Heesook Son

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.

Application of Pattern Mixture Models to Address Missing Data in Longitudinal Data Analysis Using SPSS

Background:Longitudinal studies are used in nursing research to examine changes over time in health indicators. Traditional approaches to longitudinal analysis of means, such as analysis of variance with repeated measures, are limited to analyzing complete cases. This limitation can lead to biased results due to withdrawal or data omission bias or to imputation of missing data, which can lead to bias toward the null if data are not missing completely at random. Pattern mixture models are useful to evaluate the informativeness of missing data and to adjust linear mixed model (LMM) analyses if missing data are informative. Objectives:The aim of this study was to provide an example of statistical procedures for applying a pattern mixture model to evaluate the informativeness of missing data and conduct analyses of data with informative missingness in longitudinal studies using SPSS. Methods:The data set from the Patients’ and Families’ Psychological Response to Home Automated External Defibrillator Trial was used as an example to examine informativeness of missing data with pattern mixture models and to use a missing data pattern in analysis of longitudinal data. Results:Prevention of withdrawal bias, omitted data bias, and bias toward the null in longitudinal LMMs requires the assessment of the informativeness of the occurrence of missing data. Discussion:Missing data patterns can be incorporated as fixed effects into LMMs to evaluate the contribution of the presence of informative missingness to and control for the effects of missingness on outcomes. Pattern mixture models are a useful method to address the presence and effect of informative missingness in longitudinal studies.

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.

Delirium in Trauma Patients: Prevalence and Predictors

Background Delirium is associated with increased mortality, morbidity, hospital costs, and postdischarge cognitive dysfunction. Most research focuses on nontrauma patients receiving mechanical ventilation in the intensive care unit. Objectives To determine the prevalence and predictors of delirium in trauma patients residing in intensive and intermediate care units of an academic medical center. Methods Trauma patients were screened for delirium by using the Confusion Assessment Method for the Intensive Care Unit. Exclusion criteria included documented brain injury, history of psychosis or cognitive impairment, not speaking English, and hearing or vision loss. Results Of the 215 study patients, 24% were positive for delirium; 36% of patients in the intensive care unit and 11% of patients in the intermediate care unit. Delirium‐positive patients were older (mean age, 53.4 years) than patients who were not (mean age, 44 years; P = .004). Although mechanical ventilation (odds ratio, 4.73, P = .004) was the strongest independent risk factor for delirium, 12% of delirium‐positive patients were not receiving mechanical ventilation. Other predictors of delirium were use of antipsychotic medications, higher scores on the Acute Physiology and Chronic Health Evaluation III, and lower scores on the Richmond Agitation‐Sedation Scale. Conclusions Patients in both the intermediate and intensive care units, whether mechanical ventilation was used or not, were positive for delirium. Delirium prevention protocols may benefit trauma patients regardless of their inpatient location.