A pilot clinical trial of a self-management intervention in patients with a left ventricular assist device.

Self-management is a health behavior known to predict treatment outcomes in patients with multiple co-morbidities and/or chronic conditions. However, the self-management process and outcomes in the left-ventricular assist device (LVAD) population are understudied. This pilot randomized control trial (RCT) evaluated the feasibility of a novel "smartphone app-directed and nurse-supported self-management intervention" in patients implanted with durable LVADs. Assessments included behavioral (self-efficacy and adherence), clinical (complications), and healthcare utilization (unplanned clinic, emergency room (ER) visits, and re-hospitalization) outcomes, completed at baseline (pre-hospital discharge) and months 1, 3, and 6 post-hospital discharge. Intervention patients (n = 14) had favorable patterns/trends of results across study outcomes than control patients (n = 16). Notably, intervention patients had much lower complications and healthcare utilization rates than controls. For example, intervention patients had 2 (14.3%) driveline infections in 6 months while control patients had 3 (19.0%). Additionally, at month 3, intervention patients had 0% ER visits versus 36% of control patients. At month 6, the mean cumulative number of re-hospitalizations for the control group was higher (0.9 ± 0.93) than intervention (0.3 ± 0.61) group. Despite the small sample size and limitations of feasibility/pilot studies, our outcomes data appeared to favor the novel intervention. Lessons learned from this study suggest the intervention should be implemented for 6 months post-hospital discharge. Further research is needed including large and rigorous multi-center RCTs to generate knowledge explaining the mechanism of the effect of self-management on LVAD treatment outcomes.

Patient-Reported Issues Following Left Ventricular Assist Device Implantation Hospitalization.

The purpose of this study was to explore the information reported by patients via a smartphone application (VAD Care App) used for left ventricular assist device (LVAD) self-care monitoring and reporting post hospital discharge. Specific aims were to examine the type and frequency of issues reported by patients through the app during months 1, 3, and 6 postdischarge. An exploratory-descriptive research design was used with 17 patients (12 males and 5 females) with durable LVADs, mean age of 48.6 ± 16 years. Data generated by the patients' daily smartphone app usage more than 6 months were extracted from the server. Data were coded and clustered according to issues reported by patients via the app and analyzed with descriptive statistics. Three clusters of issues were found: physiologic, behavioral (self-care), and signs and symptoms. LVAD flows and pulsatility indices, hypertension, driveline care, and heart failure symptoms were worse at month 1, and then appeared to improve at months 3-6. However, abnormal levels of the international normalization ratio were common at all assessment points. Further research is needed to understand the mechanism of the reported issues on treatment outcomes, then develop and test interventions to inform evidence-based practice and clinical guidelines for smartphone apps used in LVAD self-care monitoring.

Relationship between device acceptance and patient-reported outcomes in Left Ventricular Assist Device (LVAD) recipients.

The number of Left Ventricular Assist Devices (LVADs) implanted each year is rising. Nevertheless, there are minimal data on device acceptance after LVAD implant, and on its relationship with patient-reported outcomes. We designed a cross-sectional study to address this knowledge gap and test the hypothesis that low device acceptance is associated with poorer quality of life, depression and anxiety. Self-report questionnaires were administered to assess quality of life (12-item Kansas City Cardiomyopathy Questionnaire quality of life subscale), level of anxiety (7-item Generalized Anxiety Disorder; GAD-7), level of depression (9-item Patient Health Questionnaire; PHQ-9) and device acceptance (Florida Patient Acceptance Survey; FPAS) to 101 consecutive patients presenting to LVAD clinic. Regression analysis showed a strong correlation between device acceptance and both psychological distress (p < 0.001) and quality of life (p < 0.001). Analysis of the sub-scales of the FPAS showed that patients had significant body image concerns, but return to function and device-related distress were the main drivers of the observed correlation between device acceptance and patient well-being. Younger age was associated with lower device acceptance (r = 0.36, p < 0.001) and lower quality of life (r = 0.54, p < 0.001). These findings suggest that interventions targeting device acceptance should be explored to improve outcomes in LVAD recipients.

Advancing the Science of Self-Management in Adults With Long-Term Left Ventricular Assist Devices.

This study tested the applicability of the individual and family self-management theory (IFSMT) to self-management (SM) in patients with left ventricular assist devices (LVADs). From an existing data set, we extracted the following variables that correspond to IFSMT's conceptual dimensions: anxiety, depression, and cognition (context dimension); self-efficacy (SM process dimension); adherence and quality of life (QOL; outcome dimensions). Descriptive statistics and partial least squares path modeling procedures were used for data analyses. A total of 100 patients (mean age 52 ± 13.4 years) with continuous flow LVAD designs comprised the present study. Most patients were White (78%), married (69%), college-educated (72%), and on disability (53%). Their mean anxiety and depression scores were slightly above normal, while their cognitive function scores were slightly lower than normal. LVAD care self-efficacy, adherence, and QOL were within normal ranges. Factor loadings ranged from 0.50 to 1.0, and there were significant forward path relationships among the context, process, and outcome dimensions (ß ranges from 0.02 to 0.60, all P values < 0.05). In conclusion, the IFSMT provides a good fit for SM in LVAD. Further research is needed to clarify how best to improve LVAD SM practice and treatment outcomes.

Development and Feasibility of Self-Management Application in Left-Ventricular Assist Devices.

Despite major advancements in mechanical circulatory support, the self-management (SM) for patients with a left-ventricular assist device (LVAD) remains complex and challenging for patients and their caregivers. We have developed a mobile phone application (VAD Care App) to organize and simplify the LVAD SM process. This article describes the development and feasibility study of the app as an SM tool for LVAD patients and caregivers requiring support from ventricular assist device (VAD) coordinators. The specific aim was to evaluate the app's acceptability and usability and the users' competency. App features included an automated alert, data collection/reporting, and dynamic real-time interaction systems embedded in the LVAD SM process. Beta-testing of the prototype was completed by five adults. For the feasibility study, we employed a mixed-method descriptive research design involving nine patients and nine caregivers from two VAD centers in the Midwest. We asked them to use the app daily for more than 30 days and complete an app Evaluation Questionnaire and an interview. The questionnaire uses a five-point rating scale (1 = strongly disagree to 5 = strongly agree) evaluating usability, acceptability, and competency domains. Data generated from the questionnaires and interviews were analyzed with descriptive statistics and content analytic procedures. A total of 16 users (eight patients [all male] and eight caregivers [seven female]) aged 22 to 68 years completed the 30 day study. Median acceptability, usability, and competency scores were 4.6, 4.5, and 4.7, respectively. Based on the data, it is feasible for patients and caregivers to use an app as an LVAD SM tool warranting further research.

Preliminary investigation of multiparametric strain Z-score (MPZS) computation using displacement encoding with simulated echoes (DENSE) and radial point interpretation method (RPIM).

PURPOSE: To describe and assess an automated normalization method for identifying sentinel (septal) regions of myocardial dysfunction in nonischemic, nonvalvular dilated cardiomyopathy (DCM), using an unprecedented combination of the navigator-gated 3D spiral displacement encoding with stimulated echoes (DENSE) magnetic resonance imaging (MRI), radial point interpolation (RPIM) and multiparametric strain z-score (MPZS). MATERIALS AND METHODS: Navigator-gated 3D spiral DENSE, in a 1.5T MRI machine, was used for acquiring the displacement encoded complex images, MR Analytical Software System (MASS) for automated boundary detection and automated meshfree RPIM for left-ventricular (LV) myocardial strain computation to analyze MPZS in 36 subjects (with n = 17 DCM patients). Pearson's r correlation established relations between global/sentinel MPZS and ejection fraction (EF). The time taken for combined RPIM-MPZS computations was recorded. RESULTS: Maximum MPZS differences were seen between anteroseptal and posterolateral regions in the base (2.0 ± 0.3 vs. 0.9 ± 0.5) and the mid-wall (2.1 ± 0.4 vs. 1.0 ± 0.4). These regional differences were found to be consistent with historically documented septal injury in nonischemic DCM. Correlations were 0.6 between global MPZS and EF, and 0.7 between sentinel MPZS and EF. The time taken for combined RPIM-MPZS computations per subject was 18.9 ± 5.9 seconds. CONCLUSION: Heterogeneous contractility found in the sentinel regions with the current automated MPZS computation scheme and the correlation found between MPZS and EF may lead to the creation of a new clinical metric in LV DCM surveillance. J. MAGN. RESON. IMAGING 2016;44:993-1002.

Magnetic resonance imaging-based multiparametric systolic strain analysis and regional contractile heterogeneity in patients with dilated cardiomyopathy.

BACKGROUND: Myocardial systolic strain patterns in dilated cardiomyopathy are considered non-homogeneous but have not been investigated with magnetic resonance imaging (MRI)-based multiparametric systolic strain analysis. Left ventricular (LV) 3-dimensional (3D) multiparametric systolic strain analysis is sensitive to regional contractility and is generated from sequential MRI of tissue-tagging gridline-point displacements. METHODS: Sixty normal human volunteers underwent MRI-based 3D systolic strain analysis to supply normal average and standard deviation values for each of three strain parameters at each of 15,300 individual LV grid-points. Patient-specific multiparametric systolic strain data from each dilated cardiomyopathy patient (n = 10) were then subjected to a point-by-point comparison (n = 15,300 LV points) to the normal strain database for three individual strain components (45,900 database comparisons per patient). The resulting composite multiparametric Z-score values (standard deviation from normal average) were color contour mapped over patient-specific 3D LV geometry to detect the normalized regional contractile patterns associated with dilated cardiomyopathy. RESULTS: Average multiparametric strain Z-score values varied significantly according to ventricular level (p = 0.001) and region (p = 0.003). Apical Z-scores were significantly less than those in both the base (p = 0.037) and mid-ventricle (p = 0.002), whereas anterolateral wall Z-scores were less than those in the anteroseptal (p = 0.023) and posteroseptal walls (p = 0.028). CONCLUSIONS: MRI-based multiparametric systolic strain analysis suggests that myocardial systolic strain in patients with dilated cardiomyopathy has a heterogeneous regional distribution and, on average, falls almost 2 standard deviations from normal.