The Relationship Between Self-Care and Health Status Domains in Thai Patients With Heart Failure

Background: Little is known about the relationship between self-care in heart failure (HF) and outcomes like health status. The purpose of this study was to describe the relationship between HF self-care and Short Form-36 (SF-36) health status domains. Methods and results: A secondary analysis of cross-sectional data collected on 400 HF patients living in southern Thailand was completed using bivariate comparisons and hierarchical multiple regression modeling. Thai population norm-based SF-36 scores and Self-Care of Heart Failure Index (SCHFI) scores were used in the analysis. The sample was in older adulthood (65.7 ± 13.8 years), a slight majority of subjects were male (52%); the majority of subjects (62%) had class III or IV HF. Each health domain was low in this sample compared to the general population. SCHFI maintenance and confidence scores were correlated significantly with each health status domain. SCHFI scores explained a significant amount of variance all domains, both in bivariate and multivariate models, except social functioning. In multivariate models, higher levels of self-care were associated with better health in certain domains, but only when both SCFHI management and confidence were high. Conclusion: Improving HF self-care may be a mechanism through which future interventions can improve health in this population

Commonalities and Differences in Correlates of Depressive Symptoms in Men and Women With Heart Failure

Objective: (i) To compare the prevalence and severity of depressive symptoms between men and women enrolled in a large heart failure (HF) registry. (ii) To determine gender differences in predictors of depressive symptoms from demographic, behavioral, clinical, and psychosocial factors in HF patients. Methods: In 622 HF patients (70% male, 61 ± 13 years, 59% NYHA class III/IV), depressive symptoms were assessed by the Patient Health Questionnaire (PHQ-9). Potential correlates were age, ethnicity, education, marital and financial status, smoking, exercise, body mass index (BMI), HF etiology, NYHA class, comorbidities, functional capacity, anxiety, and perceived control. To identify gender-specific correlates of depressive symptoms, separate logistic regression models were built by gender. Results: Correlates of depressive symptoms in men were financial status (p = 0.027), NYHA (p = 0.001); functional capacity (p \u3c 0.001); health perception (p = 0.043); perceived control (p = 0.002) and anxiety (p \u3c 0.001). Correlates of depressive symptoms in women were BMI (p = 0.003); perceived control (p = 0.013) and anxiety (p\u3c 0.001). Conclusions: In HF patients, lowering depressive symptoms may require gender-specific interventions focusing on weight management in women and improving perceived functional capacity in men. Both men and women with HF may benefit from anxiety reduction and increased control

Modifiable Factors Associated With Sleep Dysfunction in Adults With Heart Failure

Background: Sleep dysfunction contributes to poor quality of life in adults with heart failure (HF). The purpose of this study was to identify factors associated with sleep dysfunction that may be modifiable. Methods: Data were collected from 266 subjects enrolled from three sites in the U.S. Sleep dysfunction was measured over the past month with the Pittsburgh Sleep Quality Index, using a score \u3e 10 to indicate sleep dysfunction. Potentially modifiable clinical, behavioral, and psychological factors thought to be associated with sleep dysfunction were analyzed with hierarchical logistic regression analysis. Results: When covariates of age, gender, race, data collection site, and New York Heart Association (NYHA) functional class were entered on the first step, only NYHA was a significant correlate of sleep dysfunction. When the clinical, behavioral, and psychological factors were entered, correlates of sleep dysfunction were the number of drugs known to cause daytime somnolence (OR = 2.08), depression (OR = 1.83), worse overall perceived health (OR = 1.64), and better sleep hygiene (OR = 1.40). Although most (54%) subjects had sleep disordered breathing (SDB), SDB was not a significant predictor of sleep dysfunction. Discussion: Factors associated with sleep dysfunction in HF include medications with sleepiness as a side-effect, depression, poorer health perceptions, and better sleep hygiene. Sleep dysfunction may motivate HF patients to address sleep hygiene. Eliminating medications with sleepiness as a side-effect, treating depression and perceptions of poor health may improve sleep quality in HF patients

Determinants of Excessive Daytime Sleepiness and Fatigue in Adults With Heart Failure

Little is known about excessive daytime sleepiness (EDS) in heart failure (HF). The aim of this cross-sectional descriptive study was to describe the prevalence of EDS and factors associated with it in HF. A secondary purpose was to explore the correlates of fatigue. We enrolled a consecutive sample of 280 adults with a confirmed diagnosis of chronic HF from three outpatient settings in the northeastern United States. Patients with major depressive illness were excluded. Clinical, sociodemographic, behavioral, and perceptual factors were explored as possible correlates of EDS. Using an Epworth Sleepiness Scale score \u3e 10, the prevalence of EDS was 23.6%. Significant determinants of EDS were worse sleep quality (p = .048), worse functional class (p = .004), not taking a diuretic (p = .005), and lack of physical activity (p = .04). Only sleep quality was associated with fatigue (p \u3c .001). Sleep-disordered breathing was not significantly associated with EDS or with fatigue. These factors may be amenable to intervention

Symptom Clusters of Heart Failure

Patients with heart failure (HF) report multiple symptoms. Change in symptoms is an indicator of HF decompensation. Patients have difficulty differentiating HF symptoms from comorbid illness or aging. The study purpose was to identify the number, type, and combination of symptoms in hospitalized HF patients and test relationships with comorbid illness and age. A secondary analysis from a HF registry (N=687) was conducted. The sample was 51.7% female, mean age 71±12.5 years. The theory of unpleasant symptoms informed the study regarding the multidimensional nature of symptoms. Factor analysis of 9 items from the Minnesota Living with HF Questionnaire resulted in three factors, acute and chronic volume overload and emotional distress. Clusters occurred more frequently in older patients, but caused less impact

The Role of Depression in Medication Adherence Among Heart Failure Patients

The purpose of the study was to explore the association between depression and medication adherence in heart failure (HF) patients. Studies have shown that people with depression are likely to be nonadherent to their prescribed medication treatment. But other studies suggest that nonadherence may be overestimated by people with depression. A total of 244 adults with Stage C HF completed the study. Self-reported medication adherence was obtained using the Basel Assessment of Adherence Scale (BAAS); objective data on medication adherence were collected using the electronic Medication Event Monitoring System (MEMS). Depression was measured via self-report with the Patient Health Questionnaire (PHQ-9). There was a significant difference between depressed and nondepressed participants in self-reported medication nonadherence (p = .008), but not in objectively measured medication nonadherence (p = .72). The depressed sample was 2.3 times more likely to self-report poor medication adherence than those who were nondepressed (p = .006)

The Impact on Anxiety and Perceived Control of a Short One-on-One Nursing Intervention Designed to Decrease Treatment Seeking Delay in People With Coronary Heart Disease

Background: Patient delay in seeking treatment for acute coronary syndrome symptoms remains a problem. Thus, it is vital to test interventions to improve this behavior, but at the same time it is essential that interventions not increase anxiety.Purpose: To determine the impact on anxiety and perceived control of an individual face-to-face education and counseling intervention designed to decrease patient delay in seeking treatment for acute coronary syndrome symptoms. Methods: This was a multicenter randomized controlled trial of the intervention in which anxiety data were collected at baseline, 3-months and 12-months. A total of 3522 patients with confirmed coronary artery disease were enrolled; data from 2597 patients with anxiety data at all time points are included. The intervention was a 45 min education and counseling session, in which the social, cognitive and emotional responses to acute coronary syndrome symptoms were discussed as were barriers to early treatment seeking. Repeated measures analysis of covariance was used to compare anxiety and perceived control levels across time between the groups controlling for age, gender, ethnicity, education level, and comorbidities. Results: There were significant differences in anxiety by group (p = 0.03). Anxiety level was stable in patients in the control group, but decreased across time in the intervention group. Perceived control increased across time in the intervention group and remained unchanged in the control group (p = 0.01).Conclusion: Interventions in which cardiac patients directly confront the possibility of an acute cardiac event do not cause anxiety if they provide patients with appropriate strategies for managing symptoms

What Puts Heart Failure Patients at Risk for Poor Medication Adherence?

Background: Medication nonadherence is a major cause of hospitalization in patients with heart failure (HF), which contributes enormously to health care costs. We previously found, using the World Health Organization adherence dimensions, that condition and patient level factors predicted nonadherence in HF. In this study, we assessed a wider variety of condition and patient factors and interactions to improve our ability to identify those at risk for hospitalization. Materials and methods: Medication adherence was measured electronically over the course of 6 months, using the Medication Event Monitoring System (MEMS). A total of 242 HF patients completed the study, and usable MEMS data were available for 218 (90.1%). Participants were primarily white (68.3%), male (64.2%), and retired (44.5%). Education ranged from 8–29 years (mean, 14.0 years; standard deviation, 2.9 years). Ages ranged from 30–89 years (mean, 62.8 years; standard deviation, 11.6 years). Analyses used adaptive methods based on heuristic searches controlled by cross-validation scores. First, individual patient adherence patterns over time were used to categorize patients in poor versus better adherence types. Then, risk factors for poor adherence were identified. Finally, an effective model for predicting poor adherence was identified based on identified risk factors and possible pairwise interactions between them. Results: A total of 63 (28.9%) patients had poor adherence. Three interaction risk factors for poor adherence were identified: a higher number of comorbid conditions with a higher total number of daily medicines, older age with poorer global sleep quality, and fewer months since diagnosis of HF with poorer global sleep quality. Patients had between zero and three risk factors. The odds for poor adherence increased by 2.6 times with a unit increase in the number of risk factors (odds ratio, 2.62; 95% confidence interval, 1.78–3.86; P\u3c0.001). Conclusion: Newly diagnosed, older HF patients with comorbid conditions, polypharmacy, and poor sleep are at risk for poor medication adherence. Interventions addressing these specific barriers are needed

The Impact of Frailty on Health Related Quality of Life in Heart Failure

Background/Aims: Most heart failure (HF) hospital discharges involve people \u3e 65 years, many frail. The purpose of this study was to determine if frailty explains variability in health related quality of life (HRQOL) in older adults with HF over and above known correlates. Methods: A frailty index score was developed by weighting age, number of comorbid conditions, and symptom severity. A multivariate hierarchical regression analysis of known predictors of HRQOLgender, income, ethnicity, health perception, NYHA class — were entered first and then the frailty index was entered and regressed on HRQOL in 2 unique samples. Results: When known predictors were tested on a sample they explained 11% (p 0.14) of the variance in HRQOL; when the frailty index score was added 24% (p 0.001) was explained. When the index was validated in a second sample, known predictors explained 15% (p 0.04) of the variance; with the frailty index score 40% (p 0.000) was explained. Conclusion: Frailty explains significant amounts of variance in HRQOL in HF. Treating comorbid conditions and controlling symptoms may improve HRQOL in HF patients. These findings support the need for further research into the impact of frailty on HRQOL in HF patients