Study for Deployment of American Heart Association Heart Failure Protocols and Educational Content Within the Intel® Health Guide System With a Congestive Heart Failure Cohort
Phase: NA
Conditions: Heart Failure
Sponsor: American Heart Association

STUDY FOR THE DEPLOYMENT OF 
AMERICAN HEART ASSOCIATION HEART 
FAILURE PROTOCOLS AND EDUCATIONAL 
CONTENT WITHIN THE INTEL® HEALTH 
GUIDE SYSTEM WITH A CONGESTIVE 
HEART FAILURE COHORT 
 
 
 
NCT01275846 
NOVEMBER 4, 2011 

1 
 
An Observational Study of Deployment of AHA Heart Failure Protocols and 
Educational Content within the Intel-GE Care Innovations™ Guide System 
Following Hospital Discharge 
 
 
Ileana L. Piña, MD, MPH*, Nancy M. Albert, PhD, CCNS, CCRN **, Gregg C. Fonarow, MD, 
Gloria Catha†, Patrick Wayte†, Tracy Plank ***, David Bruckman, MS*, George Kikano, MD* 
*Case Western Reserve University, Cleveland, OH,**Cleveland Clinic Foundation, Cleveland, 
OH, University of California at Los Angeles, Los Angeles, CA;  
†American Heart Association, Dallas, TX 
***University Hospitals At Case Medical Center of Cleveland 
 
 
 
Abbreviated title:  AHA Heart Failure Protocols and Home Monitoring Post Discharge 
Correspondence, galley proofs, reprint requests: 
Ileana L. Piña, MD, MPH 
Division of Cardiology 
Montefiore Medical Center 
Bronx, NY 
ilpina@montefiore.org 
 
 
 

2 
 
Abstract   
Background:   The rate of 30-day rehospitalization for patients with heart failure (HF) is of great 
concern. Published studies have emphasized the need for adequate care after hospital admissions and for 
early post-discharge visits with providers.  The purpose of this study was to examine short-term (60-day) 
health-related quality of life and rehospitalization after implementation of the Intel® Health Guide 
System (HGS) deployed with American Heart Association (AHA) guideline-based HF protocols.  
Methods:  This was a feasibility project of patients who were candidates for home care after a 
hospitalization for HF.  The HGS system was delivered to patient homes. Protocols were deployed to the 
HGS for patients to assess key vital signs, and provide related educational content on a daily, weekly, or 
monthly basis for 60 days.  Patients and caregivers could access the health education component and 
perform additional vitals assessments at any time.  Utility of the system and adherence to scheduled 
sessions were measured.   Health status was assessed pre and post monitoring periods. Results:  Patients 
(n=26, 62% NYHA Class II) were enrolled, and were primarily older women with HF and preserved 
systolic function.    Health status significantly improved between baseline and end of study.  Utility scores 
and adherence were high.  At 30 days, the all-cause and HF rehospitalization rates were 23% and 15%, 
respectively. Greater utility scores were correlated with improvements in health status.   Adherence and 
utility for those not rehospitalized were significantly greater than for those rehospitalized. Conclusion: A 
telehealth system embedded with AHA education information on HF themes is feasible and may be a 
useful adjunct to homecare after a HF hospitalization.  Utility and adherence to the use of the system was 
associated with a lower rate of rehospitalization.  A larger trial is warranted.  

3 
 
Introduction:   
      Heart failure (HF) is the most common DRG among elderly people and is associated with substantial 
morbidity, mortality, and healthcare expenditures. 1;1  Despite adequate and efficient hospital care, the rate 
of 30-day rehospitalization for patients with HF is of great concern to health care providers and payers.  
Of over 11 million Medicare Beneficiaries, 19.6% are rehospitalized within 30 days and 34% within 90 
days.2  Readmission rate data have become available to providers and patients on CMS’ Hospital 
Compare web site and notably vary geographically and within each state.  As hospitals and healthcare 
providers attempt to improve early morbidity rates due to pending reimbursement cuts, transitioning 
patients to home from the hospital has taken on new importance.  Published studies have emphasized the 
need for adequate care after hospital admissions and for early post-discharge visits with providers. 3-5  
Unfortunately, there are many barriers that face patients after hospital discharge. Barriers include the 
ability to see a provider within 7-10 days, availability of transportation and confusion about complex 
medication regimens.  Since a growing number of discharged patients are elderly and home bound, home 
health care has become a critical source of patient follow-up.  In their own home setting, patients should 
be followed in parallel to actual outpatient visits.  Skilled home care nursing becomes the “eyes” of the 
provider and, more recently, can be supplemented with telemonitoring.  The telemonitoring field is 
rapidly expanding, but studies to date have produced mixed results in reduction of readmissions, 
symptom management, and mortality for patients with HF.4-6 Irrespective of the type of monitoring 
system and whether implantable hemodynamic monitors are employed, outcomes were inconsistent.7;8 A 
recent meta-analysis of over 8000 patients enrolled in various clinical studies found that the majority of 
technology assisted approaches used a home monitoring system rather than an implantable device or 
phone calls with decision support. 8 Remote monitoring was associated with lower number of deaths and 
hospitalizations, with the decrease in events greater in the cohort, non-randomized trials.   In contrast 
Chaudry and colleagues failed to demonstrate improvement in outcomes in a randomized trial of a 
telephone-based interactive response system.4   

4 
 
      Patient adherence to medication intake, dietary restrictions and lifestyle changes is a key component 
of managing HF and reducing unnecessary exacerbations. Delivery of education and assurance of 
understanding of HF care expectations are key factors to adherence.  To date, home telemonitoring 
systems have not always integrated delivery of relevant and credible patient education.  Furthermore, 
telemonitoring systems have not consistently allowed for assessment of health status and symptoms. The 
SPAN-HF trial failed to show any additional improvements to health status by adding an automated home 
monitor to a nurse-driven system.9;10 
     The purpose of this study was to examine short-term (60-day) health-related quality of life and 
rehospitalization after implementation of the Intel-GE Care Innovations™ Guide (formerly the 
Intel® Health Guide) deployed with American Heart Association guideline-based HF protocols for 
assessment of clinical status and symptoms and delivery of relevant patient education to enhance 
home-bound patients’ and caregivers’ understanding of and management of HF.   
METHODS   
     This was a single center, unblinded, non-randomized feasibility study of telemonitoring with 
embedded patient education.  The University Hospitals Home Care Services program is a large 
home care agency in Northeast OH. It was chosen as the site for implementing the study and was 
the source of referrals and enrollment. This nurse-driven program was available to CMS 
recipients who were discharged home and met eligibly criteria for home care services.  The study 
was approved by the Institutional Review Board of the University Hospitals Case Medical 
Center, Cleveland OH.  The trial was registered in www.clinicaltrials.gov  Protocol ID 
#AHA100602.  

5 
 
     All nurses from the home program had been trained in HF by the National Heart Failure Training 
Program (N-HeFT™) (www.NHeFT.org).11  At the study initiation, a refresher course on symptoms, 
signs and medical therapy of HF was administered.  Patients were consented following hospital discharge 
with a HF diagnosis and were home bound, thus they qualified for the home care nursing program. The 
Care Innovations Guide (Guide) was delivered to patient homes with American Heart Association 
(AHA) HF patient education content on many topics embedded into the unit. Based on the patient’s health 
status, AHA-recommended HF protocols were deployed to the Guide for patients to assess key vital 
signs, health questions and provide related educational content on a daily, weekly, or monthly basis for 60 
days. Patients and caregivers were trained in use of the Guide and related peripherals (that included blood 
pressure monitors, weight scales, glucose monitors (for diabetics), and pulse oximeters), response to 
scheduled sessions, and access of educational content and assessing vital signs independent of scheduled 
sessions.  Patients and caregivers could access the health education component and perform additional 
vitals assessments at any time.  
     Patients were included if they had a diagnosis of NYHA Class II-IV heart failure and had been 
hospitalized for an acute decompensation in the previous 30 days and could complete the monitoring 
process alone or with a caregiver. Patients also needed to have a telephone line or broadband 
internet availability to connect to the Guide.  Patients who had a life expectance of < 6 months or 
were living in an extended care facility were not eligible. 
     Utility was defined as days of activity and interaction of the patient with the monitor / days of actual 
monitoring possible.  Adherence was defined as the percent of actual completed sessions from the number 
of scheduled sessions offered.  Re-hospitalization data were acquired directly from patients or caregivers 
and primary care physicians. Health status was assessed by the Kansas City Cardiomyopathy 
Questionnaire (KCCQ) pre and post monitoring periods. 12 Baseline medications were recorded; however, 
medications were adjusted by the patient’s primary care provider as needed during the study period. Post 

6 
 
Guide monitoring, patients and clinicians completed surveys on satisfaction with the use of the 
Guide with the embedded AHA HF protocols and educational content. 
The Intel-GE Care Innovations™ Guide PHS6000 was used in this study (See Figure 1).  It 
allows health care providers to remotely access vital sign measurements of patients at home. The 
Guide collects measurements captured on commercially available wireless or tethered medical 
devices designed for home use, stores and displays the collected information on the LCD screen, 
and transmits the information to a secure host server. Health care providers were able review the 
transmitted information and select education and reminders to send to patients using software 
interface. Patients were also able to review their stored vital sign measurement information and review 
educational and motivational content deployed to the unit separate from their scheduled sessions. 
Analysis:  
     Percentages, means ± SD are presented.  A paired Student’s t-test was used to compare the KCCQ 
score at baseline and 60 days. We compared the change in KCCQ Clinical and Overall scores to 
compliance (completing scheduled sessions) and utility (days with activity per monitored days) using 
ANOVA and generalized estimating equations (GEE).  Medians (distributions) of compliance and utility 
were compared across rehospitalization status using Wilcoxon Rank Sum test. Utility scores were 
calculated using the days of recorded activity compared to the actual days of monitoring, i.e, how well 
and often the patients or caregivers used the system. Rehospitalization rates were determined using 
product-limit survival tables and tested using log-rank test. SAS (SAS Institute, Inc.) version 9.1 was 
used.  

7 
 
RESULTS   
     Twenty six patients were consented and enrolled within a 6-month period. All had been discharged 
home after a hospitalization with a primary diagnosis of decompensated HF.  For 15% of the patients, the 
admission was for new onset HF.  Demographics are shown on Table 1.  Patients were older, and the 
majority were women and had non-ischemic HF.  More than half of patients had HF with preserved 
ejection fraction (HF-PEF) and 80.8% had a history of hypertension.  At baseline, 62% were considered 
New York Heart Association (NYHA) functional class II in the home care nurse’s assessment.  The mean 
left ventricular diastolic diameter (LVIDD) was 4.85 + 1.27 cm and therefore, not dilated.  Although the 
mean blood pressure was 125 mmHg ± 22 mm Hg, the RVSP mean, 52 mm Hg ± 11 mm Hg was 
indicative of pulmonary hypertension. Medications at baseline are noted in Table 1. Most patients were 
on loop diuretics, and only 7 (26.9%) received an aldosterone antagonist.  None of the patients were 
receiving angiotensin receptor blockers (ARB) and only 10 were on angiotensin converting enzyme 
(ACE) inhibitors. Of the 9 patients with EF ≤ 40%, only 6 were prescribed an ACE inhibitor and none 
were prescribed an ARB.  There was no documentation of the reasons for not being on guideline 
recommended vasodilator therapy. Beta blocker therapy was prescribed with similar frequency as diuretic 
therapy. Baseline laboratory values are also depicted in Table 1.  Renal function was relatively well 
preserved; however, the majority of patients were anemic.    
Health-Related Quality of Life 
     The KCCQ scores at baseline and 60 days are shown in Table 2.  KCCQ Clinical Summary score 
significantly improved (p=0.039) and the Overall Summary score trended toward improvement (p=0.077; 
Figure 1).  Patients scored high on the self-efficacy domain (1-item) at baseline and approached a perfect 
standardized score of 100 at 60 days. Utility scores were high, with a mean of 86.4% ±5.61 
(median=88.8).  Mean patient adherence was also high at 73.4% ±31.7 (median=89.4) (Figure 2).   

8 
 
 Hospitalizations 
     Thirteen patients (50%) were rehospitalized within the 60-day follow-up period, four for HF and nine 
for other reasons. Therefore, at 30 days, the all-cause and HF rehospitalization rates were 23% and 15%, 
respectively. Mean days hospitalized at follow-up was 16 ± 5 days. Using generalized estimating 
equations, greater utility but not adherence scores were correlated with improvements in health status by 
KCCQ Clinical Summary score (p=0.013) and Overall Summary score (p=0.0056). Less patient utility 
and adherence were associated with rehospitalization.  Median adherence and utility for those not 
rehospitalized (97.2% and 96.9%, respectively) were greater than for those rehospitalized (67.4% and 
82.2%: p=0.013, p=0.006, respectively; Figure 3). 
 DISCUSSION 
     This pilot study has demonstrated the feasibility of adding AHA Heart Failure guideline 
protocols and educational content within the Care Innovations Guide. Health status, as shown by 
the KCCQ Clinical and Overall Summary Scores improved after hospitalization; however, all-cause 
hospitalization rate was still above 20%, similar to those in the state of Ohio. 1  It is notable that only 6 
out of 10 patients with EF <40% were prescribed ACE inhibitors in spite of adequate blood pressures and 
renal function.  This finding further reinforces the existing gap between Guidelines and clinical care.  
Nurses, in spite of training, could not change medications without a physician’s order.  
     Clinical and overall health status measures were found to improve over the course of the study. 
Further, patients who had greater improvement in health-related quality of life were more likely to utilize 
the Guide monitoring system. In addition, there was a statistically significant association noted between 
utility, adherence, and rate of rehospitalization.  The findings of this study, although based on a small 
number of patients and requiring testing in prospective randomized controlled studies, highlights the 
potential for home monitoring with AHA guideline-based HF protocols and educational content to impact 
HF disease burden, progression and health care expenditures.  

9 
 
     It has become increasingly apparent that better strategies for monitoring HF geared towards identifying 
sub-clinical congestion, enhancing self-care, improving treatment adherence, and addressing comorbid 
conditions would be of value. Instead of being episodic and reactive, care could then become proactive 
through continual home observation and patient and caregiver education and assistance designed to slow 
or prevent further deterioration. Interventions to better monitor the patient with HF at home range from 
increasing self-care and structured telephone support to telemonitoring and remote monitoring of 
implantable devices.  In individual studies and meta-analyses, researchers have suggested that 
telemonitoring in ambulatory HF patients can improve mortality by 17 to 47% during six to twelve 
months of follow-up, with similarly significant reductions in hospitalizations varying from 7 to 48%. 8 
However, two recent multicenter randomized controlled trials failed to demonstrated benefit with 
telemonitoring for HF.  In Telemonitoring to Improve Heart Failure Outcomes (TELE-HF), a telephone-
based interactive voice-response system that obtained symptom and weight information provided no 
significant benefit over usual care in all-cause rehospitalization rates or death. 4 Similarly, Telemedical 
Interventional Monitoring in Heart Failure Study (TIM-HF) did not demonstrate a significant impact of 
remote monitoring by telemedicine on HF related rehospitalization rates or mortality.13 
 
These studies highlight the complexity of home monitoring interventions. TELE-HF relied on 
patient-initiated communication: patients had to use a toll-free telephone system in which an automated 
voice then asked a series of questions to which patients had to respond by keypad. Fourteen percent of 
patients assigned to the telemonitoring arm never used the automated call-in system, and only 55% were 
still regularly using the system by the end of the study period. Loss of adherence in the intervention arm 
highlights the need to make an intervention palatable to patients. Furthermore, nurses in TELE-HF were 
not empowered to change the medication regimen without physician consultation, adding a layer of 
communication or collaboration and delay. Home management of HF ideally involves multiple 
components, of which monitoring is only one.  There needs to be timely transmission of data, receipt of 
the information by the appropriate care team members who can analyze and act upon it, a feedback loop 

10 
 
to the patient and/or caregiver with directions, and sufficient patient and caregiver empowerment to 
understand and implement the instructions. Monitoring alone may not have been sufficient to produce 
desired outcomes. Also, although telemonitoring promises to reduce the need for in-person follow-up, it 
may actually increase the workload involved. In the TELE-HF study, while there were only 25 patients 
per site on average, there were 884 incidents per site requiring responses. Managing the volume of 
information transmitted through a telehealth system increases the need for mid-level personnel with 
adequate HF training, expertise and licensure to provide HF treatment independently of or in 
collaboration with the patient’s physician. Patient adherence to scheduled Guide system sessions in our 
study was high, although the observation time was short.  It is possible that in our study, the addition 
of patient education embedded into the Guide, and accessed during and outside of scheduled 
sessions, encouraged better adherence and improved self management. 
     Patient education is essential in the management of HF and is strongly encouraged in 
Guidelines.  Accurate information and buy-in from patients and their caregivers can often 
prevent decompensation and even hospital admission. 14;15  Although multiple agencies and 
societies have patient education tools and information, responsibility for dissemination of 
education materials is left to the provider.  The provider must guide patients to review materials 
independently or actually provide the education in-person.  Education is traditionally delivered 
via printed material and enhanced when providers review material with patients. Web sites are 
replete with information that may not only be inaccurate, but potentially harmful.  Even when 
accurate, patients may not understand and be able to utilize what they read. Materials for education used 
during a hospitalization may be different than those used in the outpatient setting. Further, in the hospital 
setting, multiple healthcare providers may deliver short bits of information on multiple HF related themes 
that may be inadequate in terms of breadth or depth. In patients who are home-bound, delivery of relevant 
patient education to facilitate disease management is usually managed by a home-care nursing team that 

11 
 
may or may not be adequately trained in delivering HF self-care information. A telehealth system 
embedded with accurate, credible AHA education information on HF themes may be a useful adjunct in 
that the materials are standardized, accurate, have adequate breadth and depth and use both words and 
pictures to provide information.   The value of patient education in optimizing self-management has not 
been consistently assessed; further research is needed.  
Limitations 
Limitations of this study included that, due to available funding, the study was limited to a very small 
patient sample size (25) from a single center enrollment in Northeast Ohio with a short monitoring period 
(60 days). An additional limitation to the outcomes analysis was that the study did not have a control 
group for comparative purposes and was non-randomized.  Finally, the patients and/or caregivers were 
capable of self-selecting to choose to view or ignore the educational content that was provided within the 
protocols. Home care nurses, in spite of training could not alter medications without the express order of 
the treating physician.  It is not known whether medication adjustments by nurses could have decreased 
rehospitalizations. 
Conclusions: This observational study showed the feasibility of adding AHA Heart Failure 
guideline-based protocols and educational content within the Care Innovations Guide. As 
expected, this home-bound population of patients with HF were older and primarily women. In 
spite of nurse training, health care providers did not prescribe ACEI or ARB therapies at 
expected rates, although many patients had HF-PEF. Health-related quality of life, as shown by 
the KCCQ Clinical and Overall Summary Scores improved after hospitalization; however, all-
cause hospitalization rate was still higher than desired.  Clinical and overall health status measures 
improved during the study, and were associated with greater patient utilization of the Guide.  In addition, 
there was a statistically significant association noted between compliance, utility, and rate of 

12 
 
rehospitalization. These preliminary observations need to be confirmed in a larger, randomized clinical 
trial. Future trials should also test the ability of trained, HF mid-level provider nurses (licensed 
independent practitioners) to adjust medications and apply other management decisions based on 
recommended evidence-based national or local guidelines or protocols.   

13 
 
Reference List 
 
 
 
(1)  Fang J, Mensah GA, Croft JB, Keenan NL. Heart failure-related hospitalization in the U.S., 1979 
to 2004. J Am Coll Cardiol. 2008;52:428-34. 
 
(2)  Jencks SF, Williams MV, Coleman EA. Rehospitalizations among patients in the Medicare fee-
for-service program. N Engl J Med. 2009;360:1418-28. 
 
(3)  Baker DW, Brown J, Chan KS, Dracup KA, Keeler EB. A telephone survey to measure 
communication, education, self-management, and health status for patients with heart failure: the 
Improving Chronic Illness Care Evaluation (ICICE). J Card Fail. 2005;11:36-42. 
 
(4)  Chaudhry SI, Mattera JA, Curtis JP, Spertus JA, Herrin J, Lin Z et al. Telemonitoring in patients 
with heart failure. N Engl J Med. 2010;363:2301-9. 
 
(5)  Rich MW, Beckham V, Wittenberg C, Leven CL, Freedland KE, Carney RM. A multidisciplinary 
intervention to prevent the readmission of elderly patients with congestive heart failure. N Engl J 
Med. 1995;333:1190-1195. 
 
(6)  Bero LA, Grilli R, Grimshaw JM, Harvey E, Oxman AD, Thomson MA. Closing the gap between 
research and practice: an overview of systematic reviews of interventions to promote the 
implementation of research findings. The Cochrane Effective Practice and Organization of Care 
Review Group. BMJ. 1998;317:465-68. 
 
(7)  Clark AM, Savard LA, Thompson DR. What is the strength of evidence for heart failure disease-
management programs? J Am Coll Cardiol. 2009;54:397-401. 

14 
 
 
(8)  Klersy C, De Silvestri A, Gabutti G, Regoli F, Auricchio A. A meta-analysis of remote 
monitoring of heart failure patients. J Am Coll Cardiol. 2009;54:1683-94. 
 
(9)  Konstam V, Gregory D, Chen J, Weintraub A, Patel A, Levine D et al. Health-related quality of 
life in a multicenter randomized controlled comparison of telephonic disease management and 
automated home monitoring in patients recently hospitalized with heart failure: SPAN-CHF II 
trial. J Card Fail. 2011;17:151-57. 
 (10)  Weintraub A, Gregory D, Patel AR, Levine D, Venesy D, Perry K et al. A multicenter 
randomized controlled evaluation of automated home monitoring and telephonic disease 
management in patients recently hospitalized for congestive heart failure: the SPAN-CHF II trial. 
J Card Fail. 2010;16:285-92. 
 (11)  Ventura HO, Pina IL. The AHF SCENE II Preceptorship Program: rationale and design of an 
educational program to optimize management of advanced heart failure. Congest Heart Fail. 
2000;6:319-24. 
 (12)  Green CP, Porter CB, Bresnahan DR, Spertus JA. Development and evaluation of the Kansas 
City Cardiomyopathy Questionnaire: a new health status measure for heart failure. J Am Coll 
Cardiol. 2000;35:1245-55. 
 (13)  Koehler F, Winkler S, Schieber M, Sechtem U, Stangl K, Bohm M et al. Telemedical 
Interventional Monitoring in Heart Failure (TIM-HF), a randomized, controlled intervention trial 
investigating the impact of telemedicine on mortality in ambulatory patients with heart failure: 
study design. Eur J Heart Fail. 2010;12:1354-62. 
 
 

15 
 
 (14)  Koelling TM. Multifaceted outpatient support can improve outcomes for people with heart 
failure. Commentary. Evid Based Cardiovasc Med. 2005;9:138-41. 
 (15)  Koelling TM, Johnson ML, Cody RJ, Aaronson KD. Discharge education improves clinical 
outcomes in patients with chronic heart failure. Circulation. 2005;111:179-85. 

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Figure Legends: 
Figure 1:  Key components of the Intel–GE Care Innovations™ Suite 
Figure 2:  KCCQ Scores at baseline and end of study 
Figure 3: Adherence and Utility Scores 
Figure 4:  Relationship of Adherence and Utility with Rehospitalization  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

17 
 
Table 1:  Demographics of the patient population, laboratory and medications at baseline 
Parameter 
Value 
Number of Patients 
26 
Gender (% women) 
61 
Age (mean + SD) 
75 + 10 
Race (% African American) 
39 
BMI   kg/m2 
29.5 + 6.5 
Etiology (% ischemic) 
23 
Ejection Fraction (EF %) 
47 + 16 
EF > 40% (%) 
62 
LVEDD (cm) (mean + SD) 
4.85 + 1.3 
Right Ventricular Systolic Pressure (RVSP mm Hg,  mean + 
SD) 
52 + 11 
NYHA Class II (%) 
62 
NYHA Class III (%) 
29 
Systolic Blood Pressure (mm Hg, mean + SD) 
125 +  22 
Diastolic Blood Pressure (mm Hg, mean + SD) 
69 + 10 
Sodium  mmol /L 
137 +  4 
Potassium mmol /L 
4.2 + 0.6 
BUN  mg/dL 
29 +  18 
Creatinine mg/dL 
1.46 + 0.9 
Hemoglobin g/dL 
11.2  +  2.1 
Albumin g/dL 
3.14 + 0.5 
ACE inhibitor dose n=10 ( mg enalapril equivalents, mean + 
SD) 
25.5 + 15.7 
Beta Blocker, n=23 ( mg metoprolol equivalents, mean + SD) 
89.3 + 51 
Loop diuretic ( mg furosemide equivalents, mean + SD) 
91.4 + 78 
Aldosterone inhibitor (spironolactone equivalents, mean + 
SD) 
23.2  + 4.7 
Angiotensin Receptor Blocker, n=0 
0 
Digoxin, n=4 ( mg, mean + SD) 
0.16 + 0.06 
 
 
 

18 
 
Table 2:   
Kansas City Cardiomyopathy Questionnaire (KCCQ) baseline and 60 days with domains and the overall and clinical summaries. 
 
Physical 
Limitation 
Symptom 
Stability 
Symptom 
Frequency 
Symptom 
Burden 
Total 
Symptom 
Score 
Self-
Efficacy 
Quality 
of Life 
Social 
Limitation 
Overall 
Summary 
Clinical 
Summary 
Baseline 46 + 25 
67 + 30 
51 + 33 
59 + 29 
55 + 29 
79 + 24 
50 + 31 
43+ 36 
49 +25 
51 + 23 
 
 
 
 
 
 
 
 
 
 
 
60 days 
58 + 24 
63 + 31 
71 + 27 
75 + 29 
73 + 27 
92 + 12 
68 + 31 
54 + 44 
63  +26 
65 + 22 
 
 
 
 
 
 
 
 

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Figure 1 
 
 

20 
 
 
Figure 2

21 
 
  
 
 
Figure 3 

22 
 
  
Figure 4 
 
 
 
   p=0.013                        p=0.006