BACKGROUND: Although current guidelines emphasize the importance of social support to the success of left ventricular assist device (LVAD) therapy, few studies examine the influence of the caregiver on patient outcomes or quantify the impact of LVAD caregiving on caregiver outcomes. The purpose of this analysis was to identify patient and caregiver determinants of patient quality of life (QOL) and caregiver strain in response to LVAD therapy. METHODS AND RESULTS: Data on patients receiving LVAD therapy and their caregivers (n=50 dyads) were prospectively collected pre-implantation and 1, 3, and 6 months post-implantation. Growth curve modeling was used to describe change in patient QOL (Kansas City Cardiomyopathy Questionnaire) and caregiver strain (Multidimensional Caregiver Strain Index). Patient QOL improved most in the first month (β=23.22±3.76, P<0.001), followed by gradual gains over 6 months (β=1.90±0.64, P<0.01). Caregivers experienced worsening of strain in the first month (β=4.30±1.42, P<0.01), followed by gradual resolution to pre-implantation levels by 6 months (β=-0.71±0.23, P<0.01). Worse pre-implantation patient symptoms were associated with greater improvement in patient QOL (β=0.53±0.19, P<0.01) but worsening caregiver strain (β=0.15±0.07, P=0.04). Better relationship quality was associated with greater improvement in patient QOL (β=14.39±5.85, P=0.01) and less pre-implantation caregiver strain (β=-9.31±2.28, P<0.001). Nonspousal caregivers experienced less pre-implantation strain (β=-8.60±3.10, P=0.01), and patients with nonspousal caregivers had less improvement in QOL (β=-3.70±1.62, P=0.02). CONCLUSIONS: A combination of patient and caregiver characteristics predicts patient and caregiver response to LVAD therapy. Including caregiver factors in future studies may be helpful in developing interventions that improve patient and caregiver outcomes, together.

BACKGROUND: Treatment of heart failure (HF) is particularly complex in the presence of comorbidities. We sought to identify and associate comorbidity profiles with inpatient outcomes during HF hospitalizations. METHODS: Latent mixture modeling was used to identify common profiles of comorbidities during adult hospitalizations for HF from the 2009 Nationwide Inpatient Sample (n = 192,327). RESULTS: Most discharges were characterized by common comorbidities. A lifestyle profile was characterized by a high prevalence of uncomplicated diabetes, hypertension, chronic pulmonary disorders and obesity. A renal profile had the highest prevalence of renal disease, complicated diabetes, and fluid and electrolyte imbalances. A neurovascular profile represented the highest prevalence of cerebrovascular disease, paralysis, myocardial infarction and peripheral vascular disease. Relative to the common profile, the lifestyle profile was associated with a 15% longer length of stay (LOS) and 12% greater cost, the renal profile was associated with a 30% higher risk of death, 27% longer LOS and 24% greater cost, and the neurovascular profile was associated with a 45% higher risk of death, 34% longer LOS and 37% greater cost (all p < 0.001). CONCLUSIONS: Comorbidity profiles are helpful in identifying adults at higher risk of death, longer length of stay, and accumulating greater costs during hospitalizations for HF.

Background

The relationship between physical and affective symptom clusters in heart failure (HF) is unclear.

Objectives

To identify associations between physical and affective symptom clusters in HF and to quantify outcomes and determinants of symptom subgroups.

Methods

This was a secondary analysis of data from two cohort studies among adults with HF. Physical and affective symptom clusters were compared using cross-classification modeling. Cox proportional hazards modeling and multinomial logistic regression were used to identify outcomes and determinants of symptom subgroups, respectively.

Results

In this young, mostly male sample (n = 274), physical and affective symptom clusters were cross-classified in a model with acceptable fit. Three symptom subgroups were identified: congruent-mild (69.3%), incongruent (13.9%), and congruent-severe (16.8%). Compared to the congruent-mild symptom group, the incongruent symptom group had significantly worse 180-day event-free survival.

Conclusion

Congruence between physical and affective symptom clusters should be considered when identifying patients at higher risk for poor outcomes.