Journal of Cardiovascular Nursing最新文献

Background: Multiple behavior change interventions have gained traction in the behavioral health space. Yet, previous studies on health coaching (HC) focused on testing its effect on stages of change for individual health behaviors.

Objective: The purpose of this study was to examine the effects of HC on stages of change across multiple health behavior domains among patients at high risk of coronary heart disease and type 2 diabetes.

Methods: This secondary analysis of a randomized clinical trial included 200 primary care patients (mean age of 47.7 years, 49.0% women, 60.5% Whites) who completed transtheoretical model-based questionnaires related to weight reduction, exercise, healthier eating, and stress management. Multigroup latent transition analysis was used to compare the stage of change distributions and transitions over time between HC and controls at baseline, midpoint of the intervention (3 months), and postintervention (6 months).

Results: Three distinct categories of behavior change were identified ("Contemplation," "Preparation to Action," and "Action"), and membership in these categories changed over time as a function of intervention exposure. Both groups exhibited positive transitions through stages of change from baseline to 3 months. Pronounced intervention effects emerged from 3 to 6 months, revealing larger differences in transition probabilities between the groups. In particular, HC increased patients' likelihood of transitioning from "Contemplation" to both "Preparation for Action" and "Action," as well as from "Preparation for Action" to "Action." The control group remained stagnant during the same period.

Conclusions: Although HC produces changes across multiple behavioral domains, it was most effective for patients who were reluctant or ambivalent about changing their behaviors.

Background: Patients with heart failure (HF) are typically classified based on left ventricular ejection fraction (LVEF). However, this may not optimally reflect distinct groups or predict risk. Therefore, alternative classification methods are needed.

Objective: Our aim was to classify patients with HF based on sociodemographic and clinical data using latent class analysis, assess if latent classes pose varying risks of mortality and rehospitalization, and explore if these classes offer better risk stratification than LVEF or N-terminal prohormone of brain natriuretic peptide (NT-proBNP) alone.

Methods: Data from 1045 patients were analyzed using latent class analysis to identify classes and assess mortality and rehospitalization risks. Kaplan-Meier curves with log-rank tests were used to compare mortality across latent classes, LVEF-based groups, and NT-proBNP-based groups.

Results: Three latent classes were identified. Class 1 (48.8%) comprised middle-aged males with HF with reduced ejection fraction (HFrEF) and high NT-proBNP levels. Class 2 (26.1%) consisted of mainly older females with HF with preserved ejection fraction, high body mass index, hypertension, atrial fibrillation, and anemia. Class 3 (25.2%) included younger patients with HFrEF, high body mass index, and a high smoking rate. Class 1 and 2 had higher mortality risks ( P < .001) and longer rehospitalization durations ( P = .011) than class 3.

Conclusion: Latent class analysis categorized a heterogeneous group of patients with HF into homogeneous classes. These classes provide a close approximation of what could be observed in clinical practice and provide insight into patients at higher risk of mortality and rehospitalization.

Background: Frailty is common in adults with end-stage heart failure receiving a left ventricular assist device (LVAD). Short-term studies show frailty reversal post-LVAD. Little is known about long-term frailty and how frailty relates to key LVAD outcomes, including depression, quality of life (QoL), and cognition beyond 6 months.

Objective: The purpose of this study was to examine physical frailty, depression, QoL, and cognition from pre-LVAD implantation to 3, 6, and 12 months post-LVAD implantation.

Methods: Clinical data and measures of physical frailty, depression, QoL, and cognition pre- and post-LVAD were extracted from an existing institutional database. Descriptive statistics and tests for statistical significance were used to describe and compare changes over time. Frailty trajectories were identified to describe physical frailty from pre-LVAD to 12 months post-LVAD.

Results: The sample (n = 46) was predominantly male (76%), with a mean age of 64.7 ± 11 years, and over half (n = 25) were physically frail. Physical frailty was reduced by nearly half at 12 months. Frailty, depression, and QoL significantly improved at all time points ( P < .001). Improvements in cognition did not reach statistical significance. Recipients of LVAD without improvement in frailty exhibited worse depression, QoL, and cognition scores at 12 months compared with those not frail pre-LVAD or no longer frail post-LVAD implantation.

Conclusion: Some recipients of LVADs experienced physical frailty reversal with benefits sustained long-term. Those without improvement recorded worse long-term patient-reported outcomes. Identifying factors that predict physical frailty response to LVAD implantation is a key area of future research.

Background: Digital health technologies can promote healthy aging, diagnosis, treatment, self-care, and prevention to reduce inequities. However, limited data exist on the feasibility and efficacy of these technologies for healthy lifestyle behaviors and clinical outcomes for older adults at risk for cardiovascular disease.

Objectives: The purpose of this pilot study was to evaluate the feasibility of the study protocol for factors impacting process, resources, and safety and compared changes in eating patterns, physical activity, and clinical outcomes in participants randomized to Get FIT vs Get FIT + at baseline and 12 weeks.

Methods: Older adults (65.6 ± 5.8 years, 61% women, 61% married, 50% Asians, 6% Whites, 33% Hispanics, 11% Blacks) were randomized to Get FIT (n = 24) or Get Fit+ (n = 30) for 12 weeks. Get FIT included 1 in-person counseling session, a participant handbook, an activity tracker, and access to a nutrition app. Get Fit+ added weekly personalized motivational text messages.

Results: All feasibility measures were excellent, with 100% consent and retention at 12 weeks. Both groups gradually increased moderate to vigorous exercise and lowered calorie intake. The Get Fit+ and Get Fit participants reported 6% and 1% weight loss, respectively. Blood pressure, lipid profiles, and HgbAa1C improved for all participants. However, improvements in high-density lipoprotein cholesterol and triglycerides were more significant in the Get FIT + group.

Conclusion: Our findings suggest that Get Fit+ can promote healthy lifestyle behaviors in older adults while lowering cardiovascular disease risk factors. A large Randomized Control Trial is needed to determine the efficacy of this intervention's personalized text-messaging feature in this population.

Background: Despite the increasing recognition of heart failure (HF) as a critical public health issue for both rural populations and women, the intersection of rurality and female sex in HF remains underexplored.

Objective: The objective of this scoping review was to synthesize the evidence on the intersection of rurality with female sex and gender in HF, examining how individual, interpersonal, organizational, or community factors influence the experience, management, and outcomes of HF in women.

Methods: Using the PubMed, Embase, and Cumulative Index to Nursing and Allied Health Literature databases, a literature search was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. Findings were organized by level of the social-ecological model (SEM).

Results: Among the 1119 articles reviewed, 11 original studies met inclusion criteria, and their results were synthesized. Rural women were found to be at higher risk of developing HF when compared with their male and urban counterparts and tended to have worse outcomes, including higher rates of hospitalizations and mortality. Rural women were also less likely to receive evidence-based care and used healthcare services less.

Conclusions: Findings underscore the intricate interplay between SEM factors that influence HF outcomes in rural women. While highlighting the disparities this demographic group faces, the findings also emphasize the urgency for targeted interventions to address these multifaceted disparities. Future research should further explore the interactions between individual, interpersonal, organizational, and community factors to improve the care and outcomes of rural women living with HF.

Background: Existing literature indicates that benefit finding and social support play protective roles against depressive symptoms. However, there is a lack of understanding regarding the interplay between benefit finding, social support, and depressive symptoms within the dyadic context of stroke survivor-spousal caregiver relationships.

Objective: The objective of this study is to investigate the relationships among benefit finding, social support, and depressive symptoms in young and middle-aged stroke survivors and their spouse caregivers. In addition, the mediating role of social support in the association between benefit finding and depressive symptoms is explored.

Methods: A total of 203 pairs of stroke survivor-spouse caregiver were included in the study. Depressive symptoms, social support, and benefit finding were measured using the Patient Health Questionnaire-9, the Perceived Social Support Scale, the Benefit Finding Scale, and the Caregiver Benefit Finding Scale. The Actor-Partner Interdependence Mediation Model was used to assess direct and indirect effect.

Results: The findings revealed a significant negative association between higher levels of benefit finding and lower depressive symptoms in both stroke survivors (actor effect, -0.126) and spousal caregivers (partner effect, -0.044). Perceived social support emerged as a significant mediator in the relationship between benefit finding and depressive symptoms in spousal caregivers (indirect effect, -0.024). Furthermore, spousal caregivers' perceived social support served as a mediating variable between caregiver benefit finding and depressive symptoms in stroke survivors (indirect effect, -0.023).

Conclusion: The study underscores the interdependence between stroke survivors and spousal caregivers, highlighting the mutual influence they have on each other. Consequently, targeted interventions addressing both members of the dyad, with a focus on enhancing benefit finding and social support, could prove beneficial in ameliorating depressive symptoms in stroke survivor-spousal caregiver.

Background: The symptom network can provide a visual insight into the symptom mechanisms. However, few study authors have explored the multidimensional symptom network of patients with atrial fibrillation (AF).

Objectives: We aimed to identify the core symptom and symptom clusters of patients with AF by generating a symptom network. Furthermore, we wanted to identify multiple characteristics related to symptom clusters.

Methods: This is a cross-sectional study. A total of 384 patients with AF at Tianjin Medical University General Hospital were enrolled. The University of Toronto Atrial Fibrillation Severity Scale was used to assess AF symptoms. Network analysis was used to explore the core symptom and symptom cluster.

Results: Shortness of breath at rest ( rs = 1.189, rc = 0.024), exercise intolerance ( rs = 1.116), shortness of breath during physical activity ( rs = 1.055, rc = 0.022), and fatigue at rest ( rc = 0.020) have the top centrality for strength and closeness. The top 3 symptoms of bridge strength were shortness of breath at rest ( rs = 0.264), dizziness ( rs = 0.208), and palpitations ( rs = 0.207). Atrial fibrillation symptoms could be clustered into the breathless cluster and the cardiac cluster. We have identified multiple factors such as mental health status, left ventricular ejection fraction, heart failure, sex, B-type natriuretic peptide, and chronic obstructive pulmonary disease as significant contributors within the breathless cluster, whereas sex, mental health status, and history of radiofrequency ablation were strongly associated with the cardiac cluster, holding promise in elucidating the underlying mechanisms of these symptoms.

Conclusion: Special attention should be given to shortness of breath at rest as its core and bridging role in patients' symptoms. Furthermore, both the breathless and cardiac clusters are common among patients. Network analysis reveals direct connections between symptoms, symptom clusters, and their influencing factors, providing a foundation for clinicians to effectively manage patients' symptoms.