A Multifaceted Adaptive Mobile Application to Promote Self-management and Improve Outcomes in Heart Failure
Phase: PHASE3
Conditions: Heart Failure
Sponsor: University of Michigan

 
 
 
A multifaceted adaptive mobile application to promote 
self-management and improve outcomes in heart 
failure: ManageHF  
National Clinical Trial (NCT) Identified Number: NCT04755816 
Principal Investigator: Michael Dorsch, PharmD, MS 
Funded by: The National Institute on Aging 
Version Number: 3.1 
27 September 2022 
 
 
Summary of Changes from Previous Version: 
 
Affected 
Section(s) 
Summary of Revisions Made 
Rationale 
1.2, 1.3, 5.1, 
5.2 
Update inclusion and exclusion criteria 
Due to lower-than-expected recruitment, 
the inclusion and exclusion criteria have 
been revised to include a broader pool of 
patients with heart failure. The changes 
were approved by the DSMB. 
 
 
 
 
 
 
 
 
 
 
 
 

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Table of Contents 
 
Statement of Compliance 
5 
1 Protocol Summary 
6 
1.1 Synopsis 
6 
1.2 Schema 
8 
1.3 Schedule of Activities (SoA) 
9 
2 Introduction 
10 
2.1 Study Rationale 
10 
2.2 Background 
11 
2.3 Risk/Benefit Assessment 
14 
2.3.1 Known Potential Risks 
14 
2.3.2 Known Potential Benefits 
14 
2.3.3 Assessment of Potential Risks and Benefits 
14 
3 Objectives and Endpoints 
15 
4 Study Design 
16 
4.1 Overall Design 
16 
4.2 Scientific Rationale for Study Design 
17 
4.3 Justification for Dose 
17 
4.4 End of Study Definition 
18 
5 Study Population 
18 
5.1 Inclusion Criteria 
18 
5.2 Exclusion Criteria 
19 
5.3 Screen Failures 
20 
5.4 Strategies for Recruitment and Retention 
20 
6 Study Intervention 
21 
6.1 Study Intervention(s) Administration 
21 
6.1.1 Study Intervention Description 
21 
6.1.2 Administration 
24 
6.2  Acquisition and Accountability 
25 
6.3 Measures to Minimize Bias: Randomization and Blinding 
25 
6.4 Study Intervention Compliance 
25 
6.5 Concomitant Therapy 
25 

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7 Study Intervention Discontinuation and Participant Discontinuation/Withdrawal 
26 
7.1 Discontinuation of Study Intervention 
26 
7.2 Participant Discontinuation/Withdrawal from the Study 
26 
7.3 Lost to Follow-Up 
26 
8 Study Assessments and Procedures 
27 
8.1 Efficacy Assessments 
27 
8.2 Safety and Other Assessments 
28 
8.3 Adverse Events and Serious Adverse Events 
30 
8.3.1 Definition of Adverse Events (AE) 
30 
8.3.2 Definition of Serious Adverse Events (SAE) 
30 
8.3.3 Events of Special Interest 
31 
8.3.4 Classification of an Adverse Event 
31 
8.3.4.1 Severity of Event 
31 
8.3.4.2 Relationship to Study intervention 
31 
8.3.5 Time Period and Frequency for Event Assessment and Follow-Up 
32 
8.3.6 Adverse Event Reporting 
32 
8.3.7 Serious Adverse Event Reporting 
33 
8.3.8 Reporting Events to Participants 
33 
8.3.9 Reporting of Pregnancy 
33 
8.4 Unanticipated Problems 
34 
8.4.1 Definition of Unanticipated Problems (UP) 
34 
8.4.2 Unanticipated Problem Reporting 
34 
8.4.3 Reporting Unanticipated Problems to Participants 
34 
9 Statistical Considerations 
35 
9.1 Sample Size Determination 
35 
9.2 Populations for Analyses 
36 
9.3 Statistical Analyses 
36 
9.3.1 General Approach 
36 
9.3.2 Analyses Of Primary And Secondary Endpoints 
36 
9.3.3 Analyses Of Secondary Endpoints:  Proximal Outcomes 
38 
9.3.4 Prediction Modeling Based On Application Data (Exploratory Analysis) 
38 
9.3.5 Safety Analyses 
39 
9.3.6 Baseline Descriptive Statistics 
39 
9.3.7 Planned Interim Analyses 
39 

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9.3.8 Tabulation of Individual Participant Data 
39 
10 Supporting Documentation and Operational Considerations 
40 
10.1 Regulatory, Ethical, and Study Oversight Considerations 
40 
10.1.1 Informed Consent Process 
40 
10.1.1.1 Consent/assent and Other Informational Documents Provided to participants 40 
10.1.1.2 Consent Procedures and Documentation 
40 
10.1.2 Study Discontinuation and Closure 
40 
10.1.3 Confidentiality and Privacy 
41 
10.1.4 Future Use of Stored Specimens and Data 
42 
10.1.5 Key Roles and Study Governance 
42 
10.1.6 Safety Oversight 
43 
10.1.7 Clinical Monitoring 
43 
10.1.8 Quality Assurance and Quality Control 
44 
10.1.9 Data Handling and Record Keeping 
44 
10.1.9.1 Data Collection and Management Responsibilities 
44 
10.1.9.2 Study Records Retention 
45 
10.1.10 Protocol Deviations 
45 
10.1.11 Publication and Data Sharing Policy 
45 
10.1.12 Conflict of Interest Policy 
46 
10.2 Additional Considerations 
46 
10.3 Abbreviations 
46 
10.4 Protocol Amendment History 
48 
11 References 
53 
References 
53 
12 Appendices 
56 
Appendix A – Patient information sheets 
56 
 

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STATEMENT OF COMPLIANCE 
 
The trial will be carried out in accordance with International Council on Harmonisation Good Clinical 
Practice (ICH GCP) and the following: 
● United States (US) Code of Federal Regulations (CFR) applicable to clinical studies (45 CFR Part 
46, 21 CFR Part 50, 21 CFR Part 56, 21 CFR Part 312, and/or 21 CFR Part 812). 
National Institutes of Health (NIH)-funded investigators and clinical trial site staff who are responsible 
for the conduct, management, or oversight of NIH-funded clinical trials have completed Human Subjects 
Protection and ICH GCP Training. 
 
The protocol, informed consent form(s), recruitment materials, and all participant materials will be 
submitted to the IRB for review and approval. Approval of both the protocol and the consent form(s) 
must be obtained before any participant is consented. Any amendment to the protocol will require 
review and approval by the IRB before the changes are implemented to the study. All changes to the 
consent form(s) will be IRB approved; a determination will be made regarding whether a new consent 
needs to be obtained from participants who provided consent, using a previously approved consent 
form. 
 
I confirm that I have read and understand the protocol referenced above. I agree to carry out the study 
by the criteria written in the protocol and understand that no changes can be made to this protocol 
without written permission from the Protocol Chairs and the IRB.   
 
Institution Name: _______________________________ 
Site Principal Investigator Name (PRINT): _____________________________ 
SITE PRINCIPAL INVESTIGATOR SIGNATURE: _____________________________ DATE:_________________

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1 PROTOCOL SUMMARY 
1.1 SYNOPSIS 
Title: 
A multifaceted adaptive mobile application to promote self-management and 
improve outcomes in heart failure  
Study Description: 
The Manage HF study is a multicenter 12-week randomized controlled 
double-blind 2x2 factorial clinical trial. This study will investigate the 
effectiveness of two contextual just-in-time adaptive interventions (JITAIs) 
delivered via a mobile app for heart failure patients. The clinical worsening 
intervention targets self-management of behaviors to prevent worsening of a 
patient’s heart failure symptoms. The dietary sodium intervention promotes 
lower sodium intake. Eligible participants will be randomized to the dietary 
sodium intervention, the clinical worsening intervention, both interventions, 
or no intervention in a 1:1:1:1 manner, stratified by site, gender, and HF type 
(HFpEF versus HFrEF). 
Objectives: 
Primary Objective: 
Determine the impact of two unique adaptive mobile 
application interventions on death, HF readmissions, 
and health-related quality of life (HRQOL) in HF 
patients. 
Secondary 
Objectives: 
Examine the effect of the two interventions on the 
individual components of the primary composite 
endpoint and relative change in heart failure 
symptoms and establish the effect of each intervention 
on its intermediate outcomes of reduction in dietary 
sodium and clinical worsening events. 
 
Endpoints: 
Primary Endpoint: 
The hierarchical composite of time to death from any 
cause, time to first HF readmission, and change from 
baseline to week 12 in quality of life as measured by 
the Minnesota Living with Heart Failure 
Questionnaire (MLHFQ). 
Secondary Endpoints: Time to all-cause mortality  
Time to first HF readmission 
HF hospitalization within 30 days of discharge 
Days alive and out of hospital over 12 weeks 
Change in MLHFQ over 12 weeks 
Change in estimated sodium intake over 12 weeks 
Percent time in a clinically worse state over 12 weeks 
 
Study Population: 
500 adult heart failure patients 
Phase: 
III 
Description of 
Sites/Facilities Enrolling 
Participants: 
The administrative site and data coordinating center for this clinical trial are 
located at the University of Michigan. Nine clinical sites in the United States 
will recruit and enroll participants for the clinical trial. 

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Description of Study 
Intervention: 
The mobile app includes two interventions that are turned on or off based on 
the randomization assignment for the clinical trial. The clinical worsening 
intervention promotes self-monitoring and self-management with a health 
status indicator that is linked to adaptive, personalized and contextual push 
notifications to promote a behavioral change. The dietary sodium 
intervention facilitates lower sodium choices at home, restaurants and 
grocery stores using tailored and contextual push notifications. 
Study Duration: 
54 months 
Participant Duration: 
12 weeks 
  

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1.2 SCHEMA 
 
 
 
 
 

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1.3 SCHEDULE OF ACTIVITIES (SOA) 
Procedure   
Screening and 
Enrollment  
(admission to 
+14 days from 
discharge) 
 
Baseline  
(day of 
discharge  
+14 days)3  
6 weeks 
 from 
randomization 
+/- 10 days 
12 weeks from 
randomization  
+/- 10 days 
Enrollment Visit (Inpatient) 
SS 
 
 
 
Informed Consent 
SS 
 
  
  
Inclusion/exclusion1 
SS 
 
  
  
Randomization2 
 
CC 
  
  
App training & application-specific 
questionnaires 
SS 
 
 
 
Demographics 
SS 
 
  
  
Medical history 
 
SS 
  
  
Follow Up Call & EHR review 
● Clinical events (death, 
hospitalization, other AEs) 
● Medications 
 
 
SS 
SS 
HRQOL surveys 
Participant 
Participant 
Participant 
Participant 
Nutritional Surveys 
Participant 
 
Participant 
Participant 
Daily self-monitoring (weight, blood 
pressure, activity monitor)  
 
 
Participant-----------------------Participant 
Final Status 
 
 
  
SS/CC 
 Key: EHR = electronic health record, SS = study site, App = mobile application, CC = coordinating center 
1If screening/enrollment and baseline do not occur on the same day, re-confirm participant’s eligibility at baseline. 
2Randomization to occur remotely after participant completes HRQOL and Nutritional Surveys. The New York Heart 
Association (NYHA) questionnaire is not required for randomization. 
3If a participant has been re-hospitalized prior to randomization, re-confirm participant’s eligibility, complete a 
new Health History (Day of Discharge) form in the database with the most recent hospitalization data, and submit 
a Serious Adverse Event report.  

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2 INTRODUCTION 
2.1 STUDY RATIONALE 
Scope of Heart Failure 
By 2030, over 8 million Americans will have heart failure (HF), and HF will account for $69 billion/year in 
medical expenditures.1 Much of this societal cost is related to hospitalizations for worsening HF, which 
also take a terrible toll on individuals. Approximately one-third of patients who survive hospitalization 
for HF die within a year.2 Hospital readmissions are common, as more than one-fifth of patients with HF 
are readmitted within 30 days of initial discharge.3 These recurrent hospital stays not only increase the 
risk of death4, but also markedly worsen health-related quality of life (HRQOL)5, contribute to functional 
decline, and increase the risk for long-term institutionalization.6 Hospitals also suffer the consequences; 
HF is the primary driver for federal 30-day readmission penalties,7 which now exceed $500 billion/year. 
Reducing HF readmissions is thus an essential goal across the healthcare spectrum from patients to 
payers.  
 
Efforts to Reduce Readmissions 
Most U.S. hospitals now have dedicated quality improvement teams to reduce readmissions in patients 
with HF.8 These efforts typically cover four domains: enhanced patient education, increased use of 
evidence-based HF therapies, timely post-discharge follow-up, and improved communication between 
inpatient and outpatient healthcare providers.9 Although based on a strong rationale, these initiatives 
have produced mixed results.10 A recent slight decline in risk-adjusted 30-day readmissions has 
plateaued, and this improvement partially relates to changes in risk coding11 rather than definitive 
improvement in outcomes. Even more concerning, both crude and risk-adjusted 30-day mortality in HF 
have gradually increased over this timeframe.4,12 It is clear that new approaches are needed to improve 
post-discharge outcomes in patients with HF. 
 
Rationale for an Intervention During an Episode of Clinical Worsening 
Research on the etiology of HF admissions has been performed to identify better why patients are 
presenting to the hospital.13–17 In a recent study, 94 patients were asked to complete a questionnaire 
about their HF admission.13 Patient-identified reasons for admission were worsening heart failure (53%), 
dietary nonadherence (16%) and medication issues (3%). Physicians in this study further identified the 
most common cause of a preventable admission, which included medication issues, salt restrictions and 
fluid restrictions. In a similar study of 173 patients readmitted for HF, patients, caregivers, cardiologists 
and HF nurses completed a questionnaire on the causes of the readmission.14 Worsening HF as a sole 
reason for the admission was the most commonly reported factor. In addition to worsening HF, 56% of 
patients, 36% of caregivers and 63% of health care providers indicated comorbidities, nonadherence and 
nonoptimal medications were critical factors in the readmission. Respondents reported that 23-31% of 
the readmissions could be prevented if patients were more adherent, requested help earlier and an 

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adequate medical professional was available. These identified factors are essential to the creation of the 
multifaceted intervention within our mobile application in this proposal. 
 
Rationale for an Intervention to Support Dietary Sodium Restriction 
Dietary nonadherence, generally understood to mean excess sodium consumption, frequently occurs 
before HF decompensation and hospitalization.13–17 As part of the HF syndrome, chronic neurohormonal 
activation and reduced renal perfusion can promote sodium and fluid retention. This may cause 
shortness of breath and other congestive symptoms, which are the most common reason for patients 
with HF to seek emergency care. Current HF guidelines advise dietary sodium restriction of 2,000-3,000 
mg/day or less,18,19 and this guidance is the most common self-care recommendation provided to 
patients with HF.20 Cohort studies suggest that lower sodium intake may be particularly important in 
patients with more severe HF symptoms.21 Yet, in the large U.S. Heart Failure Adherence and Retention 
Trial (HART), the median estimated sodium intake was 3,336 mg/day and only 17% of participants 
reported consuming <2,500 mg/day or less of sodium.22 An opportunity seemingly exists to reduce HF 
readmissions and improve HRQOL by promoting adherence to a low-sodium diet. 
 
This study will determine the effectiveness of two unique just-in-time adaptive interventions (JITAIs) 
within a mobile application that targets the two most common reasons patients are readmitted to the 
hospital, inability to recognize worsening and nonadherence to a low sodium diet. The study’s aims are:  
 
Primary Objectives: Determine the impact of two unique adaptive mobile application interventions on 
death, hospital readmission and HRQOL in HF patients. Hypothesis 1a: Each intervention will reduce 
mortality, HF readmission and improve HRQOL (measured by the Minnesota Living with Heart Failure 
questionnaire (MLHFQ)) compared to control over 12 weeks. Exploratory hypothesis 1b: The two 
interventions will have an additive impact on all-cause mortality, HF readmission and HRQOL. 
 
Secondary Objectives: Establish the effect of the interventions on intermediate outcomes and confirm 
that the proximal outcomes mediate the interventions’ impact on survival, all-cause mortality, HF 
readmission and HRQOL. The intermediate outcomes are time clinically worse for the clinical worsening 
intervention and change in sodium intake for the dietary sodium intervention from baseline to 12 
weeks. Hypothesis: The intermediate outcomes facilitate the effects of their respective intervention and 
clarify how each intervention improves HRQOL and reduces readmission. 
 
Exploratory Objectives: Develop data-driven machine learning models that can predict episodes of 
clinical worsening. Continuously measured active and passive remote monitoring will be performed over 
12 weeks for all patients in the clinical trial. Currently, the clinical worsening intervention is centered on 
a rule-based model to identify when a patient is experiencing a clinical worsening episode. Hypothesis: 
Machine learning models can more accurately predict a clinical worsening episode compared to the 
current rule-based model. 

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2.2 BACKGROUND 
HF is the most common hospital discharge diagnosis among older adults in the United States, affecting 
900,000 patients each year.23 One-fifth of HF patients are readmitted within 30 days of discharge, and 
readmissions are directly linked to poor health-related quality of life (HRQOL).13–17 HF readmissions also 
result in significant, potentially avoidable costs to our already strained healthcare system, since 
hospitalizations account for nearly 70% of annual HF costs.15 The most common causes of HF 
readmission – failure to recognize clinical worsening and nonadherence to dietary sodium restrictions – 
are related to poor HF self-management.13–17 Currently, there are no effective HF self-management 
tools to support older adult HF patients in managing their condition after they transition from the 
hospital back into the community. 
  
Preliminary Data  
Several studies have shown that self-
monitoring can improve HRQOL in HF.24,25 We 
performed a prospective single-center single-
group study to determine the effectiveness of 
our web application designed to promote self-
regulation.26 Participants were instructed on 
how to use the web application and to perform 
self-monitoring daily for 12 weeks. A 
comprehensive physical exam, assessment of 
New York Heart Association (NYHA) class, 
Minnesota Living with Heart Failure 
Questionnaire (MLHFQ), and an evaluation of 
self-management were performed in person at baseline and 12 weeks. Participants (N = 24) consisted of 
older (mean 59 years), predominantly female (63%) adults with NYHA class II or III symptoms. NYHA 
classification (Pre 2.5 ± 0.13 versus Post 2.0 ± 0.13; p = 0.0032) and MLHFQ score (Pre 55.7 ± 4.6 versus 
Post 42.6 ± 5.1; p = 0.0078) improved over 12 weeks of self-monitoring. Numerical improvement was 
also demonstrated in weight (Pre 209 ± 9.6 pounds versus Post 207 ± 9.4 pounds; p = 0.39), number of 
times exercised per week (Pre 1.29 ± 0.5 versus Post 2.5 ± 0.6; p = 0.30), and walk distance (Pre 572 ± 
147 yards versus Post 845 ± 187 yards; p = 0.129).  Jugular venous distention (Pre 8.1 ± 0.6 centimeters 
versus Post 6.7 ± 0.3 centimeters; p = 0.08) and peripheral edema (Pre 29.2% versus Post 16.7%; p = 
0.38) decreased after 12 weeks of self-monitoring via the web application. 
 
Clinical Worsening Intervention 
We developed a mobile application that can effortlessly assist in self-monitoring, ultimately driving self-
management in HF. Version 1 of the application provided patients a health status indicator (HSI) using 
standard stop light color concept (green, yellow, red) and a message explaining the meaning of the HSI. 
A deterministic algorithm, based on a daily survey and the change in patient weight compared to dry 
weight, produces the number for the HSI. See figure 2 for a depiction of the HSI page. We studied this 
intervention in a randomized clinical trial, which was Aim 1 of an R21 funded by the National Institute on 

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Aging. We hypothesized that the HSI would accomplish enhanced self-management and improve 
HRQOL. HF patients at hospital discharge were randomized to the App or usual care (No App) in a 1:1 
fashion and followed for 12 weeks. The MLHFQ was collected at baseline, 6 weeks and 12 weeks and HF 
readmissions were collected over the 12 weeks. Eighty-three patients were enrolled and completed all 
baseline assessments. Baseline characteristics were similar between groups, except HF type. The 
average age is 60.2 and 62 years in the App and No App arms, respectively. Most patients were NYHA 
class III, 58% had ischemic heart disease as the origin of HF, 57% had atrial fibrillation and 35% were 
female. The App group had a reduced MLHFQ at 6 weeks (p=0.039) but not at 12 weeks (p=0.778) 
compared to control. The time to first HF readmission was not statistically different between the two 
groups, but in favor of the App group (App 26.2% vs. No App 19.3%, HR 0.89, 95% CI 0.39-2.02, p=0.781). 
 
Motivational push messages were developed for the clinical worsening intervention to support HF self-
management. In addition to the above study, Aim 2 of our R21 grant developed motivational messages 
to be delivered via the mobile application to improve HF self-management. We performed 3 HF patient 
and 2 HF nurse focus groups. The messages emphasize knowledge about their disease, behaviors that 
lead to success and knowledge that encourages positive behavior. Topics of the messages include: 
avoiding major mistakes with medications after discharge, basics of diuretics, fluid restriction 
information, the relationship between fluid intake, sodium and volume overload, troubleshooting 
changes in weight, and medication information. We created 58 messages to test in the focus groups. 
After the 5 focus groups, we generated a list of 37 messages that HF patients and nurses agreed would 
promote a behavior change through self-management and be effective at reducing HF readmissions. 
 
Dietary Sodium Intervention 
In an R21 grant from the Agency for Healthcare Research and Quality (AHRQ), we have developed a 
mobile application-based intervention to help patients reduce sodium intake in hypertension. The 
dietary sodium intervention delivers just-in-time contextual push notifications using the mobile phone 
sensors and geofencing to promote lower sodium alternatives at home, grocery stores and restaurants. 
A single center, prospective, open-label study evaluated the effectiveness of the dietary sodium 
intervention. Patients > 18 years of age diagnosed with hypertension and on antihypertensive therapy 
for at least 3 months were enrolled. Participants were randomized 1:1, stratified by gender, to receive 
the mobile app or usual dietary advice for 8 weeks. The primary endpoint was the change in 24-hour 
urinary sodium excretion. Secondary outcomes included the change in estimated sodium intake from a 
Block Food Frequency Questionnaire (FFQ), 24-hr dietary recall and blood pressure (BP). 
 
Fifty patients (24 App, 26 No App) were randomized. Baseline demographics were similar between the 
groups. The average age was 57 years and BP 131/83 mmHg. The reduction in 24-hour urinary sodium 
excretion from baseline was greater in the App compared to No App group (App -574±1646 vs. No App -
52±1708 mg, p=0.30). The reduction in FFQ (App -1554±1764 vs. No App -409±929 mg, p=0.008) and 24-
hr dietary recall (App -1537±2692 vs. No App -374±2172 mg, p=0.11) sodium intake from baseline were 
greater in the App compared to No App group. A standard sodium intake screener also demonstrated a 
greater reduction in the App group compared to No App group (App -9.5±8.9 vs. No App -3.9±8.8 points, 

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p=0.036). Systolic BP was reduced from baseline in the App compared to No App group (-7.5 vs. -0.7 
mmHg, p=0.12). 
 
Reducing sodium intake has improved HRQOL and reduced hospitalizations. Our research group recently 
completed the Geriatric OUt-of-hospital Randomized MEal Trial in Heart Failure (GOURMET-HF) pilot 
study.27 GOURMET-HF was the first randomized study to evaluate the feasibility and safety of providing 
home-delivered meals following HF hospitalization. Patients discharged from HF hospitalization at three 
sites (University of Michigan, Ann Arbor Veterans Affairs Health System, and Columbia University) were 
randomized to four weeks of home-delivered, low-sodium, nutritionally robust meals vs. usual care. The 
primary outcome of GOURMET-HF was the between-group change in the Kansas City Cardiomyopathy 
Questionnaire (KCCQ) Score, a measure of HRQOL, from discharge to four weeks post-discharge. Sixty-
six patients were randomized 1:1 at discharge to meals versus usual care (age, 71±8 years; 30% female; 
ejection fraction, 39±18%). The KCCQ Score increased similarly between groups between discharge and 
four weeks post-discharge (meals 46±23 to 59±20 vs. usual care 43±19 to 53±24, p=0.37) but the KCCQ 
Clinical Summary Score (average of two KCCQ domains: symptoms of HF and physical limitations) 
improved to a greater degree in the patients receiving meals (47±22 to 65±19 vs. 45±20 to 55±26, 
p=0.053). Readmissions within 30 days for HF (11% vs. 27%, p=0.06) and total days re-hospitalized 
within that timeframe (17 vs. 55 days, p=0.055) trended lower in patients receiving meals. 
 
2.3 RISK/BENEFIT ASSESSMENT 
2.3.1 KNOWN POTENTIAL RISKS 
The main potential risks of the study are loss of protected health information and the potential of "over 
adherence" to the mobile application. Although the education in the intervention is considered standard 
of care, over adherence to guideline-based educational interventions (e.g. extreme sodium restriction) 
could lead to renal insufficiency and/or hypotension. 
2.3.2 KNOWN POTENTIAL BENEFITS 
The benefits of the research to study participants include gaining information on their own self-
management strategies and how they can improve their disease progression. If proven effective, this 
could potentially benefit others when the mobile application software is fully available to the public. 
Potential benefits to society include improved understanding of the management of heart failure 
patients upon hospital discharge. This could ultimately lead to better follow up care and lower morbidity 
and mortality for patients with heart failure.   
2.3.3 ASSESSMENT OF POTENTIAL RISKS AND BENEFITS 
Study Intervention Risks 
The mobile application-based study interventions are push notifications and educational content during 
a clinical worsening and just-in-time contextual messages to decrease sodium intake that are part of 
standard HF education. The potential risk to participants is over adherence to either intervention. Over 

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adherence could result in restricting sodium or food intake too greatly. The risk is small, but important in 
the clinical trial. A full plan for reducing this small risk is found in the Data Safety and Monitoring Plan. 
  
Risk of Loss of Confidentiality 
Information obtained during assessments is confidential and used solely for research purposes. While 
every effort is made to maintain confidentiality and to protect Patient Health Information (PHI), there 
always exists a small possibility that some information could be compromised. A full plan for reducing 
this small risk is found in the Data Safety and Monitoring Plan. 
  
Benefits 
If the mobile application-based interventions are effective in the treatment of HF, then it could be 
possible the participant treated with the app may receive the benefits of improvement in HF. There are 
only potential benefits to the individual participants in this study. However, direct participation in the 
clinical trial may be of no benefit to an individual participant. 
  
The knowledge gained from this study will allow us to determine the interventions, pieces of our 
interventions and groups of individuals that demonstrate improved outcomes over time. This 
information will be critical to the success of this intervention. The information from this proposal will 
also allow us to build a more tailored mobile application intervention, if needed, for heart failure 
patients which has the ability to be impactful in future studies. 
3 OBJECTIVES AND ENDPOINTS 
 
OBJECTIVES 
ENDPOINTS 
JUSTIFICATIONS 
Primary 
 
Determine the impact of two 
unique adaptive mobile 
application interventions on 
death, hospital readmission and 
HRQOL in HF patients. 
The hierarchical composite 
endpoint of time to death, 
time to HF readmission, and 
change in the Minnesota Living 
with Heart Failure 
Questionnaire (MLHFQ). 
  
The composite endpoint is clinically 
relevant and consistent with the 
published data. Time to death will be 
prioritized over time to hospital 
readmission, which will be 
prioritized over change in MLHFQ. 
MLHFQ is a validated HRQOL survey 
that correlates to many adverse 
outcomes in HF. 
 Secondary 
 
Estimate the effect of the two 
interventions on the individual 
components of the primary 
composite endpoint and relative 
change in heart failure symptoms. 
Time to all-cause mortality  
Time to first HF readmission  
30-day recurrent 
hospitalizations 
Change in MLHFQ over 12 
weeks 
Days alive and out of hospital 
(DAOH) over 12 weeks 
Thirty-day all-cause readmission is a 
quality metric by the Centers for 
Medicare and Medicaid Services. 
DAOH is an emerging outcome in HF 
trials that incorporates both 
morbidity and mortality and 
captures disease burden. 

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Change in NYHA classification 
over 12 weeks 
Establish the effect of each 
intervention on its proximal 
outcome and the mediation 
properties of the proximal 
outcomes on the individual 
components of the composite 
endpoint. 
Change in estimated sodium 
intake over 12 weeks 
Percent time in a clinically 
worse state over 12 weeks 
Composite primary outcome 
 
Estimated sodium intake will be used 
to establish the dietary sodium 
intervention efficacy. 
Percent time in a clinically worse 
state will be used to establish the 
clinical worsening intervention 
efficacy. 
Tertiary/Exploratory 
 
Determine whether there is an 
interaction effect between the 
two interventions. 
 
The hierarchical composite 
endpoint of death, HF 
readmission, and change in the 
Minnesota Living with Heart 
Failure Questionnaire 
(MLHFQ). 
The composite endpoint is clinically 
relevant and consistent with the 
published data.  Death will be 
prioritized over hospital 
readmission, which will be 
prioritized over change in MLHFQ. 
Identify differences in associations 
based on race or sex. 
All primary and secondary 
endpoints. 
As health behaviors may vary by race 
and sex, differences between these 
groups should be explored. 
Develop data-driven machine 
learning models that can predict 
episodes of clinical worsening. 
Clinical worsening as defined 
by the mobile app 
A machine learning model from the 
physical activity and heart rate 
monitor, scale, and blood pressure 
cuff could identify clinical worsening 
more accurately than our rule-based 
model. 
 
4 STUDY DESIGN 
4.1 OVERALL DESIGN 
This phase III trial will determine the effectiveness of two interventions within a mobile application and 
builds on the research team’s previous work. The two mobile interventions are the clinical worsening 
intervention and the sodium intake intervention. Our central hypothesis is that a patient-centered 
mobile application with contextual just-in-time adaptive interventions (JITAIs) about self-management 
during a clinical worsening and dietary sodium will improve the health status of HF patients.  
 
This study is a 12-week prospective randomized controlled double-blind 2x2 trial. See section 1.2 for an 
overview of the schema. The 2x2 factorial arms of the study are: 1) Both the sodium intervention and 
the clinical worsening intervention, 2) the sodium intervention only, 3) the clinical worsening 
intervention only, and 4) no intervention. Eligible participants will be randomized to the dietary sodium 
intervention, the clinical worsening intervention, both interventions, or no intervention in a 1:1:1:1 
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prepare the randomization schedule, using computer-generated block randomization with the random 
block size(s) known only by the DCC. See Section 9.3.2 for more stratification details.  
 
This multicenter clinical trial will be managed by the University of Michigan through the clinical 
coordinating center(CCC) and the data coordinating center. The CCC will be led by chief principal 
investigator, Michael Dorsch, and the data coordinating center will be led by the Statistical Analysis of 
Biomedical and Educational Research (SABER) unit. Nine sites, including the lead site, have been 
selected because of their extensive experience either in the NHLBI Heart Failure Research Network or 
completion of several randomized clinical trials at the site.  
4.2 SCIENTIFIC RATIONALE FOR STUDY DESIGN 
Factorial Design 
Two of the most common clinical problems that lead to a HF hospitalization are lack of recognizing 
worsening HF and dietary sodium nonadherence. Over the past four years, the research team has 
developed interventions for each of these clinical problems. As our preliminary data suggests, each 
intervention may be effective, but larger studies are needed to confirm their efficacy. Although dietary 
sodium interventions have been studied in HF, this specific dietary sodium intervention has not been 
studied in HF. These facts have led us to the proposed 2x2 factorial design of this clinical trial. A factorial 
design allows comparing the interventions main effects, additive effects and mediators in a more 
efficient manner without requiring large numbers of participants in the study. This is different from a 
standard randomized clinical trial that compares the interventions to each other and allows us to 
determine what interventions should ultimately be included in a next generation mobile application.  
 
Control Group 
Once enrolled, all participants receive the mobile application (which includes the two interventions), a 
physical activity monitor with heart rate sensing capabilities, a blood pressure monitoring device, and a 
scale. Each participant will then be randomized to one of 4 treatment groups: 1) the app with neither 
intervention activated, 2) the app with dietary intervention and clinical worsening intervention 
activated, 3) the app with clinical worsening intervention activated and the dietary intervention not 
activated, and 4) the app with dietary intervention activated and the clinical worsening app not 
activated.  All patients will receive the health monitoring devices and perform the daily questionnaire. 
This is done to assure that the interventions are the reasons for any outcome differences, rather than 
the questionnaire and health monitoring devices. Some studies have shown that remote monitoring 
may not effect outcomes28, but we aimed to remove all question in the design of the control group. 
 
4.3 JUSTIFICATION FOR DOSE 
The “doses” or intensity of the interventions in this study have been investigated in preliminary work in 
focus groups, surveys, and clinical trials. In general, patients felt that the number of push notifications 
was appropriate for the dietary sodium intervention, so we based the max number of push notifications 

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per day for both interventions off that premise. When a participant is randomized to both interventions, 
the user can receive several messages throughout the day, overburdening the participant and causing 
user fatigue. In order to reduce message burden, we maximize the number of messages a user can 
receive in one day for both interventions. 
HF patients are at greatest risk for hospital readmission and death for 7-weeks post-discharge and then 
the risk plateaus.25 To account for the increased risk for 7 weeks post-hospitalization, participants will be 
followed for 12 weeks to capture data both during the highest risk phase and as patients enter a lower 
risk period. 
4.4 END OF STUDY DEFINITION 
A participant is considered to have completed the study if he or she has completed all phases of the 
study including the last scheduled event shown in the Schedule of Activities (SoA), Section 1.3 
  
In our examination of each intervention, we have a single primary endpoint and are not conducting 
interim analyses to stop for benefit or futility. 
5 STUDY POPULATION 
5.1 INCLUSION CRITERIA 
All eligibility criteria must be met in order to participate in this study:   
1. Age 18 years and older at screening  
2. Currently admitted or discharged from the hospital within the last 14 days with a diagnosis of 
acute or acute on chronic decompensated HF. 
3. Based on one of the EF criteria (LVEF within 12 months of randomization. BNP or NT-proBNP 
criteria within 30 days prior to randomization): 
• 
Left ventricular ejection fraction (LVEF) ≤ 40%.   
• 
LVEF >40% and BNP > 175 pg/ml or NT-proBNP > 700 pg/ml. Thresholds for NT-proBNP 
and BNP for LVEF > 40% will be corrected for body mass index (BMI) using a 4% 
reduction per BMI unit over 25 kg/m2.*  
4. Have a personal physician for follow-up 
5. A smartphone with a compatible Apple or Android operating system installed and able to 
download and use ManageHF including accepting all permissions 
6. A valid email address 
7. Fluent in spoken and written English  

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8. Signed written informed consent. (Note that each participant must be able to consent for 
themselves.) 
 
 
*BNP threshold for eligibility 
 
 
BNP 
 
 
NT-
ProBNP 
BMI 
 
LVEF >40 
 
 
LVEF >40 
25 
 
175 
 
 
700 
26 
 
168 
 
 
672 
27 
 
161 
 
 
644 
28 
 
154 
 
 
616 
29 
 
147 
 
 
588 
30 
 
140 
 
 
560 
31 
 
133 
 
 
532 
32 
 
126 
 
 
504 
33 
 
119 
 
 
476 
34 
 
112 
 
 
448 
35 
 
105 
 
 
420 
36 
 
98 
 
 
392 
37 
 
91 
 
 
364 
38 
 
84 
 
 
336 
39 
 
77 
 
 
308 
40 
 
70 
 
 
280 
41 
 
63 
 
 
252 
42 
 
56 
 
 
224 
43 
 
49 
 
 
196 
44 
 
42 
 
 
168 
45 
 
35 
 
 
140 
46 
 
28 
 
 
112 
47 
 
21 
 
 
84 
48 
 
14 
 
 
56 
49 
 
7 
 
 
28 
 
5.2 EXCLUSION CRITERIA 
An individual who meets any of the following criteria will be excluded from participation in this study: 
 
1. Contraindication to recommending a sodium restriction diet 
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3. Cardiac resynchronization therapy (CRT) within 3 months prior to screening or current plan to 
implant CRT device during the study period. 
4. Dialysis  
5. Previous cardiac transplantation or implantation of a ventricular assistance device or similar 
device. 
6. Listed status 1, 2 or 3 for heart transplant 
7.  Implantation of a ventricular assistance device is expected within 3 months after randomization  
8. Non-cardiac illness with expected survival of less than 3 months  
9. Discharge to a setting other than home 
10. Requirement for chronic inotropic therapy (e.g. milrinone, dobutamine) 
11. Inability to use Withings devices due to equipment limitations or contraindications 
12. Currently pregnant or intend to become pregnant during the study period. 
5.3 SCREEN FAILURES 
Screen failures are defined as participants who consent to participate in the clinical trial but are not 
subsequently randomly assigned to the study intervention or entered in the study. A minimal set of 
screen failure information is required to ensure transparent reporting of screen failure participants, to 
meet the Consolidated Standards of Reporting Trials (CONSORT) publishing requirements and to 
respond to queries from regulatory authorities. Minimal information includes demographics, screen 
failure details, eligibility criteria, and any serious adverse event (SAE). 
Participants whose sodium intake is less than 1,500 mg per day as measured by the Block Sodium 
Screener will be considered screen fails. 
If a participant is randomized during a re-hospitalization they will be considered a screen failure.  
  
Individuals who do not meet the criteria for participation in this trial (screen failure) may be re-screened 
if they are readmitted at a later point in time.  
5.4 STRATEGIES FOR RECRUITMENT AND RETENTION 
Potential participants will be identified from current HF admissions at the enrolling site. During the 
enrollment period an online dashboard of participants enrolled in the clinical trial will be available to the 
CCC. This dashboard will demonstrate all milestones that need to be met by each study participant and 
compare local retention with de-identified overall metrics from the other sites. This information will be 
reviewed at the meetings with each site to identify retention successes/concerns and determine 
strategies to improve retention. Successful site retention strategies will be shared with all sites through 
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to determine solutions for low retention. In addition, the study closeout payment to each site will be 
linked to the completion of all patient data entered in the dashboard. 
 
Study participants will also be targeted to improve retention. Study site staff will stress the importance 
of adherence during the informed consent interview and throughout the study. After initial enrollment, 
participants receive a welcome email with baseline assessments. Outcomes from the clinical trial are 
completed remotely and do not require the participants to travel to a study site after study initiation. 
Online assessments are sent via email and text message. Reminder emails and text messages are sent 
from the system if participants do not complete them. As the study enrolls, we will continuously review 
feedback to determine if there are other participant-specific items to implement that can improve 
retention.  
 
To improve recruitment and retention, participants will receive up to $200 for participating in the study. 
Participants will receive $50 for completing the enrollment visit, $50 for completing all Week 6 study 
activities, and $100 for completing all Week 12 study activities. Participants will be paid at the end of 
their participation in the research study. Additionally, participants keep the study devices (blood 
pressure monitor, scale, and smartwatch) at the end of their participation in the study.  
 
6 STUDY INTERVENTION 
6.1 STUDY INTERVENTION(S) ADMINISTRATION 
6.1.1 STUDY INTERVENTION DESCRIPTION 
The mobile application, developed at the University of Michigan, includes two JITAIs that are turned on 
or off based on the randomization assignment for the clinical trial. The clinical worsening intervention 
promotes self-monitoring and self-management with a health status indicator that is linked to adaptive, 
personalized and contextual push notifications to promote a behavioral change (see figure 2). The 
dietary sodium intervention facilitates lower sodium choices at home, restaurants, and grocery stores 
using tailored and contextual push notifications.  
 
Both JITAIs use NumberEight, an internet-based service, that use sensors (Wi-Fi, Bluetooth, 
accelerometer, gyroscope, magnetometer, GPS) on the participant’s device to predict their location. 
User’s identifying information is anonymized in NumberEight. The mobile sensor data and NumberEight 
profiles are not attached to the personalized identifiers (e.g. phone number, email). Data are stored as 
long as the user is using NumberEight. Study staff will not have access to participants’ location during 
the study period. 
  
Clinical worsening intervention: The intervention adapts to the participant's reported symptoms and 
provides feedback with a global health status indicator (HSI). The mobile application includes 8 
questions which are completed by all (see table 1). After the questions are answered, participants 

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randomized to the clinical worsening intervention arm will be shown the HSI screen. Access to the HSI 
screen is restricted to participants in the clinical worsening intervention arms. The HSI screen presents a 
graphic (figure 2). The HIS graphic is a speedometer-like pictograph that goes from green (good health 
status) to yellow (fair health status) to red (poor health status). The movement from green to yellow to 
red is based on the answers to each daily questionnaire. The health status indicator includes text 
explaining the green, yellow or red status and what they can do for self-management. Additionally, 
users will receive two push notifications per day in the yellow and three push notifications per day in the 
red until they are back in the green. The notifications will link to in-app educational content, if 
appropriate for the notification.          
 
 
 
Personalization: We have developed a baseline survey, adapted from the Self-Care in Heart Failure Index 
(SCHFI) questionnaire parts B, C and D. The survey includes 2 questions: 1. Listed below are behaviors 
that people with heart failure use to control their symptoms. When you have symptoms, how likely do 
these behaviors help you feel better? (5-point scale); 2. In general, how confident are you that you can: 
(list behaviors and 5-point scale). The questions will include behaviors that are linked to message 
categories from patient and nurse focus groups (weight management, fluid restriction, symptom 
recognition, and medications). Messages are prioritized in the categories that have previously helped 
them feel better. Questions are used to frame the message to be congruent with the user’s confidence. 
A user that is less confident performing a behavior will receive a more motivational message than 
someone very confident. Also, we use the participant’s name, emojis and time of day to provide 
messages that engage participants. The clinical worsening intervention selects three times a day to send 
a message (when a user wakes, 6 hours after a user wakes and before a user goes to bed). These times 
are different every day and predicted by NumberEight. Messages at bedtime will be used for reflection 
on the behavior for the current day and planning for the following day. 
 

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Dietary Sodium intervention: The dietary intervention provides just-in-time contextual information 
using NumberEight’s location services to determine when a participant is at home, arrives at a grocery 
store or arrives at a restaurant. NumberEight uses artificial intelligence algorithms that analyze the 
changes in mobile phone sensors, including Wi-Fi, Bluetooth, accelerometer, gyroscope, magnetometer, 
and GPS. The artificial intelligence algorithm understands the user’s pattern of phone sensor use, 
recognizes his or her present context and predicts future activity. For example, when a user gets in their 
car in the morning and drives to work, they exit their home Wi-Fi network and connect to their car 
Bluetooth. Patterns like this happen continuously and are analyzed in the background. NumberEight 
does not collect any identifiers on the users, other than a unique identifier that links to the user in the 
App. These predictions, generated by NumberEight, then alert the mobile application that the user is at 
home, a grocery store or restaurant. 
  
Nutritionix is a company that aggregates nutrition data for over 690,000 grocery store items and 
149,000 restaurant menu items of over 790 national chains. It also provides the Universal Product Code 
(UPC) for the grocery items to enable the scanning of products with labels and the ability to receive 
standard nutritional facts for common foods without a label. The Nutritionix data is used to gain access 
to the most up-to-date food information at the time the user is interacting with the app. The essential 
advantage of using Nutritionix is the ability to tailor what data elements are presented and show items 
based on sodium content. 
  
Once the app knows the user’s context from NumberEight, the user receives a tailored message based 
on the context (home, grocery store or restaurant). Tapping on a push notification at a grocery store 
takes the user to a page where they can scan UPC on food packaging or text search at the grocery store. 
As the participant scans the food item, the UPC will be linked to the nutritional facts for the product. 
Tapping on a push notification at a restaurant will take the user to a page with dietary information about 
that specific restaurant based on GPS location. The user can also find the nutritional information in the 
app at any time, regardless of context or location. This allows participants to also check foods in their 
homes and receive feedback. The mobile app provides feedback on the sodium content of the food 
using a traffic light signal red, yellow and green to show participants, at a glance, whether a product is 
high, medium or low in sodium. 
  
Personalization: Confidence in following a low sodium diet and a sodium intake screener, two simple 
baseline surveys, personalize the intervention. At baseline, all participants will complete a short survey 
to identify their top sodium-containing foods and will select lower sodium alternatives to their top 
sodium-containing foods, and tag locations where they eat those foods. The responses from the survey 
and lower sodium alternative foods will be used to program the dietary sodium intervention. The 
confidence in following a low sodium diet questionnaire is used to determine the user’s confidence.29 
The result of this survey alters the framing push notification to align with their feelings. The sodium 
intake screener asks how often and the quantity of the most common high sodium foods 
(NutritionQuest, LLC). After completion, there is a summary score of sodium intake. The app asks the 
participant to define 3 alternative lower sodium foods and the location they eat for each of the top 5 

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sodium-containing foods from this survey. These alternatives and locations are used as reminders in the 
push notifications and app about lower sodium foods that the participant committed to eating. 
6.1.2 ADMINISTRATION 
Study teams at the sites will be responsible for identifying eligible participants using the study’s inclusion 
and exclusion criteria (see section 5 for more details). Study teams will approach potential participants 
and obtain consent prior to enrolling a participant. After enrollment, participants will complete the 
enrollment activities outlined in the SoA including all baseline questionnaires and surveys, creating 
accounts with Withings and ManageHF, and downloading the app. 
 
Study coordinators will also conduct a chart review at baseline to gather demographics, medical history, 
vitals including weight, clinical labs, HF diagnosis, and hospitalizations. As applicable, coordinators will 
also record adverse events of special interest (AESI), protocol deviations, and concomitant medications 
at baseline. Please see section 8.3 for more information about adverse event reporting. In addition to 
baseline data, coordinators will collect hospitalizations, AESI, serious adverse events, concomitant 
medications, and protocol deviations at 6 weeks and 12 weeks.  
 
After the baseline MLHFQ is completed, the coordinating center will randomize enrolled participants per 
the study manual of procedures (MOP). Each participant will be randomized to each of the interventions 
in the trial (clinical worsening and dietary interventions). The participant, clinician, and investigators will 
be blinded to the intervention assignment.  All enrolled participants will perform daily self-
monitoring. Participants answer a short 8 question survey assessing their HF symptoms every day within 
the mobile application (table 1). Participants also perform self-monitoring by continuously wearing an 
activity monitor with heart rate monitor, taking blood pressure measurements, and performing a weigh-
in using the study provided equipment.   
  
When a participant is randomized to both interventions, the user can receive several messages 
throughout the day, overburdening the participant and causing user fatigue. In order to reduce message 
burden, we maximize the number of messages a user can receive in one day to three messages for both 
interventions. We also authenticate that both interventions are presented. For example, if a user 
receives a morning clinical worsening intervention message and receives two dietary sodium 
intervention messages, they will not receive another message. The following day, the app prioritizes the 
clinical worsening intervention to present at least two messages because of the previous day. 
Ultimately, this averages both interventions to deliver 1.5 messages per day over a week. 
6.2  ACQUISITION AND ACCOUNTABILITY 
The device supplier, Withings, will ship the physical activity monitors, Bluetooth blood pressure 
monitors and Bluetooth scales directly to the participants’ home addresses. Devices will be retained by 
the participants after their participation is over; as such, no accounting is required for returning devices 
to the study team. 

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6.3 MEASURES TO MINIMIZE BIAS: RANDOMIZATION AND BLINDING 
Participants will be randomized after all screening assessments have been completed and the 
investigator has verified that eligibility criteria have been met. At the time of randomization, participants 
will be assigned a unique randomization number. Eligible participants will be randomized to the dietary 
sodium intervention, the clinical worsening intervention, both interventions, or standard care in a 
1:1:1:1 manner, stratified by site, gender, and HF type (HFpEF versus HFrEF). The DCC unblinded 
statistician will prepare the randomization schedule, using computer-generated permuted block 
randomization with the random block size(s) known only by the DCC. The randomization schedule will 
be provided to software developers who are building the mobile apps. Participants who withdraw from 
the study prior to completion of the treatment period will not be replaced. 
  
This study will be double-blinded, with participants, investigators, and study team masked to study 
assignments. Due to the interventions using push notifications, users will likely be able to guess which 
intervention group they are in over time. That is the nature of this type of research. Implications of this 
are unknown given the objective nature of our primary composite endpoint. Some users could report 
better HRQOL because they are receiving more push notifications. At the week 12 visit, participants will 
be asked to complete a short exit questionnaire via Redcap asking them to guess their treatment group. 
 
6.4 STUDY INTERVENTION COMPLIANCE 
After device set up, participants’ use of the mobile app will be tracked within the app, but study staff 
will not intervene for lack of interaction with the mobile app. Use of the blood pressure monitor, scale, 
and watch will also not be monitored by the sites and the study team will not intervene for lack of use.  
 
6.5 CONCOMITANT THERAPY 
Practitioners will treat participants using their own clinical judgment. Chronic inotropic 
therapy is not allowed. 
7 STUDY INTERVENTION DISCONTINUATION AND PARTICIPANT DISCONTINUATION/WITHDRAWAL 
7.1 DISCONTINUATION OF STUDY INTERVENTION 
Discontinuation of the mobile intervention does not mean discontinuation from the study, and 
remaining study procedures should be completed as indicated by the study protocol. If a clinically 
significant finding is identified (including, but not limited to changes from baseline) after enrollment, the 
investigator or qualified designee will determine if any change in participant management is needed.  
  

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7.2 PARTICIPANT DISCONTINUATION/WITHDRAWAL FROM THE STUDY 
Participants are free to withdraw from the study at any time. Data collected prior to the withdrawal may 
be used for analysis and publications. The study site will instruct the participant to delete the study app 
from their phone and notify the UM project manager via email within 3 business days. Upon participant 
discontinuation, the study site is also responsible for asking permission to continue to follow the 
participant’s EHR in order to obtain study endpoints. The participant’s decision to allow EHR access after 
active study participation will be documented in REDCap on the Final Status eCRF. 
 
An investigator may discontinue or withdraw a participant from the study for the following reasons: 
● 
If any clinical adverse event (AE), laboratory abnormality, or other medical condition or situation 
occurs such that continued participation in the study would not be in the best interest of the 
participant 
● 
Disease progression which requires discontinuation of the study intervention 
The reason for participant discontinuation or withdrawal from the study will be recorded on the Final 
Status CRF.  
 
Participants who sign the informed consent form, and are randomized and receive the study 
intervention, and subsequently withdraw, or are withdrawn or discontinued from the study, will not be 
replaced. 
7.3 LOST TO FOLLOW-UP 
A participant will be considered lost to follow-up if he or she does not complete surveys at week 6 and 
12 and is unable to be contacted by the study site staff. 
  
The following actions must be taken if a participant fails to complete the online 6-week and/or 12-week 
follow-up surveys: 
● 
The site will attempt to contact the participant and counsel the participant on the importance of 
completing the daily interventions and ascertain if the participant wishes to and/or should 
continue in the study. 
● 
Before a participant is deemed lost to follow-up, the investigator or designee will make every 
effort to regain contact with the participant (where possible, 3 telephone calls and, if necessary, 
a certified letter to the participant’s last known mailing address or local equivalent methods). 
These contact attempts should be documented in the participant’s study file. 
● 
Should the participant continue to be unreachable at week 12, he or she will be considered to 
have withdrawn from the study with a primary reason of lost to follow-up. 
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8 STUDY ASSESSMENTS AND PROCEDURES 
8.1 EFFICACY ASSESSMENTS 
Primary Outcome 
The primary outcome is a hierarchical composite of time to all-cause death, time to first HF readmission, 
and change from baseline to week 12 in MLHFQ using the win ratio.  
 
Death (from any cause) occurring during the study period will be reported by each site.  
 
Readmission is defined as admission to an inpatient unit or stay in an emergency department following 
discharge after the index hospitalization that results in at least a 24-hour stay.30 Only admissions 
associated with events that occur on an emergency or unplanned basis will be considered as potential 
endpoints and then adjudicated. A HF readmission must have clinical manifestation of new dyspnea, 
orthopnea, paroxysmal nocturnal dyspnea, edema, pulmonary basilar rales/crackles, jugular venous 
distension, renal hypoperfusion with no other apparent cause or radiological evidence of acute HF and 
additional increased treatment with either intravenous HF medications (diuretics, inotropes, 
vasodilators) or mechanical or surgical intervention specifically directed at the treatment of HF. Only 
readmissions during the study period will be assessed. 
 
The MLHFQ tool consists of 21 questions regarding patients' perception of the effects of HF on their 
daily lives.29 The questions produce a total score of 0 to 105, with a higher score indicating poorer 
HRQOL.  The MLHFQ will be collected at baseline, 6 and 12 weeks. A score change of 5 or more is 
considered a clinically significant difference for the hierarchical composite endpoint. 
 
Secondary outcomes 
The individual components of the composite primary endpoint will be assessed and defined as above:  -- 
time to all-cause mortality, time to first HF readmission, change from baseline to week 12 in MLHFQ.  
Self-reported New York Heart Association Classification using a simple 1 question questionnaire will be 
used as a secondary endpoint at baseline, 6 and 12 weeks.31 Evidence demonstrates that this simple 
questionnaire is a predictor of HF admissions, HRQOL and death.  
 
All-cause 30-day hospitalization will be recorded as a dichotomous variable.  In addition, percent of days 
alive and out of hospital will be measured from baseline to week 12. 
 
Nutritional questionnaires will be used to assess the participants nutritional status and sodium intake. 
The Food Frequency Questionnaire (FFQ) collected at baseline, 6 and 12 weeks will measure sodium 
intake. The 110-item Block FFQ (NutritionQuest, LLC) will be electronically self-administered or via paper 
depending on participant preference. The FFQ records commonly consumed food to estimate nutrient 
and energy intake. Estimated daily intake of sodium will be the main outcome from the FFQ.  
 

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Percent time in a clinically worse state (time in yellow/red) over 12 weeks in combination will also be 
collected. See intervention section 6.1.1 for more detail on yellow and red status for the HSI. 
 
Tertiary outcomes 
The Self Mini Nutritional Assessment (MNA) is a six-question validated nutrition assessment tool that 
can identify geriatric patients who are malnourished or at risk of malnutrition.32,33 The MNA will be 
collected at baseline and 12 weeks. 
8.2 SAFETY AND OTHER ASSESSMENTS 
Participants will not undergo any procedures. The following information will be captured at 
screening/baseline:  
● Mini-Mental State Exam (MMSE)  – administered by study staff 
● Medical chart review for eligibility, medical history and demographics - This must include an 
echocardiogram previously performed for clinical purposes.  
● Vital Signs- including blood pressure, heart rate, respiratory rate, SpO2. Use values closest to 
discharge 
● Laboratory tests- serum sodium, serum potassium, blood urea nitrogen, brain natriuretic 
peptide (BNP), N-terminal-pro hormone BNP, and serum creatinine performed locally as part of 
standard of care. Use values reported closest to discharge. 
● Hospital Anxiety and Depression Scale -- self-administered via study website 
● Baseline questionnaires for mobile app settings - The participant will complete these web-based 
questionnaires at the time of mobile app set-up. 
○ 
Block Sodium Screener (screening assessment) 
○ 
Adapted SCHFI Questions 
○ 
Self-Care Confidence in Low Sodium Diet questionnaire  
● HRQOL Surveys - Participant will complete these web-based questionnaires 
● Nutritional Surveys - Participant will complete these web-based questionnaires 
The following procedures will be performed daily by participants during Intervention period: 
● Daily self-weigh-in - Using study provided scale. Weight will be recorded in app via Bluetooth 
● Self-administered survey - 8 questions will be answered each day within the app. 
● Daily activity monitoring - The participant will wear a heart rate and activity monitor provided by 
the study. 
● Blood Pressure measurement - The participant will take daily blood pressure measurements 
using the study provided blood pressure cuff. Measurement will be uploaded to the app via 
Bluetooth.    
 

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While in the hospital, participants will be instructed on how to use the devices and be informed that 
their readings will not be monitored. The blood pressure monitor does provide easy-to-read color-coded 
feedback based on recommendations from the American Heart Association; however, it is the 
participant’s responsibility to contact their doctors or seek medical attention for high readings. 
The following procedures will be performed at 6 weeks and 12 weeks: 
● Follow-up phone call - Study staff will contact the participant to capture clinical events, vital 
status, medication changes and AESI.  
● HRQOL Surveys - Participant will complete these web-based questionnaires 
● Nutritional Surveys - Participant will complete these web-based questionnaires 
Study coordinators are responsible for monitoring the completion of the surveys. Remote participant 
follow-up will be performed by the study coordinator to ensure timely completion of the surveys and to 
gather information hospitalizations at outside institutions, AESI, and other data that may not be 
available in the electronic health records.  Please see the table below for an estimation of time 
commitment needed by each participant in this study. Note: this does not include the daily requirement 
of weighing in, checking vitals and taking a short (8 question) survey on the app. 
 
Study Assessment 
Screening/ 
Baseline 
Visit 
6-Week 
Visit 
12-Week 
Visit 
MMSE (Approximately 10 minutes) 
✔  
 
 
SCHFI (Approximately 5 minutes) 
✔  
 
 
High 5 alternatives (Approximately 10 minutes) 
✔  
 
 
HADS (Approximately 5 minutes) 
✔  
 
 
FFQ (Approximately 45 minutes) 
✔  
✔  
✔  
Self-MNA (Approximately 5 minutes) 
✔  
 
✔  
NYHA (Less than 2 minutes) 
✔  
✔  
✔  
MLHFQ (Less than 10 minutes) 
✔  
✔  
✔  
Block Sodium Screener (Approximately 5 minutes) 
✔  
✔  
✔  
Follow-up Phone Call (Approximately 15 minutes) 
 
✔  
✔  
App Summary Survey (Approximately 5 minutes) 
 
 
✔  
Approximate time to complete all activities 
92 minutes 
77 minutes 87 minutes 
The main safety objectives in ManageHF are to characterize the risk profiles of the two management 
strategies and to monitor for unanticipated risks to study participants. In this study, all medications 
prescribed as a part of standard of care for the management of HF have well defined safety profiles. For 
this trial, reporting is primarily governed by the Common Rule (45 CFR Part 46, Subpart A), 
Investigational Device Exemptions (Part 812), as well as ICH Guidelines, IRBs and local regulations. 
The investigator is responsible for monitoring the safety of subjects enrolled into the study at the study 
site. The investigator or qualified designee will enter the required initial and follow-up information 
regarding events into the appropriate module of the eCRF within data capture system. Investigators are 

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to report serious adverse events in accordance with their local IRB requirements. Investigators should 
follow usual clinical practices at their institution for reporting to regulatory authorities serious, 
unexpected events related to standard of care medications and devices.  
 
Research staff may review participants’ medical records for up to 5 years after their participation to 
study long-term health outcomes. 
8.3 ADVERSE EVENTS AND SERIOUS ADVERSE EVENTS 
8.3.1 DEFINITION OF ADVERSE EVENTS (AE) 
An adverse event (AE) is any untoward or unfavorable medical occurrence associated with the subject’s 
participation in the research, whether or not considered related to the subject’s participation in the 
research (modified from the definition of adverse events in the 1996 International Conference on 
Harmonization E-6 Guidelines for Good Clinical Practice) (from OHRP "Guidance on Reviewing and 
Reporting Unanticipated Problems Involving Risks to Subjects or Others and Adverse Events 
(1/15/07)"http://www.hhs.gov/ohrp/policy/advevntguid.html#Q2). 
8.3.2 DEFINITION OF SERIOUS ADVERSE EVENTS (SAE) 
An adverse event or suspected adverse reaction is considered a serious adverse event (SAE) if, in the 
view of the investigator it results in any of the following outcomes (21 CFR 312.32(a)): 
● 
Results in death; 
● 
Is life-threatening, i.e. places a participant at immediate risk of death from the event as it occurred; 
● 
Requires inpatient hospitalization or prolongation of existing hospitalization; 
● 
Results in a persistent or significant disability/incapacity; 
● 
Results in a congenital anomaly/birth defect; OR 
● 
Any other adverse event that, based upon appropriate medical judgment, may jeopardize the 
participant’s health and may require medical or surgical intervention to prevent one of the other 
outcomes listed in this definition Elective hospitalizations or hospital admissions for the purpose of 
conduct of protocol mandated procedures are not to be reported as an SAE unless hospitalization is 
prolonged due to complications. 
8.3.3 EVENTS OF SPECIAL INTEREST 
AEs of Special Interest (AESI) for the ManageHF trial, which may or may not meet serious criteria, 
include any of the following: 
● Symptomatic hypotension 
● 
Symptomatic bradycardia 
● 
Hyperkalemia (Potassium > 6.0 mEq/dl or requiring change in therapy) 

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● 
Worsening renal function (increase in creatinine by 0.5 mg/dl from last visit or requiring change 
in therapy) 
8.3.4 CLASSIFICATION OF AN ADVERSE EVENT 
AESI will be graded for severity and relationship to the intervention by the investigator according to the 
guidelines to be specified below. 
 
8.3.4.1 SEVERITY OF EVENT 
The following guidelines will be used to grade severity of AESI: 
● 
Mild – Events require minimal or no treatment and do not interfere with the participant's daily activities. 
● 
Moderate – Events result in a low level of inconvenience or concern with the therapeutic measures. 
Moderate events may cause some interference with functioning. 
● 
Severe – Events interrupt a participant's usual daily activity and may require systemic drug therapy or 
other treatment. Severe events are usually potentially life-threatening or incapacitating. Of note, the term 
“severe” does not necessarily equate to “serious”. 
8.3.4.2 RELATIONSHIP TO STUDY INTERVENTION 
All AESI must have their relationship to study intervention assessed by the clinician who examines and 
evaluates the participant based on temporal relationship and his/her clinical judgment. The degree of 
certainty about causality will be graded using the categories below. In a clinical trial, the study product 
must always be suspect. 
● 
Definitely Related – There is clear evidence to suggest a causal relationship, and other possible 
contributing factors can be ruled out. The clinical event, including an abnormal laboratory test result, 
occurs in a plausible time relationship to study intervention administration and cannot be explained by 
concurrent disease or other drugs or chemicals. The response to withdrawal of the study intervention 
(dechallenge) should be clinically plausible. The event must be pharmacologically or phenomenologically 
definitive, with use of a satisfactory rechallenge procedure if necessary. 
● 
Probably Related – There is evidence to suggest a causal relationship, and the influence of other factors is 
unlikely. The clinical event, including an abnormal laboratory test result, occurs within a reasonable time 
after administration of the study intervention, is unlikely to be attributed to concurrent disease or other 
drugs or chemicals, and follows a clinically reasonable response on withdrawal (dechallenge). Rechallenge 
information is not required to fulfill this definition. 
● 
Potentially Related – There is some evidence to suggest a causal relationship (e.g., the event occurred 
within a reasonable time after administration of the trial medication). However, other factors may have 
contributed to the event (e.g., the participant's clinical condition, other concomitant events). Although an 
AE may rate only as “possibly related” soon after discovery, it can be flagged as requiring more 
information and later be upgraded to “probably related” or “definitely related”, as appropriate. 

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● 
Unlikely to be related – A clinical event, including an abnormal laboratory test result, whose temporal 
relationship to study intervention administration makes a causal relationship improbable (e.g., the event 
did not occur within a reasonable time after administration of the study intervention) and in which other 
drugs or chemicals or underlying disease provides plausible explanations (e.g., the participant's clinical 
condition, other concomitant treatments). 
● 
Not Related – The AE is completely independent of study intervention administration, and/or evidence 
exists that the event is definitely related to another etiology. There must be an alternative, definitive 
etiology documented by the clinician. 
8.3.5 TIME PERIOD AND FREQUENCY FOR EVENT ASSESSMENT AND FOLLOW-UP 
AESI will be collected from the time of discharge for participants consented inpatient and from time of 
consent for participants consented outpatient. AESI will be collected until a participant completes study 
participation. AESI and serious adverse events may be discovered through any of these methods: 
● 
Observing the subject. 
● 
Interviewing the subject [e.g., using a checklist, structured questioning]. 
● 
Receiving an unsolicited report from the subject. 
Throughout the study, the investigator will record AESI and serious adverse events on the appropriate 
eCRF regardless of the relationship to study intervention. Once recorded, an AE/SAE will be followed 
until it resolves with or without sequelae, or until the end of study participation. 
8.3.6 ADVERSE EVENT REPORTING 
Only Adverse Events that meet SAE criteria and AESI will be reported in the ManageHF database. 
 
SAEs and AESI that occur from (1) the time of discharge for those consented inpatient or (2) the time of 
consent for those consented outpatient through completion of the final study visit will be reported in 
the ManageHF database in the following manner: 
● AEs of Interest that do not meet SAE criteria will be recorded on the eCRF. 
● SAEs that require hospitalization will be reported on the eCRF noting the reason for the 
hospitalization. 
● Secondary SAEs that may occur while a subject is hospitalized due to a different reason will be 
reported on the eCRF. 
● Deaths will be reported on the eCRF.  
● If the subject was hospitalized for the event that led to death, the event will need to be reported 
on the eCRF. 
The Investigator will follow all SAEs and AEs of Interest until resolution, stabilization or the event is 
otherwise explained.  
8.3.7 SERIOUS ADVERSE EVENT REPORTING 
SAEs are reportable from the time of discharge or consent (based on hospitalization status) until a 
subject completes study participation or until he/she prematurely withdraws or is withdrawn from the 

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study. All SAEs should be reported within 24 hours of site awareness. As additional details become 
available, the AE/SAE eCRF will be updated and submitted. 
  
When an SAE report is sent it will include the PI assessment of the adverse event and assignment of a 
relationship to any specific aspect of the study. In addition, an investigator may be requested to obtain 
specific additional follow-up information in an expedited fashion. This information may be more detailed 
than that captured on the adverse event case report form. In general, this will include a description of 
the adverse event in sufficient detail to allow for a complete medical assessment of the case and 
independent determination of possible causality. Information on other possible causes of the event, 
such as concomitant medications and illnesses must be provided. 
  
In the case of a subject death, a summary of available autopsy findings must be submitted as soon as 
possible to the DCC or its designated representative. The investigator’s assessment of causality must be 
provided. An investigator’s causality assessment is the determination of whether there exists a 
reasonable possibility that the investigational product caused or contributed to an adverse event. If the 
investigator's causality assessment is "unknown but not related to study intervention", this should be 
clearly documented on study records. In addition, if the investigator determines the adverse event is 
associated with trial procedures, the investigator must record this causal relationship in the source 
documents and eCRF, as appropriate. 
  
Expedited Safety Reporting 
The investigator shall report any suspected adverse reaction that is both serious and unexpected (i.e., 
serious and unexpected suspected adverse reaction [SUSAR]). The investigator shall report an adverse 
event as a suspected adverse reaction only if there is evidence to suggest a causal relationship between 
the study intervention and the adverse event, such as: 
1. A single occurrence of an event that is uncommon and known to be strongly associated with 
exposure to the intervention; 
2. One or more occurrences of an event that is not commonly associated with exposure to the 
intervention, but is otherwise uncommon in the population exposed to the intervention; 
3. An aggregate analysis of specific events observed in a clinical trial (such as known consequences 
of the underlying disease or condition under investigation or other events that commonly occur 
in the study population independent of the intervention) that indicates those events occur more 
frequently in the intervention group than in a concurrent or historical control group. 
SAEs that are related and unexpected will be reported to the DSMB by the protocol chairs and the DCC 
within 15 calendar days of their notification of the event. If a death or life-threatening event occurs that 
is believed by the site investigator to be related to the study intervention, notification to the DSMB by 
the protocol chairs and the DCC will occur within 7 calendar days after their initial notification of the 
event. Copies of the Expedited Safety Report will also be provided to the site investigators. 
 

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8.3.8 REPORTING EVENTS TO PARTICIPANTS 
Not applicable 
8.3.9 REPORTING OF PREGNANCY 
Pregnancies are not reported as serious adverse events. 
8.4 UNANTICIPATED PROBLEMS 
8.4.1 DEFINITION OF UNANTICIPATED PROBLEMS (UP) 
The Office for Human Research Protections (OHRP) considers unanticipated problems involving risks to 
participants or others to include, in general, any incident, experience, or outcome that meets all of the 
following criteria: 
● 
Unexpected in terms of nature, severity, or frequency given (a) the research procedures that are 
described in the protocol-related documents, such as the Institutional Review Board (IRB)-approved 
research protocol and informed consent document; and (b) the characteristics of the participant 
population being studied; 
● 
Related or possibly related to participation in the research (“possibly related” means there is a reasonable 
possibility that the incident, experience, or outcome may have been caused by the procedures involved in 
the research); and 
● 
Suggests that the research places participants or others at a greater risk of harm (including physical, 
psychological, economic, or social harm) than was previously known or recognized. 
8.4.2 UNANTICIPATED PROBLEM REPORTING 
The investigator will report unanticipated problems (UPs) to the reviewing institutional review board 
(IRB) and to the data coordinating center (DCC)/lead principal investigator (PI). The UP report will 
include the following information: 
● 
Protocol identifying information: protocol title and number, PI's name, and the IRB project number; 
● 
A detailed description of the event, incident, experience, or outcome; 
● 
An explanation of the basis for determining that the event, incident, experience, or outcome represents 
an UP; 
● 
A description of any changes to the protocol or other corrective actions that have been taken or are 
proposed in response to the UP. 
To satisfy the requirement for prompt reporting, UPs will be reported using the following timeline:  
● 
UPs that are serious adverse events (SAEs) will be reported to the IRB and to the DCC/study sponsor 
within 24 hours of the investigator becoming aware of the event. 
● 
Any other UP will be reported to the IRB and to the DCC/study sponsor within 2 weeks or 10 business days 
of the investigator becoming aware of the problem. 

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8.4.3 REPORTING UNANTICIPATED PROBLEMS TO PARTICIPANTS 
Not applicable.   
9 STATISTICAL CONSIDERATIONS 
9.1 SAMPLE SIZE DETERMINATION 
Each intervention (clinical worsening intervention and dietary sodium application) will be treated as a 
standalone study in this 2x2 factorial trial, so there is no need to adjust the Type I error in our sample 
size calculation. The primary endpoint is a composite of time to event of all-cause death, time to event 
of HF rehospitalization, and change in HRQOL from baseline to 12 weeks. A win ratio34  will be estimated 
to compare the number of participants receiving the interventions who remain event free longer and 
have more favorable quality of life change than those not receiving the intervention. A win ratio of 1.0 
indicates that both comparison groups have equivalent outcomes in terms of events and quality of life, 
while a win ratio > 1.0 indicates the intervention group has a favorable profile compared to the control 
group and < 1.0 indicates the intervention group has a unfavorable profile compared to the control 
group.  
We hypothesize that the win ratio for the hierarchical endpoint in our pilot study will be 1.33 in favor of 
the clinical worsening intervention group, meaning that people receiving the intervention will be 33% 
more likely to experience favorable outcomes compared to the group not given the intervention. 
Assuming 10% dropout, 500 randomized participants (250 per main intervention arm) provides 80% 
power to show a win ratio of 1.30 (56.6% winners in the intervention group excluding ties) assuming a 
two-sided 5% type-one error rate).34–36 Figure 3 shows the sample size calculation for different win ratios 
at 80% power. After dropout, 225 participants per arm will have completed the study, producing 50,400 
(225 x 224) permutations of paired comparisons.  Identical reasoning is applied to the power and sample 
size necessary for the analysis of the dietary intervention. 
  
A mediation analysis using structural equation modeling will be used to determine the proximal effect of 
the mobile phone apps results (M), “clinical worsening” and “dietary sodium intake”. Assuming 10% 
dropout, and an alpha of 0.05, this study’s 500 participants will provide at least 80% power to detect 
either a small standard effect size (0.14) on the association between each intervention and the proximal 
outcomes, and a medium effect size (0.39) on the association between proximal and distal outcomes, or 
a medium effect of each intervention on proximal results and a small effect on the association between 
proximal and distal outcomes.37  
 
There is insufficient power to detect an interaction effect of both interventions relative to the control.  
However, this effect will be estimated as an exploratory analysis. 

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9.2 POPULATIONS FOR ANALYSES 
All randomized participants will be included in the intent-to-treat (ITT) population, which is the analysis 
set used in all treatment comparisons of primary and secondary outcomes. All randomized participants 
who received an intervention (safety population) will be included in safety analyses. 
9.3 STATISTICAL ANALYSES 
9.3.1 GENERAL APPROACH 
The number of expected participants, the expected effect size, the power and the statistical methods for 
the clinical trial adequately address the factorial design study’s hypotheses.  As each primary analysis 
will be for an independent hypothesis concerning each individual intervention, there will be no 
multiplicity for corresponding statistical tests, and statistical tests with a two-sided p-value <0.05 will be 
considered statistically significant.  Secondary and tertiary analyses are considered hypothesis-
generating and will also not incorporate any adjustments for multiplicity.  Analyses will be performed 
using SAS software (SAS Institute, Inc., Cary, NC) or R freeware. 38 A statistical analysis plan (SAP) will be 
written for the study that contains detailed descriptions of the analyses to be performed; it will be 
finalized prior to the database lock. 
9.3.2 ANALYSES OF PRIMARY AND SECONDARY ENDPOINTS 
There are two primary hypotheses for the 2x2 factorial study that investigate the main effects of each of 
the 2 interventions: 
 
1. The use of the clinical worsening intervention will reduce deaths and HF readmissions and 
improve health-related quality of life compared to not using the intervention. 
2. The use of the dietary sodium intervention will reduce deaths and HF readmissions and improve 
health-related quality of life compared to not using the intervention. 
 
Note that all analyses will be conducted separately for each mobile app intervention. 
 
The primary outcome is a composite of death, HF readmission, and change in quality of life using the win 
ratio method, which incorporates a hierarchy of clinical prioritization on event occurrence. We do not 
expect an intervention effect on death but are including the event because of its importance using this 
methodology. Following the unmatched pairs win ratio method of Finkelstein and Schoenfeld,34–36 each 
participant receiving intervention will be compared to each participant not receiving intervention, 
resulting in Ni x Nni pairwise comparisons, where Ni is the sample size for the intervention arm, and Nni is 
the sample size for the non-intervention arm. For each comparison, “winners” will be determined 
according to Table 2, starting with scenario 1.  
 
 
Table 2 

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Scenario 
Time to 
all-cause 
death 
Time to HF 
readmission 
Change in 
MLHFQ 
Win/loss 
1 
Low 
  
  
Loss 
High 
  
  
Win 
2 
Tie or both 
alive 
Low 
  
Loss 
High 
  
Win 
3 
Tie or both 
alive 
Tie or both not 
hospitalized 
Comparator 
Loss 
12-week change 
>=5 points better 
than comparator 
Win 
4 
Tie or both 
alive 
Tie or both not 
hospitalized 
Comparator 
Tied 
12-week change 
within 5 points of 
comparator's 12-
week change 
Tied 
 
 
Within each pairing, the participant with the longest survival time is counted as the “winner” of that 
pairing. The win ratio is the number winners divided by the number of losers associated with the 
intervention.  The estimate of the win ratio will be calculated, and its 95% confidence interval will be 
calculated using bootstrap methods.  The test for intervention effect is a nonparametric rank sum test. 
In the event there is more than a 10% loss-to-follow-up, sensitivity analyses based on multiple 
imputation of the primary outcome will be conducted. However, if some lost or withdrawn participants 
were readmitted to hospital, a determination may still be possible for the win ratio statistic. 
For secondary endpoints, individual components of the composite outcome will be examined, using 
survival methods for time-to-event outcomes, and linear mixed effects models or piecewise linear 
regression for longitudinal continuous outcomes (e.g., MLHFQ).  The proportion of participants 
experiencing 30-day readmissions will be analyzed using logistic regression.  Number and percent of 
days alive and out of hospital (DAOH) will be analyzed using linear regression.39  Repeated measures 
proportional odds logistic regression40 will be used to compare NYHA classifications (ordinal 
measurements).27 If the proportionality assumption does not hold, the outcome will be dichotomized 
and a generalized linear mixed model will be used.  
 
For the primary analysis, the following stratification factors will be explored:  site, sex, race, and HF type 
(HFpEF versus HFrEF).  For the secondary analyses, the same stratification factors will be explored, and 
multivariable models will be fit adjusted for the same variables.  A subgroup analysis will be conducted 
to examine intervention effects by cognition and depression status. In addition, we will explore whether 
there is a signal for an interaction effect for the use of both mobile applications. 
 

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9.3.3 ANALYSES OF SECONDARY ENDPOINTS:  PROXIMAL OUTCOMES  
For Aim 2, we hypothesize that that each intervention, “clinical worsening – time in yellow and red” for 
the clinical worsening intervention and “measurement of dietary sodium intake” for the dietary sodium 
intervention is an intermediate outcome, with a significant association with the intervention, and 
significant association with a composite endpoint of death, hospitalization and 12-week MLHFQ decline.  
 
Mediation analysis will be used to discern the strength of these measurements as proximal 
outcomes.37,41 Structural equation modelling will be used to estimate the effect of each interventions 
proximal results (M), on the relationship between the mobile app interventions (X) on the distal 
outcomes (Y) of adverse heart failure outcomes and quality of life. In particular, we will estimate the 
effect of “clinical worsening – time in yellow and red” (M) on the relationship between the clinical 
worsening intervention (X) and clinical and quality of life outcomes (Y), and the effect of “measurement 
of dietary sodium intake” (M) on the relationship between the dietary sodium intervention (X) and the 
clinical and quality of life outcomes (Y). The structural equation model will consist of a statement on the 
association between the intervention (X) on the proximal outcome (M), and a statement on the 
association between (X) and (M) on (Y), assuming error terms are uncorrelated. Structural equation 
modelling will be used rather than widely used standard regression techniques such as those proposed 
in Baron and Kenny Causal Steps  because it provides more power to detect an effect, and because it 
acknowledges the role of the proximal outcome as both an effect of the intervention and a cause of the 
distal outcome.42,43 Both clinical outcomes and quality of life outcomes will be used to explore the 
assessment of the proximal outcomes as mediators. 
 
As secondary analyses, we will conduct the same mediation analysis using the individual components of 
the composite endpoint.  As exploratory analysis, we will conduct all the above analyses stratifying by 
race and gender.  
 
9.3.4 PREDICTION MODELING BASED ON APPLICATION DATA (EXPLORATORY ANALYSIS) 
 
A retrospective analysis of the data collected from the 500-participant clinical trial. Each participant day 
will be represented by a high-dimensional feature vector summarizing the current day and previous day 
(data preprocessing). In addition, each day will have a binary label indicating whether or not the 
participant felt clinically worse compared to the previous day. We formulate the problem as a binary 
classification task, in which we aim to map data in the feature space to a binary label. We will explore 
both population-level and participant-specific models. When training models for the entire populations, 
we will split the data at the participant-level into training and test sets. Using the training set, we will 
perform model selection for both linear (e.g., L2-regularized logistic regression) and non-linear models 
(e.g., XGBoost). We will evaluate the model’s ability to predict clinical worsening on the held-out test set 
in terms of model accuracy. When training participant-specific models, we will temporally split the data 
for an individual participant, training on data collected during the first period and testing on the 

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remaining held-out data. In addition to the model building and evaluation, we will use permutation 
importance to identify which variables are most predictive of a clinical worsening episode. Permutation 
importance is used since it is model agnostic, easily understandable and works with black-boxes. 
 
9.3.5 SAFETY ANALYSES 
The number of and proportion of participants with SAEs, (including segregation of those involving 
deaths), treatment-emergent AEs, and discontinuation of study intervention due to AEs will be 
presented, overall, and by randomization group (both intervention, diet intervention only, clinical 
worsening intervention only, neither intervention).  These presentations will be descriptive, with no 
formal inferential methods used.  The JITAIs are not expected to have great risk to participant safety.  
Thus, no specific rules for halting study enrollment or study interventions for safety are specified.  
 
In accordance with clinicaltrial.gov reporting requirements, the following tables are required and will be 
provided: 
● All-Cause Mortality:  A table of all anticipated and unanticipated deaths due to any cause, with 
the number and frequency of such events by arm or comparison group of the clinical study. 
● Serious Adverse Events:  A table of all anticipated and unanticipated serious adverse events, 
grouped by organ system, with the number and frequency of such events by arm or comparison 
group of the clinical study. (See Adverse Events definition below). 
● Other (Not Including Serious) Adverse Events:  A table of anticipated events of special interest 
(not included in the serious adverse event table) with the number and frequency of such events 
by arm or comparison group of the clinical study. 
9.3.6 BASELINE DESCRIPTIVE STATISTICS 
The two treatment groups for each intervention will be compared descriptively with respect to 
demographic and baseline variables (e.g., age, race, heart failure type).  No hypothesis tests will be used 
to compare the treatment groups.   
9.3.7 PLANNED INTERIM ANALYSES 
No interim analyses for futility nor benefit will be conducted. The final analyses of the clinical trial will be 
performed after the last subject last visit. 
9.3.8 TABULATION OF INDIVIDUAL PARTICIPANT DATA 
SAEs, deaths, AEs resulting in discontinuation of study intervention, and AEs will be tabulated for 
participants who experience these events.  

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10 SUPPORTING DOCUMENTATION AND OPERATIONAL CONSIDERATIONS 
10.1 REGULATORY, ETHICAL, AND STUDY OVERSIGHT CONSIDERATIONS 
10.1.1 INFORMED CONSENT PROCESS 
10.1.1.1 CONSENT/ASSENT AND OTHER INFORMATIONAL DOCUMENTS PROVIDED TO PARTICIPANTS 
IRB approved consent forms describing in detail the study intervention, study procedures, and risks are 
given to the participant and written documentation of informed consent is required prior to starting the 
study intervention.  
10.1.1.2 CONSENT PROCEDURES AND DOCUMENTATION 
Informed consent is a process that is initiated prior to the individuals agreeing to participate in the study 
and continues throughout the individual’s study participation. Consent forms will be IRB-approved and 
the participant will be asked to read and review the document. A study team member will explain the 
research study to the participant and answer any questions that may arise. A verbal explanation will be 
provided in terms suited to the participant’s comprehension of the purposes, procedures, and potential 
risks of the study and of their rights as research participants.  Participants will have the opportunity to 
carefully review the written consent form and ask questions prior to signing. 
  
The participants will be given the opportunity to discuss the study with their family or surrogates or 
think about it prior to agreeing to participate. The participant will sign the informed consent document 
prior to any procedures being done specifically for the study. Participants must be informed that 
participation is voluntary and that they may withdraw from the study at any time, without prejudice. A 
copy of the informed consent document will be given to the participants for their records. The informed 
consent process will be conducted and documented in the source document (including the date), and 
the form signed, before the participant undergoes any study-specific procedures. The rights and welfare 
of the participants will be protected by emphasizing to them that the quality of their medical care will 
not be adversely affected if they decline to participate in this study. 
 
If the protocol is amended and requires a change in the consent form, determination of whether a 
participant is re-consented will be based on IRB discretion.  
10.1.2 STUDY DISCONTINUATION AND CLOSURE 
This study may be temporarily suspended or prematurely terminated if there is sufficient reasonable 
cause. Written notification, documenting the reason for study suspension or termination, will be 
provided by the suspending or terminating party to study participants, investigators, funding agency, 
and regulatory authorities.  If the study is prematurely terminated or suspended, the PI will promptly 
inform study participants, the IRB, and sponsor and will provide the reason(s) for the termination or 
suspension.  Study participants will be contacted, as applicable, and be informed of changes to study 
visit schedule. 
  

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Circumstances that may warrant termination or suspension include, but are not limited to: 
● 
Determination of unexpected, significant, or unacceptable risk to participants 
● 
Insufficient compliance to protocol requirements 
● 
Data that are not sufficiently complete and/or evaluable 
● 
Determination that the primary endpoint has been met 
● 
Determination of futility 
Study may resume once concerns about safety, protocol compliance, and data quality are addressed, 
and satisfy the sponsor and/or the IRB. 
10.1.3 CONFIDENTIALITY AND PRIVACY 
Participant confidentiality and privacy is strictly held in trust by the participating investigators, their 
staff, and the sponsor(s) and their interventions. This confidentiality is extended to cover testing of 
biological samples and genetic tests in addition to the clinical information relating to participants. 
Therefore, the study protocol, documentation, data, and all other information generated will be held in 
strict confidence. No information concerning the study or the data will be released to any unauthorized 
third party without prior written approval of the sponsor. 
 
All research activities will be conducted in as private a setting as possible. 
 
The study monitor, other authorized representatives of the sponsor, representatives of the IRB, or 
regulatory agencies may inspect all documents and records required to be maintained by the 
investigator, including but not limited to, medical records (office, clinic, or hospital) and pharmacy 
records for the participants in this study. The clinical study site will permit access to such records. 
 
The study participant’s contact information will be securely stored at each clinical site for internal use 
during the study. At the end of the study, all records will continue to be kept in a secure location for as 
long a period as dictated by the reviewing IRB, Institutional policies, or sponsor requirements. 
  
Study participant research data, which is for purposes of statistical analysis and scientific reporting, will 
be transmitted to and stored at the University of Michigan. This will include the participant’s contact 
and identifying information.  The study data entry and study management systems used by clinical sites 
and by the University of Michigan research staff will be secured and password protected. At the end of 
the study, all study databases will be de-identified and archived at the University of Michigan. 
 
To protect participant confidentiality, mobile application data stored on participants’ devices is 
automatically encrypted before it is written to disk using 256-bit Advanced Encryption Standard (AES). 
AES encryption used for Android devices has an AES secret key that is encrypted with RSA and the RSA 
key is stored in KeyStore. Keychain is used for encryption on iOS devices. All mobile application data will 

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be stored on HIPAA-compliant servers to protect from loss of data or in case of the loss of the device. 
Participant data is transferred via secure sockets layer (SSL) and stored on a secure HIPAA-compliant 
server with encryption of all identifiable data. If there was a loss of information in transfer from mobile 
application to server, SSL ensures the data is encrypted and SSL is the industry standard. If data is stolen 
from our server, encryption of identifiable data ensures that the information cannot be linked to the 
individual in our study. 
 
We are also using an internet service, NumberEight, for location services. NumberEight uses sensors 
(Wi-Fi, Bluetooth, accelerometer, gyroscope, magnetometer, GPS) on the participant’s device to predict 
their location. User’s data is stored as long as the user is in the NumberEight system. User’s identifying 
information is anonymized in the system. The mobile sensor data and NumberEight profiles are not 
attached to the personalized identifiers (e.g. phone number). While participants will identify locations 
they commonly eat or purchase food and pin them on the map, study staff will not have access to 
participants’ location during the study.  
 
The self-monitoring devices (blood pressure cuff, scale, and activity tracker with heart rate monitor) are 
supplied by Withings. In order to ship the devices directly to the participants’ homes and activate the 
devices, the University of Michigan and Withings will need the participants’ name and address.  
  
Certificate of Confidentiality 
To further protect the privacy of study participants, a Certificate of Confidentiality are automatically 
issued by the National Institutes of Health (NIH).  This certificate protects identifiable research 
information from forced disclosure. It allows the investigator and others who have access to research 
records to refuse to disclose identifying information on research participation in any civil, criminal, 
administrative, legislative, or other proceeding, whether at the federal, state, or local level. By 
protecting researchers and institutions from being compelled to disclose information that would identify 
research participants, Certificates of Confidentiality help achieve the research objectives and promote 
participation in studies by helping assure confidentiality and privacy to participants. 
10.1.4 FUTURE USE OF STORED SPECIMENS AND DATA 
Data collected for this study will be analyzed and stored at the University of Michigan. After the study is 
completed, the de-identified, archived data will be transmitted to and stored in a repository, for use by 
other researchers including those outside of the study. Permission to transmit data to the repository will 
be included in the informed consent. 
10.1.5 KEY ROLES AND STUDY GOVERNANCE 
Principal Investigator 
Co-Medical Monitor 
Co-Medical Monitor 
Michael Dorsch, PharmD, MS 
 Scott Hummel, MD  
Todd Koelling, MD 
University of Michigan 
University of Michigan 
University of Michigan 
North University Bldg Rm 2560E 
1500 E Medical Center Dr #6303 1500 E Medical Center Dr SPC 5856 
Ann Arbor, MI 48109-2054 
Ann Arbor, MI 48109 
Ann Arbor, MI 48109 

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734-647-1452 
734-998-7991 
888-287-1082 
mdorsch@umich.edu 
scothumm@med.umich.edu 
tkoellin@med.umich.edu 
  
10.1.6 SAFETY OVERSIGHT 
Safety oversight will be under the direction of a Data and Safety Monitoring Board (DSMB) composed of 
individuals with the appropriate expertise, including members with expertise in heart failure medicine, 
statistics, epidemiology, and/or research ethics. Members of the DSMB should be independent from the 
study conduct and free of conflict of interest, or measures should be in place to minimize perceived 
conflict of interest.  The DSMB will meet at least semiannually to assess safety and efficacy data on each 
arm of the study. The DMSB will operate under the rules of an approved charter that will be written and 
reviewed at the organizational meeting of the DSMB. At this time, each data element that the DSMB 
needs to assess will be clearly defined. The DSMB will provide its input to the National Institute on Aging 
(NIA), DCC and the PI.  
 
The DSMB will act in an advisory capacity to the study team and NIA to monitor patient safety, data 
quality and to evaluate the ability of the trial to achieve its research goals. The DSMB serves in an 
advisory capacity to the sponsor (study PIs and NIA). They will review the study protocol, monitor all 
aspects of the study (e.g., recruitment, adverse events, protocol adherence, data quality, attrition, 
demographic and baseline characteristics) and recommend protocol modifications, including early study 
termination. All proposed changes to the study protocol will be reviewed by the DSMB.  
 
Reports will be prepared by the DCC every 6 months and will be sent to the DSMB. These will minimally 
include recruitment, adherence, attrition, adverse events, data quality (e.g., missed visits, late visits), 
and descriptive characteristics of the study sample. The DSMB will routinely meet yearly via 
teleconference/webinar to review the cumulative data. An executive secretary will be present for all 
DSMB meetings. The sponsor or the chairman of the DSMB in consultation with the sponsor may 
convene additional meetings. Based on the data presented, the DSMB will make recommendations 
including continuation or termination of the study. 
 
A formal report containing the recommendations for continuation or modifications of the study, 
prepared by the DSMB executive secretary with concurrence from the DSMB, will be sent to the sponsor 
within 4 weeks. The DCC will forward the DSMB report or a summary of the DSMB recommendations to 
the clinical study site PI(s). It is the responsibility of the PI(s) to distribute this report to all co-
investigators and to assure that copies are submitted to all the IRBs associated with the study. 
10.1.7 CLINICAL MONITORING 
Remote site visits will be conducted by the DCC.  
 
More detailed information about clinical monitoring can be found in the Clinical Monitoring Plan. 

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10.1.8 QUALITY ASSURANCE AND QUALITY CONTROL 
Each clinical site will perform internal quality management of study conduct, data collection, 
documentation and completion. An individualized quality management plan will be developed to 
describe a site’s quality management. 
  
Quality control (QC) procedures will be implemented beginning with the data entry system and data QC 
checks that will be run on the database will be generated. Any missing data or data anomalies will be 
communicated to the site(s) for clarification/resolution. 
  
Following written Standard Operating Procedures (SOPs), the monitors will verify that the clinical trial is 
conducted, and data are generated, documented (recorded), and reported in compliance with the 
protocol and ICH GCP. 
  
The investigational site will provide direct access to all trial related sites, source data/documents, and 
reports for the purpose of monitoring and auditing by the sponsor, and inspection by local and 
regulatory authorities. 
10.1.9 DATA HANDLING AND RECORD KEEPING 
10.1.9.1 DATA COLLECTION AND MANAGEMENT RESPONSIBILITIES 
Data collection is the responsibility of the clinical trial staff at the site under the supervision of the site 
investigator. The investigator is responsible for ensuring the accuracy, completeness, legibility, and 
timeliness of the data reported. 
  
All source documents should be completed in a neat, legible manner to ensure accurate interpretation 
of data.  
  
Data recorded in the electronic case report form (eCRF) derived from source documents should be 
consistent with the data recorded on the source documents. 
  
Clinical data (including adverse events (AEs), concomitant medications, and expected adverse reactions 
data) and clinical laboratory data will be entered into RedCap, a data capture system provided by the 
University of Michigan. The data system includes password protection and internal quality checks, such 
as automatic range checks, to identify data that appear inconsistent, incomplete, or inaccurate. Clinical 
data will be entered directly from the source documents. 
 
Participant self-administered questionnaires at baseline, week 6 and week 12 will be captured directly 
into Redcap through a participant portal. Due to the length of the FFQ, paper copies may be available for 
participants who prefer to complete a paper and pencil version. Daily self-monitoring performed by the 
participants (weight, blood pressure, activity monitor) will be transmitted to the study app. The daily 8 
question survey assessing participants’ HF symptoms every day will be administered within the mobile 
application 

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10.1.9.2 STUDY RECORDS RETENTION 
Each clinical study site will maintain the paper data for the study for at least 5 years after the study 
ends, or per local or federal requirements. 
10.1.10 PROTOCOL DEVIATIONS 
All local sites are required to report all protocol deviations that significantly impact the integrity of the 
study or subject safety in Redcap. All reports must be made within 10 business days through Advarra’s 
IRB platform. Any event that requires immediate action will be brought to the attention of the IRB Chair. 
All protocol-wide decisions will be coordinated with the lead site. All other events will be coordinated 
with the submitting party. Events that meet the criteria of serious and/or continuing noncompliance will 
be communicated to the submitting party and the lead site by Advarra. Advarra will ensure prompt 
reporting to the applicable Federal Agency. The lead site will have access to all reported events of 
noncompliance across each local site. 
10.1.11 PUBLICATION AND DATA SHARING POLICY 
The PI will share unique research resources developed by the proposed study in accordance with NIH 
and policies at each clinical study site. As NIH policy requires that unique research resources be made 
available to the scientific community after the conclusion of a study, the DCC will plan to release 
databases and adequate descriptors to allow other investigators to determine relevance of the 
materials. In accordance with NIH NOT-OD-16-149 and DHHS rule 81 FR 64922, we plan to register our 
trial with and report our results to clinicaltrials.gov as well as present our findings through convention 
dissemination routes like publications and presentations at specialty societies. 
  
Resource sharing may include sharing of study documents (e.g., recruitment materials, protocols, SOPs, 
informed consents, and CRFs that may be useful as starting points for other studies) as well as sharing of 
data and other participant information. Study participants will be informed about sharing of their 
information and possible risks of breach of confidentiality and will consent to sharing of their 
information in order to participate. Identification of individuals even in limited access datasets may be 
possible. Therefore, care will be taken in drafting consent language that describes sharing and in 
creating sharing plans and datasets. 
 
Our aim will be to prepare data for deposit into the National Institute on Aging supported National 
Archive of Computerized Data on Aging (NACDA) data repository, located within the Inter-university 
Consortium for Political and Social Research (ICPSR) (https://www.icpsr.umich.edu). ICPSR is an 
international consortium of more than 750 academic institutions and research organizations that 
advances social and behavioral research, acting as a global leader in data stewardship. Researchers at 
institutions with a Federal Wide Assurance will be able to gain access to repository data by submitting a 
data access request in accordance with applicable policies. In order to prepare for the eventual archiving 
and sharing of data: 
a. We will use consent forms that allow broad data sharing within the research community. 

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b.  We will create global unique identifiers (GUIDS) for all research participants in the study. 
c. We will use the NIH Common Data Elements (CDE) (or Clinical Data Acquisition Standards 
Harmonization (CDASH, part of the Clinical Data Interchange Standards Consortium or CDISC) 
and incorporate appropriate measures to serve as the source for data elements included in our 
CRFs. This will standardize the definitions and data collection, thereby improving data quality, 
while also making the data more readily accessible for data sharing and incorporation in meta-
analyses. Examples of such forms include demographic, adverse events, and protocol deviation 
forms. We will also explore other disease-specific CDEs with National Institute on Aging. 
We understand that because of the nature of our clinical trial (PI masked to results until interim and 
final analyses), it is unlikely the data will be released to the research community until after the award is 
complete; however, the DCC will prepare the de-identified data during year 5 after the database lock. As 
per National Institute on Aging policy, these datasets will be reviewed prior to release and shared 
through the NACDA data repository, no later than 3 years after the end of the study or 2 years after the 
main paper reporting the results of the trial, whichever comes first. The de-identified analytic data will 
be prepared as SAS transport files or ASCII comma-delimited files with accompanying codebooks that 
describe the data and data structure. The redaction will employ best practices and will be consistent 
with National Institute on Aging data sharing policies. 
10.1.12 CONFLICT OF INTEREST POLICY 
The independence of this study from any actual or perceived influence is critical.  Therefore, any actual 
conflict of interest of persons who have a role in the design, conduct, analysis, publication, or any aspect 
of this trial will be disclosed and managed. Furthermore, persons who have a perceived conflict of 
interest will be required to have such conflicts managed in a way that is appropriate to their 
participation in the design and conduct of this trial.  
10.2 ADDITIONAL CONSIDERATIONS 
None 
 
10.3 ABBREVIATIONS 
AE 
Adverse Event 
AESI 
Adverse Event of Special Interest 
AHRQ 
Agency for Healthcare Research and Quality  
BNP 
Brain Natriuretic Peptide  
BP 
Blood Pressure  
CCC 
Clinical Coordinating Center 
CDASH 
Clinical Data Acquisition Standards Harmonization 
CDE 
NIH Common Data Elements  

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CDISC 
Clinical Data Interchange Standards Consortium 
CFR 
Code of Federal Regulations 
CONSORT 
Consolidated Standards of Reporting Trials 
CRF 
Case Report Form 
CRT 
Cardiac Resynchronization Therapy  
DAOH 
Days Alive and Out of Hospital  
DCC 
Data Coordinating Center 
DHHS 
Department of Health and Human Services 
DSMB 
Data Safety Monitoring Board 
eCRF 
Electronic Case Report Forms 
FFQ 
Block Food Frequency Questionnaire  
GCP 
Good Clinical Practice 
GOURMET-HF 
Geriatric OUt-of-hospital Randomized MEal Trial in Heart Failure  
GUIDS 
Global Unique Identifiers  
HADS 
Hospital Anxiety and Depression Scale 
HF 
Heart Failure 
HRQOL 
Health Related Quality of Life 
HSI 
health status indicator  
ICH 
International Conference on Harmonization 
IRB 
Institutional Review Board 
ITT 
Intention-To-Treat 
JITAI 
Just-In-Time Adaptive Interventions 
KCCQ 
Kansas City Cardiomyopathy Questionnaire  
LVEF 
Left ventricular ejection fraction  
MLHFQ 
Minnesota Living with Heart Failure Questionnaire 
MMSE 
Mini-Mental State Exam  
MNA 
Self Mini Nutritional Assessment 
MOP 
Manual of Procedures 
NACDA 
National Institute on Aging supported National Archive of Computerized Data 
on Aging  
NIH 
National Institutes of Health 
NIA 
National Institutes of Aging 
HSI 
health status indicator  
NYHA 
New York Heart Association  
OHRP 
Office for Human Research Protections 
PHI 
Patient Health Information  
PI 
Principal Investigator 
QC 
Quality Control 
SAE 
Serious Adverse Event 
SABER 
Statistical Analysis of Biomedical and Educational Research  
SAP 
Statistical Analysis Plan 

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SCHFI 
Self-Care in Heart Failure Index 
SOA 
Schedule of Activities 
SOP 
Standard Operating Procedure 
SUSAR 
Serious and Unexpected Suspected Adverse Reaction  
UP 
Unanticipated Problem 
US 
United States 
 
 
10.4 PROTOCOL AMENDMENT HISTORY 
Version 
Date 
Description of Change  
Brief Rationale 
 1.1 
2020.12.17 
Section 1.3: Moved the 
timing of the HADS and 
nutritional assessments from 
day of discharge to 
screening/enrollment. 
 
 
 
 
 
 
 
Section 8.2 Added the 
HRQOL and nutritional 
assessments to the list of 
items at the  screening/ 
baseline visit. 
This will streamline the 
workflow. Coordinators will 
be present to answer 
participants’ questions and 
ensure data collection is 
completed. This will also 
decrease the amount of 
activities the participant 
needs to complete 
immediately upon discharge. 
 
For internal consistency 
within the protocol to match 
the change described above. 
Section 8.2 now matches the 
schedule of activities. 
 
1.2 
2021.04.09 
Added language to describe 
the smartphone inclusion 
criteria more clearly (bolded 
text is new): 
A smartphone with a 
compatible Apple or Android 
operating system installed 
and able to download and 
use ManageHF including 
accepting all permissions 
To ensure the app works as 
intended, the smartphone 
must run a compatible 
operating system and all 
permissions must be 
accepted.  
1.2  
2021.12.03 
Updated the study workflow 
to reflect the new visit 
windows. 
The study workflow has been 
updated to reflect the 
changes included in this 
amendment. 
1.3 
2021.12.03 
Screening, recruitment, 
enrollment, and the baseline 
Recruitment and enrollment 
have been slower than 

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visit can now occur up to 7 
days post-discharge. 
 
 
 
 
 
 
 
 
The visit windows for weeks 
6 & 12 have been extended 
to +/-10 days.  
 
 
 
 
The 1-question NHYA survey 
is not required for 
randomization 
 
 
 
Process for randomizing 
participants who are re-
hospitalized has been spelled 
out. 
anticipated. The sites have 
indicated they are 
experiencing challenges 
approaching participants 
before discharge. It is 
expected that extending the 
enrollment and baseline visits 
to up to 7 days post-discharge 
will improve enrollment by 
giving the participants and 
coordinators additional time 
to complete all enrollment 
activities.  
 
 
Due to low survey completion 
at weeks 6 & 12, we are 
extending the visit windows to 
give participants more time to 
complete the survey and give 
the coordinators more time to 
follow up.  
 
 
This one question survey is 
not a primary outcome 
measure and we do not want 
to lose participants due to 1 
missing question. 
 
 
By allowing enrollment to 
occur after discharge, there is 
a higher likelihood a 
participant could be re-
hospitalized prior to 
randomization.  
5.1 
2021.12.03 
Inclusion criterion #1 – 
removed “and able to 
provide consent” 
 
Inclusion criterion #2 – 
changed language to “or 
discharged from the hospital 
within the last 7 days with a 
diagnosis of” 
This text was redundant as it 
is already mentioned in 
inclusion criterion #8. 
 
The language added to 
inclusion criterion #2 allows 
participants to be enrolled up 
to 7 days post-discharge.  
5.3 
2021.12.03 
Added: Participants whose 
Low sodium intake is a 

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sodium intake is less than 
1,500 mg per day as 
measured by the Block 
Sodium Screener will be 
considered screen fails. 
 
Added: If a participant is 
randomized during a re-
hospitalization they will be 
considered a screen failure. 
contraindication for this study 
(exclusion criterion #1) due to 
the dangers associated with 
too little sodium.  
 
Time to readmission is an 
outcome measure. 
Participants who are 
readmitted prior to 
randomization would 
confound the primary 
outcome measure. They will 
be recorded as screen failures 
and can be re-evaluated for 
eligibility based on their new 
hospitalization. 
 
6.1.2 
2021.12.03 
Added an abbreviation for 
adverse events of special 
interest (AESI).  
 
 
Changed timing of 
randomization from upon 
discharge to ‘after the 
baseline MLHFQ is 
completed’ 
 
 
Removed reference to after 
discharge. 
Abbreviation was added for 
ease of reading and for 
consistency with the use of 
other abbreviations in the 
document (e.g. SAE). 
 
Since participants may be 
enrolled after discharge, the 
text was updated to reflect 
that randomization will occur 
after the MLHFQ is 
completed. 
 
Removed since participants 
may be enrolled after 
discharge. 
7.2 
2021.12.03 
Removed: Adverse events of 
special interest will be 
collected from the time of 
discharge through study 
completion or study 
withdrawal/discontinuation. 
Section 8 details how AESIs 
will be captured. 
7.3 
2021.12.03 
Revised text: A participant 
will be considered lost to 
follow-up if he or she fails to 
completely engage (i.e. 
never uses the study devices 
or interacts with the mobile 
app does not complete 
surveys at week 6 and 12) 
Study endpoints use data 
from weeks 6 and 12. If data is 
missing from both time 
points, the participant will be 
considered lost to follow up. 
 
 
 

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with the mobile application 
and is unable to be 
contacted by the study site 
staff. 
 
Added: “at week 12” to 
bullet point #3. 
 
 
 
 
 
Added:  A medical record 
review at the 12-week visit 
will be completed in order to 
obtain various endpoints. 
 
If a participant is unreachable 
at week 6, every attempt 
should be made to contact 
the participant at week 12 
before considering the 
participant lost to follow up. 
 
 
A medical chart review will be 
conducted at week 12 to 
gather any available 
endpoints. 
8.1 
2021.12.03 
Added a paper copy option 
for the FFQ.  
Due to the length of the FFQ, 
the sites have indicated some 
of their participants would 
prefer to complete the survey 
via paper instead of 
electronically. 
8.2 
2021.12.03 
Reordered baseline 
questionnaires  
 
 
 
Indicated that the Block 
Sodium Screener is a 
screening assessment 
 
 
 
Summary of assessment 
table – updated time 
commitment for the FFQ 
from 35 minutes to 45 
minutes. 
Administrative change only to 
reflect the order of the 
questionnaires as they appear 
in the real-world 
 
The Block Sodium Screener is 
used as a screening 
instrument to rule out 
participants whose sodium 
intake is too low and further 
reduction could cause harm. 
 
 
Based on feedback from the 
coordinators, the FFQ is taking 
approximately 45 minutes to 
complete.  
8.3.5 
2021.12.03 
Revised text (bolded text is 
added): AESI will be 
collected from the time of 
discharge for participants 
consented inpatient and 
from time of consent for 
participants consented 
outpatient. AESI will be 
The clarifying language is 
necessary to describe the 
timeframe for collecting AESI 
based on hospitalization 
status at time of consent 
(inpatient vs outpatient). 

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collected until a participant 
completes study 
participation 
8.3.6 
2021.12.03 
Revised text (bolded text is 
added): SAEs and AESI that 
occur from (1) the time of 
discharge for those 
consented inpatient or (2) 
the time of consent for 
those consented outpatient 
through completion of the 
final study visit will be 
reported in the ManageHF 
database in the following 
manner 
The clarifying language is 
necessary to describe the 
timeframe for collecting SAEs 
and AESI based on 
hospitalization status at time 
of consent (inpatient vs 
outpatient). 
8.3.7 
2021.12.03 
Revised text (bolded text is 
added): SAEs are reportable 
from the time of discharge or 
consent (based on 
hospitalization status) until 
a subject… 
The clarifying language is 
necessary to describe the 
timeframe for collecting SAEs 
based on hospitalization 
status at enrollment 
(inpatient vs outpatient). 
10.1.9.1 
2021.12.03 
Added text: Due to the 
length of the FFQ, paper 
copies may be available for 
participants who prefer to 
complete a paper and pencil 
version. 
Due to the length of the FFQ, 
the sites have indicated some 
of their participants would 
prefer to complete the survey 
via paper instead of 
electronically. 
10.1.3 
2021.12.03 
Added bolded text: In order 
to ship the devices directly to 
the participant’s homes and 
activate the devices, the 
University of Michigan and 
Withings will need the 
participant’s name,  address, 
and email address.  
 
Providing Withings with the 
participant’s email address 
will allow the participant to 
receive a shipping 
confirmation email with 
tracking information. 
10.3 
2021.12.03 
Added: AESI to the 
abbreviation table. 
Added for internal consistency 
of the document. 
1.2, 5.1, 5.2 
2022.04.18 
Update inclusion and 
exclusion criteria 
Due to lower than expected 
recruitment, the inclusion and 
exclusion criteria have been 
revised to include a broader 
pool of patients with heart 
failure. 
5.4 
2022.04.18 
Added compensation with 
timing and dollar amount. 
Participant incentives have 
been added to improve 

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Added texting as a 
participant contact method. 
participant recruitment and 
retention 
 
The DSMB recommended 
adding texting as participant 
contact method to improve 
participant retention. 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
 
11 REFERENCES 
REFERENCES 
1 
Benjamin EJ, Virani SS, Callaway CW, Chamberlain AM, Chang AR, Cheng S, et al. American Heart Association 
Council on epidemiology and prevention statistics committee and stroke statistics subcommittee. Heart 
Disease and Stroke Statistics-2018 Update: A Report from the American Heart Association Circulation 
2018;137:e67–492. 
2 
Kommuri NVA, Koelling TM, Hummel SL. The Impact of Prior Heart Failure Hospitalizations on Long-Term 
Mortality Differs by Baseline Risk of Death. Journal of Cardiac Failure 2011:S73. 
https://doi.org/10.1016/j.cardfail.2011.06.246. 
3 
Dharmarajan K, Wang Y, Lin Z, Normand S-LT, Ross JS, Horwitz LI, et al. Association of Changing Hospital 
Readmission Rates With Mortality Rates After Hospital Discharge. JAMA 2017;318:270–8. 
4 
Lee DS, Austin PC, Stukel TA, Alter DA, Chong A, Parker JD, et al. ‘Dose-dependent’ Impact of Recurrent 
Cardiac Events on Mortality in Patients with Heart Failure. Am J Med 2009;122:162.e1–162.e9. 
5 
Rodríguez-Artalejo F, Guallar-Castillón P, Pascual CR, Otero CM, Montes AO, García AN, et al. Health-related 
quality of life as a predictor of hospital readmission and death among patients with heart failure. Arch Intern 
Med 2005;165:1274–9. 
6 
Goodwin JS, Howrey B, Zhang DD, Kuo Y-F. Risk of continued institutionalization after hospitalization in older 
adults. J Gerontol A Biol Sci Med Sci 2011;66:1321–7. 
7 
Vidic A, Chibnall JT, Hauptman PJ. Heart failure is a major contributor to hospital readmission penalties. J Card 
Fail 2015;21:134–7. 
8 
Bradley EH, Curry L, Horwitz LI, Sipsma H, Thompson JW, Elma M, et al. Contemporary evidence about 
hospital strategies for reducing 30-day readmissions: a national study. J Am Coll Cardiol 2012;60:607–14. 
9 
Kociol RD, Peterson ED, Hammill BG, Flynn KE, Heidenreich PA, Piña IL, et al. National survey of hospital 
strategies to reduce heart failure readmissions: findings from the Get With the Guidelines-Heart Failure 
registry. Circ Heart Fail 2012;5:680–7. 
10 Baker H, Oliver-McNeil S, Deng L, Hummel SL. Regional Hospital Collaboration and Outcomes in Medicare 
Heart Failure Patients: See You in 7. JACC Heart Fail 2015;3:765–73. 
11 Ibrahim AM, Dimick JB, Sinha SS, Hollingsworth JM, Nuliyalu U, Ryan AM. Association of Coded Severity With 
Readmission Reduction After the Hospital Readmissions Reduction Program. JAMA Intern Med 2018;178:290–
2. 
12 Abdul-Aziz AA, Hayward RA, Aaronson KD, Hummel SL. Association Between Medicare Hospital Readmission 

 ManageHF Protocol  
 
 
 
 
 
 
 
 
        Version 3.1 
 27 September 2022 
54 
 
Penalties and 30-Day Combined Excess Readmission and Mortality. JAMA Cardiol 2017;2:200–3. 
13 Retrum JH, Boggs J, Hersh A, Wright L, Main DS, Magid DJ, et al. Patient-identified factors related to heart 
failure readmissions. Circ Cardiovasc Qual Outcomes 2013;6:171–7. 
14 Gilotra NA, Shpigel A, Okwuosa IS, Tamrat R, Flowers D, Russell SD. Patients Commonly Believe Their Heart 
Failure Hospitalizations Are Preventable and Identify Worsening Heart Failure, Nonadherence, and a 
Knowledge Gap as Reasons for Admission. Journal of Cardiac Failure 2017:252–6. 
https://doi.org/10.1016/j.cardfail.2016.09.024. 
15 Annema C, Luttik M-L, Jaarsma T. Reasons for readmission in heart failure: Perspectives of patients, 
caregivers, cardiologists, and heart failure nurses. Heart Lung 2009;38:427–34. 
16 Michalsen A, König G, Thimme W. Preventable causative factors leading to hospital admission with 
decompensated heart failure. Heart 1998;80:437–41. 
17 Dharmarajan K, Hsieh AF, Lin Z, Bueno H, Ross JS, Horwitz LI, et al. Diagnoses and Timing of 30-Day 
Readmissions After Hospitalization for Heart Failure, Acute Myocardial Infarction, or Pneumonia. JAMA 
2013:355. https://doi.org/10.1001/jama.2012.216476. 
18 WRITING COMMITTEE MEMBERS, Yancy CW, Jessup M, Bozkurt B, Butler J, Casey DE Jr, et al. 2013 ACCF/AHA 
guideline for the management of heart failure: a report of the American College of Cardiology 
Foundation/American Heart Association Task Force on practice guidelines. Circulation 2013;128:e240–327. 
19 Lindenfeld J, Albert NM, Boehmer JP, Collins SP, Ezekowitz JA, Givertz MM, et al. HFSA 2010 comprehensive 
heart failure practice guideline. J Card Fail 2010;16:e1–194. 
20 Gupta D, Georgiopoulou VV, Kalogeropoulos AP, Dunbar SB, Reilly CM, Sands JM, et al. Dietary sodium intake 
in heart failure. Circulation 2012;126:479–85. 
21 Lennie TA, Song EK, Wu J-R, Chung ML, Dunbar SB, Pressler SJ, et al. Three Gram Sodium Intake is Associated 
With Longer Event-Free Survival Only in Patients With Advanced Heart Failure. Journal of Cardiac Failure 
2011:325–30. https://doi.org/10.1016/j.cardfail.2010.11.008. 
22 Doukky R, Avery E, Mangla A, Collado FM, Ibrahim Z, Poulin M-F, et al. Impact of Dietary Sodium Restriction 
on Heart Failure Outcomes. JACC Heart Fail 2016;4:24–35. 
23 Global Burden of Cardiovascular Diseases Collaboration, Roth GA, Johnson CO, Abate KH, Abd-Allah F, Ahmed 
M, et al. The Burden of Cardiovascular Diseases Among US States, 1990-2016. JAMA Cardiol 2018;3:375–89. 
24 Shively M, Kodiath M, Smith TL, Kelly A, Bone P, Fetterly L, et al. Effect of behavioral management on quality 
of life in mild heart failure: a randomized controlled trial. Patient Educ Couns 2005;58:27–34. 
25 Varma S, McElnay JC, Hughes CM, Passmore AP, Varma M. Pharmaceutical care of patients with congestive 
heart failure: interventions and outcomes. Pharmacotherapy 1999;19:860–9. 
26 Dorsch MP, Farris KB, Bleske BE, Koelling TM. A web application for self-monitoring improves symptoms in 
chronic systolic heart failure. Telemed J E Health 2015;21:267–70. 
27 Wessler JD, Maurer MS, Hummel SL. Evaluating the safety and efficacy of sodium-restricted/Dietary 
Approaches to Stop Hypertension diet after acute decompensated heart failure hospitalization: design and 
rationale for the Geriatric OUt of hospital Randomized MEal Trial in Heart Failure (GOURMET-HF). Am Heart J 
2015;169:342–8.e4. 
28 Treskes RW, van Winden LAM, van Keulen N, van der Velde ET, Beeres SL, Atsma DE, et al. Effect of 
Smartphone-Enabled Health Monitoring Devices vs Regular Follow-up on Blood Pressure Control Among 
Patients After Myocardial Infarction: A Randomized Clinical Trial. JAMA Network Open 2020;3:e202165–
e202165. 
29 Heo S, Moser DK, Lennie TA, Payne-Emerson H, Welch JL, Weaver M. Development and testing of the 
feasibility and acceptability of a tailored dietary intervention in patients with heart failure. J Cardiovasc Nurs 
2015;30:213–21. 
30 Hicks KA, Mahaffey KW, Mehran R, Nissen SE, Wiviott SD, Dunn B, et al. 2017 Cardiovascular and Stroke 
Endpoint Definitions for Clinical Trials. Circulation 2018;137:961–72. 
31 Holland R, Rechel B, Stepien K, Harvey I, Brooksby I. Patients’ self-assessed functional status in heart failure by 
New York Heart Association class: a prognostic predictor of hospitalizations, quality of life and death. J Card 
Fail 2010;16:150–6. 
32 Vellas B, Villars H, Abellan G, Soto ME, Rolland Y, Guigoz Y, et al. Overview of the MNA--Its history and 
challenges. J Nutr Health Aging 2006;10:456–63; discussion 463–5. 
33 Rubenstein LZ, Harker JO, Salvà A, Guigoz Y, Vellas B. Screening for undernutrition in geriatric practice: 

 ManageHF Protocol  
 
 
 
 
 
 
 
 
        Version 3.1 
 27 September 2022 
55 
 
developing the short-form mini-nutritional assessment (MNA-SF). J Gerontol A Biol Sci Med Sci 
2001;56:M366–72. 
34 Pocock SJ, Ariti CA, Collier TJ, Wang D. The win ratio: a new approach to the analysis of composite endpoints 
in clinical trials based on clinical priorities. European Heart Journal 2012:176–82. 
https://doi.org/10.1093/eurheartj/ehr352. 
35 Finkelstein DM, Schoenfeld DA. Combining mortality and longitudinal measures in clinical trials. Stat Med 
1999;18:1341–54. 
36 Kotalik A, Eaton A, Lian Q, Serrano C, Connett J, Neaton JD. A win ratio approach to the re-analysis of Multiple 
Risk Factor Intervention Trial. Clin Trials 2019;16:626–34. 
37 MacKinnon DP, Fairchild AJ, Fritz MS. Mediation analysis. Annu Rev Psychol 2007;58:593–614. 
38 Team RC. R: a language and environment for statistical computing. R Foundation for Statistical Computing, 
Vienna. http s. Www R-Proje Ct Org 2017. 
39 Ariti CA, Cleland JGF, Pocock SJ, Pfeffer MA, Swedberg K, Granger CB, et al. Days alive and out of hospital and 
the patient journey in patients with heart failure: insights from the candesartan in heart failure: assessment of 
reduction in mortality and morbidity (CHARM) program. Am Heart J 2011;162:900–6. 
40 Parsons NR, Costa ML, Achten J, Stallard N. Repeated measures proportional odds logistic regression analysis 
of ordinal score data in the statistical software package R. Comput Stat Data Anal 2009;53:632–41. 
41 Imai K, Keele L, Tingley D. A general approach to causal mediation analysis. Psychol Methods 2010;15:309–34. 
42 MacKinnon DP, Fairchild AJ. Current Directions in Mediation Analysis. Curr Dir Psychol Sci 2009;18:16–20. 
43 Clark AM, Thirsk LM, Wiens KS, Ski CF, Thompson DR. How to research the mechanisms of non-
pharmacological cardiac interventions. Int J Cardiol 2015;201:457–61. 
 

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12 APPENDICES 
APPENDIX A – PATIENT INFORMATION SHEETS 

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