Deborah W. Chapa

Poor social support is associated with increases in depression but not anxiety over 2 years in heart failure outpatients.

Background:Heart failure (HF) is a major health problem in the United States, affecting 5.7 million American adults. Psychosocial distress, in particular depression, contributes to morbidity and mortality in patients with HF. Little is known about the interrelationship among disease severity, social support, and depression. Objective:The aim of this study was to examine the contributions of social support and disease severity to longitudinal changes in depression and anxiety of outpatients with HF. Methods:Patients (N = 108) enrolled in the Psychosocial Factors Outcome Study completed the Beck Depression Inventory-II, the State Trait Anxiety Inventory, and the Social Support Questionnaire-6 at study entry and every 6 months for up to 2 years. Results:At baseline, 30% of the patients were depressed and 42% were anxious. Social support amount contributed to changes in depression (P = .044) but not anxiety (P = .856). Depression increased over time for patients who had lower initial social support amount. Depression did not increase for those with higher initial social support amount. Neither New York Heart Association class nor treatment group (placebo or implantable cardioverter defibrillator) interacted with time to predict depression, which indicates that changes in depression were parallel for patients with New York Heart Association class II and class III HF and for those who received implantable cardioverter defibrillators and those who did not. Assessment of patients with HF should include depression and social support. Interventions to enhance social support among patients with HF who have low social support may help alleviate the development of depression. Conclusions:Reducing psychological distress and increasing social support may improve health outcomes among HF outpatients. It is important for studies of HF to include assessment of depression, anxiety, and social support and evaluate their contributions to health outcomes.

The influence of depression and anxiety symptoms on health-related quality of life in patients with atrial fibrillation and atrial flutter.

Background:The health-related quality of life (HRQoL) of patients with atrial fibrillation (AF) and atrial flutter (AFL) is an important issue in cardiovascular health management. Determinants of poor HRQoL of AF/AFL patients require further elucidation. Objectives:The purpose of this study was to evaluate the influencing factors related to the HRQoL of AF/AFL patients. Methods:In 150 consecutively recruited patients in a multicenter, cross-sectional study from April 2010 to February 2011, depression and anxiety were measured with the Beck Depression Inventory II and the State Trait Anxiety Inventory, respectively, whereas HRQoL was assessed with the generic Medical Outcomes Survey 36-Item Short-Form Survey version 2 and the Symptom Checklist. Linear regression modeling was performed to determine predictors of HRQoL among variables, including the patients’ age, gender, race, marital status, type of AF/AFL, frequency of AF/AFL symptoms, time since diagnosis, and anxiety and depression symptoms. Results:Female patients with AF/AFL reported poorer physical HRQoL than male patients did (P < .001, R2 = 0.391). Symptoms of depression and anxiety were found to be associated with poorer HRQoL (P < .001, R2 = 0.482). Anxiety was the strongest predictor of the mental component of the Medical Outcomes Survey 36-Item Short-Form Survey version 2 and the Symptom Checklist. Younger patients had worse AF/AFL-related symptoms and severity than older patients did (P < .001, R2 = 0.302). Increased frequency of symptomatic episodes was associated with worse AF/AFL-related symptoms and severity. Conclusion:In conclusion, depression and anxiety symptoms and female gender emerged as clear indicators of poor HRQoL in AF/AFL patients. These risk factors should be used to identify patients who may require additional evaluation and treatment efforts to manage their cardiac conditions or HRQoL. Interventions to improve HRQoL in these individuals require further investigation.

Pathophysiological Relationships Between Heart Failure and Depression and Anxiety

Depression and anxiety are common comorbid conditions in patients with heart failure. Patients with heart failure and depression have increased mortality. The association of anxiety with increased mortality in patients with heart failure is not established. The purpose of this article is to illustrate the similarities of the underlying pathophysiology of heart failure, depression, and anxiety by using the Biopsychosocial Holistic Model of Cardiovascular Health. Depression and anxiety affect biological processes of cardiovascular function in patients with heart failure by altering neurohormonal function via activation of the hypothalamic-pituitary-adrenal axis, autonomic dysregulation, and activation of cytokine cascades and platelets. Patients with heart failure and depression or anxiety may exhibit a continued cycle of heart failure progression, increased depression, and increased anxiety. Understanding the underlying pathophysiological relationships in patients with heart failure who experience comorbid depression and/or anxiety is critical in order to implement appropriate treatments, educate patients and caregivers, and educate other health professionals.

Gender differences in stroke, mortality, and hospitalization among patients with atrial fibrillation: A systematic review

OBJECTIVE To conduct a systematic review of gender differences in stroke, mortality, and hospitalization for patients with atrial fibrillation and/or flutter (AF/Afl). METHODS Full texts, published, peer-reviewed, English language articles from 1999 through July 2014 were examined. Articles with populations of patients with AF/Afl were included if they conducted longitudinal analysis of any of three outcomes: stroke, mortality, and hospitalization, and reported or compared at least one of the outcomes according to gender. RESULTS Seventeen articles were included: sixteen on stroke, nine on mortality, and one on hospitalization. In nine articles women had more strokes (RRs 0.89-1.9). Findings about gender differences in mortality (RRs 0.69-2.8) and hospitalizations were equivocal. CONCLUSIONS Few articles examine differences in outcomes between men and women with AF/Afl. Given the prevalence of AF/Afl and health care costs it is vital to determine gender differences to evaluate appropriate therapies to decrease stroke, mortality, and hospitalizations.

Is health-related quality of life a predictor of hospitalization or mortality among women or men with atrial fibrillation?

Background:Little is known about predictors of mortality or hospitalization in women compared with men in patients with atrial fibrillation (AF). Although there are established gender differences in patients with coronary artery disease (CAD), differences have not been established in AF. Objectives:The aim of this study was to examine clinical and health-related quality of life (HRQOL) predictors of mortality and 1-year hospitalization in women compared with men with AF. Methods:Limited-use data from the National Institutes of Health/National Heart, Lung, and Blood Institute Atrial Fibrillation Follow-up Investigation of Rhythm Management clinical trial provided the sample of 693 patients with AF, 262 women and 431 men. Clinical predictors examined were heart failure (HF), CAD, left ventricular ejection fraction, diabetes, stroke, and age. Predictors of HRQOL included overall HRQOL (Medical Outcomes Study Short Form-36 physical [PCS] and mental component scores) and cardiovascular HRQOL using Quality of Life Index–Cardiac Version. Results:Mortality did not differ (women, 11.4%; men, 14.5%; &khgr;21 = 0.437, P = .509) according to gender, with mean 3.5-year follow-up. Different variables independently predicted mortality for women and men. For women, diabetes (hazard ratio [HR], 3.415; P = .003), HF (HR, 2.346; P = .027), stroke (HR, 2.41; P = .032), and age (HR, 1.117; P = .002), and for men, CAD (HR, 1.914; P = 02), age (HR, 1.103, P = < .001), worse PCS (HR, 1.089, P = .001), and worse Quality of Life Index–Cardiac Version score (HR, 1.402, P = .025) independently predicted mortality.One-year hospitalization (women, 38.9%; men, 36.4%) did not differ by gender (&khgr;21 = 0.914, P = .339). Different variables independently predicted 1-year hospitalization—for women: diabetes (odds ratio [OR], 2.359; P = .022), worse PCS (OR, 1.070; P = .003), and rhythm control trial arm (OR, 2.111; P = .006); for men: HF (OR, 2.072; P = .007), worse PCS (OR, 1.045; P = .019), living alone (OR, 1.913; P = .036), and rhythm control trial arm (OR, 2.113; P < .001). Conclusion:Only clinical status predicted mortality among women; HRQOL and clinical status predicted mortality among men. Both clinical and HRQOL variables predicted hospitalization for women and men. Increased monitoring of HRQOL and interventions designed to target the clinical and HRQOL predictors could impact mortality and hospitalization. Nursing interventions may prove effective for modifying most of the predictors of mortality and hospitalization for women and men with AF.

Using preappraised evidence sources to guide practice decisions.

Purpose: The purpose of this article is two‐fold. The first is to describe preappraised evidence sources or a top‐down approach to obtaining the best available evidence. The second purpose of the article is to describe how to incorporate preappraised evidence into clinical decision making with the Best Practice Decision Guide. Data Sources: The Best Practice Decision Guide begins with a query of preappraised and filtered electronic sources to obtain recommended evidence summaries, or a so‐called “top‐down” approach to obtaining the best available evidence. Conclusions: Information on the major issues and dilemmas encountered at each step is presented, including evaluation of clinical practice guidelines and the consideration of relevant studies to particular patients or subpopulations. Implications for Practice: Recommendations for other resources to use in the appraisal process and in making final practice decision are also described in the article.