue over time were related to a worse event-free survival as compared with low but stable fatigue. KEY WORDS: Disease outcome; Kaplan-Meier survival analysis; Symptom trajectory.
BACKGROUND:Dyspnea and fatigue are distressing symptoms commonly seen in heart failure (HF) patients, and are closely related to patients' disease trajectory of contributes. Identifying the effect of symptom trends on disease outcomes is important to develop effective symptom management interventions in HF patients. METHODS: One hundred and twenty-two patients were recruited. Dyspnea, fatigue, clinical characteristics, and disease outcomes were measured at the baseline assessment, three months, and 12 months. Latent class growth model and Kaplan-Meier survival analysis were used on dyspnea and fatigue to examine the relationship of disease trajectories and effects on disease outcomes. RESULTS: A total of 122 patients were examined (mean age 62.8 ± 13.0 yrs; 79% male; 39% NYHA III/IV; 48% preserved systolic function HF). Three groups based on HF patients' dyspnea-fatigue trends were identified as "constant good," "recovery," and "getting worse." The cumulative incidence of a first cardiac event in both dyspnea and fatigue groups yielded similar results. The quality of life score for the getting worse group was significantly higher than that of the constant good and recovery groups. The result of the log-rank test was significant (χ(2) = 8.11, p = 0.017). Post hoc comparison showed that the prognosis status of the constant good group was better than that of the getting worse (p = 0.046) and recovery groups (p = 0.020), while getting worse and recovery groups did not differ in prognosis status (p = 0.30). CONCLUSIONS: The results demonstrate the value of tracking symptoms over time to determine symptom trajectories as well as severe baseline (even with improvements at follow-ups) or increased fatigue over time were related to a worse event-free survival as compared with low but stable fatigue. KEY WORDS: Disease outcome; Kaplan-Meier survival analysis; Symptom trajectory.
Authors: Ioannis Laoutaris; Athanasios Dritsas; Margaret D Brown; Athanasios Manginas; Peter A Alivizatos; Dennis V Cokkinos Journal: Eur J Cardiovasc Prev Rehabil Date: 2004-12
Authors: Otto R F Smith; Johan Denollet; Angélique A Schiffer; Nina Kupper; Yori Gidron Journal: Eur J Heart Fail Date: 2009-01-29 Impact factor: 15.534