Heart Failure, Congestive Clinical Trial
Official title:
ENABLE: CHF-PC (Educate, Nurture, Advise, Before Life Ends: Comprehensive Heartcare for Patients and Caregivers)
Background: Early palliative care (EPC) is recommended but rarely integrated with advanced
heart failure (HF) care. This pilot study engaged patients and family caregivers to study the
feasibility and site differences in a two-site EPC trial, ENABLE CHF-PC (Educate, Nurture,
Advise, Before Life Ends Comprehensive Heartcare for Patients and Caregivers).
An EPC feasibility study (4/1/14-8/31/15) was conducted for patients with New York Heart
Association (NYHA) Functional Class III/IV HF and their caregivers in academic medical
centers in the northeast and southeast U.S. The EPC intervention comprised: 1) an in-person
palliative care consultation; and 2) telephonic nurse coach sessions and monthly calls.
Patient- and caregiver-reported outcomes were collected for quality of life (QOL), symptom,
health, anxiety, and depression outcomes at baseline, 12- and 24-weeks. Linear mixed-models
were used to assess baseline to week 24 longitudinal changes. The intervention was tailored
to rural, older adults (ageā„65) with advanced HF in reducing HF morbidity and improving
patient and caregiver QOL and quality of care.
High quality trials have demonstrated positive patient and family caregiver outcomes from
early palliative care (EPC) in cancer However, given the difficulties in prognostication, the
prevalence of sudden cardiac death, and an erratic illness trajectory, it is not clear when
or how to integrate palliative care in HF. Furthermore, the high morbidity and mortality of
HF in persons with low income, poor education, minority race, and residence in rural,
medically-underserviced areas further complicates appropriate timing of integration.
To address these challenges, patients and family members were actively engaged to aid in the
development of ENABLE CHF-PC (Educate, Nurture, Advise, Before Life Ends Comprehensive
Heartcare for Patients and Caregivers), a telephonic EPC intervention for rural-dwelling,
underserved HF patients and their family caregivers. In a proof-of-concept, formative
evaluation study, materials and protocols were translated from our successful EPC ENABLE
oncology model to a HF population. This study demonstrated acceptability, feasibility, and a
signal of potential efficacy in an educationally, socioeconomically, and racially homogeneous
sample of 11 patient-caregiver dyads. Thus, the current ENABLE CHF-PC feasibility trial was
conducted in a northeastern and a southeastern US academic center to capture the perspectives
of a more demographically and culturally-diverse sample. The purpose of this study was to: 1)
determine the feasibility of recruiting and retaining patient-caregiver dyads for 24 weeks in
a rural, racially-diverse sample and 2) explore longitudinal patient and caregiver outcomes
including QOL, global health, anxiety, and depression to inform intervention and protocol
modifications for a larger clinical efficacy trial.
Study Design: In this feasibility study, conducted April 1, 2014 to December 31, 2015,
individuals with American College of Cardiology (ACC) /American Heart Association (AHA) Class
C/D and/or NYHA Stage III/IV HF and their family caregivers received the ENABLE CHF-PC
intervention and were followed for 24 weeks. The study protocol was approved by the
institutional review boards of Dartmouth College (Lebanon, New Hampshire) and the University
of Alabama at Birmingham (Birmingham, Alabama).
Setting and Sample: Study participants were recruited from cardiology clinics at
Dartmouth-Hitchcock Medical Center (DHMC) and the University of Alabama at Birmingham (UAB).
Study coordinators at both sites reviewed outpatient cardiology clinic schedules to identify
eligible patients. Following physician approval, a study coordinator approached patients and
their caregivers during a clinic appointment to explain the study and obtain consent.
Data Collection and Measures: Study coordinators completed measures with patients and
caregivers by phone at baseline, 12- and 24-weeks. Baseline demographics included age,
gender, race/ethnicity, religion, marital and work status, educational level, and medical
insurance. Clinical characteristics abstracted from electronic health records included NYHA
class, ejection fraction, presence of an implanted heart device, medications, and laboratory
data. These data were entered into the Seattle Heart Failure Model (SHFM) a web-based
calculator to compute 1-, 2- and 5-year survival estimates
https://depts.washington.edu/shfm/). Nurse coaches also informed patients and caregivers that
the purpose of this pilot trial was to determine acceptability in a new population - patients
with heart failure from 2 distinctly different regions/cultures. Nurses recorded sessions,
and tracked patient and caregiver feedback on intervention components that were found to be
helpful or in need of improvement.
Statistical Analysis: The feasibility primary aim was determined by monitoring study status
(enrolled, deceased, lost to follow-up) and calculating intervention and measurement
completion (e.g. actual # completed/possible # per protocol). Patient and caregiver
demographic characteristics were tabulated and compared between sites with bivariate tests of
association and effect sizes (Cohen's d or d-equivalent or nominal variables). Associations
were assessed between baseline characteristics and participant attrition using simple
logistic regressions. Estimated odds ratios were used to determine associations between
patient characteristics and attrition.
Longitudinal, fitted, linear mixed methods, adjusted for covariates associated with attrition
were used to estimate participant-reported outcomes' changes from baseline to follow-up
(12-week and 24-week means combined). Change estimates were transformed to effect sizes
(Cohen's d) using baseline estimates of pooled standard deviations. Change was estimated
overall and by site. All analyses were conducted using SAS v9.4.
Due to the exploratory nature of the study, the analysis relied on effect size estimation
using Cohen's guidelines for magnitude of effect size d (i.e. small: 0.2, moderate: 0.5, and
large: 0.8) rather than hypothesis testing to interpret results; however p-values are also
provided for completeness.
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