Apple Heart Study: Assessment of Wristwatch-Based Photoplethysmography to Identify Cardiac Arrhythmias
Phase: NA
Conditions: Atrial Fibrillation, Arrhythmias, Cardiac, Atrial Flutter
Sponsor: Apple Inc.

Protocol
Study Official Title: Apple Heart Study: Assessment of Wristwatch-Based
Photoplethysmography to Identify Cardiac Arrhythmias
ClinicalTrials.gov Identifier: NCT03335800
Document Date: 20 Mar 2018

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1 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
Protocol 
Apple Heart Study 
Assessment of Wristwatch-Based Photoplethysmography to Identify Cardiac 
Arrhythmias 
Protocol Version:  
8.0   
Protocol Date:  
March 20, 2018 
Sponsor: 
Apple Inc. 
1 Infinite Loop 
Cupertino CA 95014 
United States 
Coordinating Principal Investigators and Study Contacts: 
Marco V. Perez, MD 
Assistant Professor of Medicine 
Stanford University 
300 Pasteur Dr., M/C 5773 
Stanford, CA 94305 
Tel (650) 723-9363 
Fax (650) 725-7568 
E-mail: mvperez@stanford.edu
Minang (Mintu) Turakhia, MD, MAS 
Associate Professor of Medicine 
Stanford University 
1070 Arastradero Rd 
Palo Alto, CA 94304 
Phone: (650) 497-9345 
E-mail: mintu@stanford.edu
In collaboration with Stanford Center for Clinical Research (SCCR), Quantitative 
Sciences Unit (QSU), and Center for Digital Health (CDH). 

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3 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
INVESTIGATORS’ SIGNATURE PAGE 
 
  
STUDY TITLE:  
Apple Heart Study: Assessment of Wristwatch-Based 
Photoplethysmography to Identify Cardiac Arrhythmias 
 
Protocol Version:  
8.0  
 
Protocol Date:  
March 20, 2018  
   
I have read this Study Protocol and agree to adhere to the requirements of this current version 
of the protocol. 
  
I have not been restricted from participating in clinical research, nor is any action pending that 
could result in such restriction.  If this occurs, I shall provide immediate notification to the 
Sponsor. 
  
I, the undersigned, have read and understand the protocol specified above and agree on its 
content.  I agree to perform and conduct the study as described in the protocol and in 
accordance with applicable parts of 21 CFR Parts 50, 54, 56 and 812, and all governing IRB 
requirements. 
 
 
 

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required by applicable laws and regulations. The information in this document is the property of Apple Inc. and may not 
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4 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
TABLE OF CONTENTS 
PROTOCOL APPROVAL PAGE 
2 
INVESTIGATORS’ SIGNATURE PAGE 
3 
ACRONYMS 
5 
PROTOCOL SYNOPSIS 
6 
1.0 INTRODUCTION 
9 
2.0 STUDY OBJECTIVES 
13 
3.0 ENDPOINTS 
14 
4.0 STUDY DESIGN 
15 
5.0 STUDY POPULATION 
18 
6.0 STUDY DEVICE 
19 
7.0 STUDY PROCEDURES 
21 
8.0 STUDY OUTCOMES 
33 
9.0 ADVERSE EVENTS REPORTING 
34 
10.0 WITHDRAWAL 
38 
11.0 STATISTICAL CONSIDERATIONS 
39 
12.0 TRAINING 
44 
13.0 STEERING AND DATA MONITORING COMMITTEES 
44 
14.0 ETHICAL AND REGULATORY CONSIDERATIONS 
44 
15.0 HUMAN SUBJECTS PROTECTION 
45 
16.0 RECORD KEEPING/REPORTING 
46 
17.0 REFERENCES 
47 
 
 

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Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
ACRONYMS 
AF - Atrial Fibrillation or Atrial Flutter 
AHS - Apple Heart Study 
CFR - Code of Federal Regulations 
DSMB - Data and Safety Monitoring Board 
EAS - ECG Analysis Set 
ECG - Electrocardiography, Electrocardiogram, Electrocardiographic 
EMS - Emergency Medical Services 
EOS PRO - End Of Study PRO 
FAS - Full Analysis Set 
FDA - Food and Drug Administration 
HIPAA - Health Insurance Portability and Accountability Act  
HITRUST - Health Information Trust Alliance 
HR - Heart Rate 
IPNA - Irregular Pulse Notification Algorithm 
IRB - Institutional Review Board 
NAS - Notification Analysis Set 
NOC - Network Operating Center 
OAC - Oral anticoagulation 
OCG - Online Care Group 
PCI - Payment Card Industry 
PPG - Photoplethysmography, Photoplethysmogram  
PPV - Positive Predictive Value 
PRO - Patient Reported Outcomes 
SC - Steering Committee 
 
 
  
 
 

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6 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
PROTOCOL SYNOPSIS 
 
Study Title 
Apple Heart Study: Assessment of Wristwatch-Based 
Photoplethysmography to Identify Cardiac Arrhythmias 
Protocol Version 
8.0 
Protocol Date 
March 20, 2018 
Study Design 
Prospective, single arm, experimental, non-significant risk study. 
Inclusion Criteria 
1. Possession of the following at time of eligibility screening, 
ascertained from automatic hardware/software/device pairing 
check: 
I. iPhone (5s or later) with iOS version 11.0 or later defined 
as iPhone model/iOS version used to complete screening 
eligibility. 
II. Apple Watch (Series 1 or later) with watchOS version 4.0 
or later defined as Apple Watch model/watchOS paired 
with iPhone used to complete screening eligibility. 
2. Age ≥ 22 years at time of eligibility screening, ascertained from 
self-reported date of birth. 
3. Current resident of the United States at time of eligibility 
screening, defined by self-reported state of residence within the 
50 states of the United States or District of Columbia. 
4. Proficient in written and spoken English, defined by self-report of 
comfort reading, writing, and speaking English on iPhone. 
5. Valid phone number associated with iPhone, ascertained from 
self-report. 
6. Valid email address, ascertained from self-report. 
Exclusion Criteria 
1. Self-reported diagnosis of Atrial Fibrillation at the time of 
consent. 
2. Self-reported diagnosis of Atrial Flutter at the time of consent. 
3. Currently on anticoagulation therapy, as self-reported at the time 
of consent. 

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7 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
Study Objectives 
Objective 1a: To measure the proportion of participants aged ≥ 65 
with irregular pulse watch notifications who have demonstrable atrial 
fibrillation or flutter (AF) as confirmed by ambulatory 
electrocardiographic (ECG) patch monitoring. 
 
Objective 1b: To measure the proportion of all participants with 
irregular pulse watch notifications who have demonstrable atrial 
fibrillation or flutter (AF) as confirmed by ambulatory ECG patch 
monitoring. 
 
Objective 2: To characterize the concordance between pulse 
irregularity determined using spot tachograms (approximately one 
minute of beat-to-beat intervals) and AF detected by simultaneous 
ambulatory ECG patch monitoring. 
 
Objective 3: To estimate the rate of initial contact with a health care 
provider within 3 months after an irregular pulse watch notification. 
Co-Primary 
Endpoints 
1. AF of greater than 30 seconds duration detected on ambulatory 
ECG monitoring for a participant who received an irregular pulse 
watch notification.  
 
2. Simultaneous ambulatory ECG monitoring indicating an irregular 
rhythm consistent with AF during time intervals when the spot 
tachogram is positive for an irregular pulse among those who received 
a notification. 
Secondary 
Endpoints 
1. Simultaneous ambulatory ECG monitoring indicating an irregular 
rhythm consistent with AF when the Irregular Pulse Notification 
Algorithm (IPNA) based on multiple tachograms is positive for an 
irregular pulse among those who received a notification.   
  
2. Self-reported contact with a health care provider within 3 months 
following an irregular pulse watch notification.  
Test Device 
Apple Heart Study app 

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8 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
Duration of Study 
Participation  
Participants will have approximately 10 month-period to enroll. For 
each participant, the monitoring period will begin upon consent for 
that participant and end on September 1, 2018 (for those who never 
receive a notification) or on January 31, 2019 (for those who receive a 
notification). Every participant who receives a notification will 
receive an in-app Patient Reported Outcomes (PRO) survey within the 
app 90 days following the notification. All participants will receive a 
web-based End Of Study PRO (EOS PRO) survey that they will have 
until January 31, 2019, to complete. 
Number of 
Participants  
We anticipate total enrollment to be approximately 500,000 
participants. Ambulatory ECG monitoring is expected on 
approximately 500-5000 participants comprised of participants from 
two main subgroups (< 65 yrs, ≥ 65 yrs).   
 
 
 
 

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9 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
 
1.0 INTRODUCTION 
 
1.1 Background 
 
Impact of Undiagnosed Atrial Fibrillation 
 
Atrial fibrillation, the most common sustained cardiac arrhythmia with an estimated lifetime 
risk of one in four,1,2 accounts for 15% of the 700,000 strokes per year in the United States.3 
The prevalence of AF in the United States is estimated to be between 3 and 5 million4 and this 
number is expected to rise sharply due to an aging population and a rising age-adjusted 
incidence of AF. Oral anticoagulation (OAC) has been shown to substantially reduce the risk 
of AF associated stroke.5 However, 18% of AF-related strokes occur in patients with 
asymptomatic or subclinical AF that is newly-detected at the time of stroke.6 Asymptomatic 
and subclinical AF have been associated with similar morbidity and mortality rates as 
symptomatic AF,7 and with similar rates of silent embolic events.8 Moreover, untreated AF 
substantially increases the risk of the development of heart failure and other cardiac 
complications. Therefore, earlier detection of asymptomatic or subclinical AF could reduce the 
total public-health burden of ischemic stroke, heart failure, and other AF-related sequelae with 
upstream therapies. 
 
With an aging population in which AF prevalence is forecast to increase substantially,1 
effective AF screening strategies may have important public health implications.  
 
Guidelines for AF Screening 
 
Contemporary international guidelines on primary prevention of AF-related stroke, and general 
guidelines on AF management, recommend opportunistic pulse detection (pulse palpation by 
trained health care personnel during routine health care contact) in patients ≥ 65 years of 
age.9,10 Guideline statements recognize the demonstrated improvements to sensitivity for AF 
detection achieved through ambulatory ECG (both intermittent and continuous) monitoring. 
Professional society clinical guidelines and the U.S. Preventive Services Task Force have not 
yet recommended systematic screening for AF in general or high-risk populations.  
 
However, further studies are needed to clarify the effectiveness of screening (e.g., 
sensitivity/specificity, cost-effectiveness, subsequent health care utilization, and downstream 
impact on stroke incidence), before endorsing broader AF screening approaches utilizing 
contemporary technologies.  

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Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
 
Prevalence of Undiagnosed AF 
 
Prior work indicates a high rate of undiagnosed AF in the general population. In a back 
calculating modeling study based on incidence of AF shortly following ischemic stroke in 
Medicare and commercial claims beneficiaries, there are an estimated 500,000 persons with 
undiagnosed AF in the United States, with an estimated incremental cost burden of $3.2 
billion.11 
 
In a study of patients with no AF by history, AF was identified in 10 of 767 (1.3%) participants 
on baseline electrocardiogram (ECG). Intermittent ECG monitoring over a 2-week period 
(Zenicor ECG, Zenicor Medical Systems, Stockholm, Sweden), identified an additional 20 of 
403 (5.0%) participants with previously undiagnosed AF.7 Similarly, the SEARCH-AF study 
screened 1,000 patients with a 30-second single vector ECG rhythm strip coupled to a 
smartphone device (AliveCor Kardia Mobile, AliveCor, Inc., Ashmore, Australia).12 In this 
population (mean age 76 years; 44% male), newly-identified AF was found in 1.5% of 
participants. Recently, results have been published from the STROKE-STOP study, a large 
randomized control trial of systematic AF screening of individuals in Sweden who were 75 to 
76 years of age.13 Patients were advised to assess their heart rhythm twice a day or during 
symptoms such as palpitations, with a handheld heart rate monitor (Zenicor ECG, Zenicor 
Medical Systems, Stockholm, Sweden). In the 14,487 patients enrolled, 12.3% were found to 
have AF, 3.0% were found to have previously unknown AF, and 5.1% of the screened 
population had AF and were not receiving adequate stroke prevention therapy. Screening 
resulted in the initiation of OAC in 3.7% of the screened population, demonstrating that 
screening can lead to AF treatment both in patients with newly-diagnosed as well as prevalent 
AF. 
 
However, given the paroxysmal and asymptomatic nature of AF, brief intermittent screening 
strategies are highly insensitive and likely to only capture patients with high AF burdens. This 
issue is highlighted by a recent retrospective study that showed in patients diagnosed with AF 
after stroke, using a 14-day ambulatory ECG monitor, the median AF burden was 0.33 hours.14 
Similarly, the investigation of prolonged ambulatory ECG screening (30 days) for AF after 
stroke, as compared to conventional 24-hour Holter monitors, detected 5-fold more AF (16.1% 
vs. 3.2%).15 With improvements in AF detection algorithms, long-term implantable loop 
recorders are being increasingly used to screen for occult AF. However, the benefits of long-
term screening with this modality come with the downsides of an invasive procedure. 
 
Wearable Health Technologies  
 
Recently, there has been substantial uptake, both from consumers and patients, of wearable 
health technology such as wrist-worn devices incorporating multiple sensors. Such 

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11 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
technologies can generate large amounts of real-time data on patient activity and heart rate 
variability, often through photoplethysmography (PPG) based measurements of capillary blood 
volume. As technologies advance and adoption increases, wearable health technologies will be 
able to deliver increasingly more complex information on patient health. To date, efficient 
utilization of these data sources to effect improvement in traditional patient outcomes has been 
limited. For decades, cardiac implanted electronic devices (e.g., pacemakers and implantable 
cardioverter defibrillators) have collected and transmitted real time patient data, ranging from 
measures of patient activity to life-threatening arrhythmia notifications. These systems have 
been shown to improve clinical outcomes (e.g., time to clinical decision and mortality) and 
serve as proof of concept for wearable health technology based patient monitoring. However, 
further investment and study is needed to develop and define wearable health technologies’ 
health care applications.  
 
App Based Health Care Research  
 
Traditional approaches to prospective health care investigation are limited by high start-up 
costs and large infrastructure requirements. Utilization of apps in health care research can 
streamline patient consent, data collection, and distribution of health care interventions (e.g., 
medical information, medication reminders, etc.).  App-based research also enables enrollment 
of a broader population.  ResearchKit, an open source framework to conduct medical research, 
developed by Apple, has been effectively used to operationalize large prospective 
observational studies. MyHeart Counts, a Stanford led app-based investigation of 
cardiovascular health and patient activity, demonstrated impressive enrollment metrics, with 
50,000 participants enrolled within the first year of launch. Altogether, app based health care 
research can decrease the barriers to, and costs of, performing large studies quickly. 
   
Apple Watch Irregular Pulse Notification Algorithm (IPNA) 
 
Using observable variations in PPG signal intensity, changes in blood flow can be measured 
and beat-to-beat pulse measurements can be made. During normal sinus rhythm, there is 
minimal variation in pulse. However, during AF, the beat-to-beat variability increases 
significantly. Therefore, a PPG signal can be used to differentiate between a regular pulse and 
an irregular pulse that may be indicative of AF. 
 
An algorithm has been developed by Apple to identify periods of irregular pulse based on PPG 
signal variation as measured by the Irregular Pulse Notification Algorithm (IPNA). The time 
between PPG signal peaks observed during periods of minimal arm movement are marked as 
intervals between heart beats. A tachogram is a period of time over which heart beat intervals 
are measured. The degree of beat-to-beat variability is measured from spot tachograms over the 
course of approximately one minute intervals. An irregular tachogram is flagged when the 
variability, measured using a Poincare plot, crosses a predefined threshold. An IPNA checks 

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12 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
multiple tachograms over a period of approximately an hour or more. A notification is then 
sent to the user when a period of an irregular pulse consistent with AF has been identified.  
 
 
1.2 Study Rationale 
  
Leveraging existing wearable technology paired with a novel app-based health algorithm that 
analyzes heart rate irregularity consistent with AF has the potential to scale opportunistic AF 
screening strategies across large populations. 
 
In recent years, wearable technology has rapidly diffused into consumer markets and provides 
unique opportunities to engage individuals on health issues of personal interest, and to collect 
personal health data. One example of such technology are PPG sensors that can measure heart 
rate and heart rate variability for exercise and training purposes. However, utilization of this 
data source to improve patient outcomes has not been fully realized in the health care field. An 
app-based heart irregularity algorithm that identifies possible AF from collected PPG data and 
then notifies the user of such potential irregularities could lead to widespread screening and 
subsequent early AF detection and oral anticoagulation initiation, ultimately resulting in 
reductions in stroke incidence. 
 
 
 
 

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13 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
2.0 STUDY OBJECTIVES 
 
2.1 Research Question 
 
The overarching objective is to evaluate the ability of the IPNA to identify AF and guide 
subsequent clinical evaluation. 
 
 
2.2 Study Objectives  
 
Objective 1a: To measure the proportion of participants aged ≥ 65 with irregular pulse watch 
notifications who have demonstrable AF as confirmed by ambulatory ECG patch monitoring. 
 
Objective 1b: To measure the proportion of all participants with irregular pulse watch 
notifications who have demonstrable AF as confirmed by ambulatory ECG patch monitoring. 
 
Objective 2: To characterize the concordance between pulse irregularity determined using spot 
tachograms and AF detected by simultaneous ambulatory ECG patch monitoring.  
 
Objective 3:  To estimate the rate of initial contact with a health care provider within 3 months 
after an irregular pulse watch notification. 
 
 
 
 

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14 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
3.0 ENDPOINTS 
 
3.1 Co-Primary Endpoints 
 
1. Atrial fibrillation or atrial flutter (AF) of greater than 30 seconds duration detected on 
ambulatory ECG monitoring for a participant who received an irregular pulse watch 
notification. 
 
2. Simultaneous ambulatory ECG monitoring indicating an irregular rhythm consistent 
with AF during time intervals when the spot tachogram is positive for an irregular pulse 
among those who received a notification. This endpoint will be evaluated during time 
intervals when the watch provides tachogram data. Thus, each participant contributes 
multiple observations for this endpoint. 
  
 
3.2 Secondary Endpoints 
 
1. Simultaneous ambulatory ECG monitoring indicating an irregular rhythm consistent 
with AF when the IPNA based on multiple tachograms is positive for an irregular pulse 
among those who received a notification.  
 
2. Self-reported contact with a health care provider within 3 months following an irregular 
pulse watch notification. 
 
 
3.3 Tertiary Endpoints 
 
1. Arrhythmias, other than AF, detected on an ambulatory ECG monitor that can also 
result in an irregular pulse. These include sinus arrhythmia, frequent premature atrial 
contractions, frequent premature ventricular contractions, intermittent heart block, 
multifocal atrial tachycardia, and atrial tachycardia with variable conduction. 
 
2. AF of greater than 6 minutes, 1 hour, 6 hours, and 24 hours duration detected on an 
ambulatory ECG monitor following an irregular pulse watch notification. 
 
3. Self-reported initiation of therapies for AF, including anticoagulant, rate-controlling 
and antiarrhythmic therapy. 
 
4. Self-reported electrical or chemical cardioversion by a health care provider. 

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15 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
4.0 STUDY DESIGN 
4.1 Overall Study Design 
Scope 
This will be a prospective, single arm, experimental non-significant risk study, conducted with 
the assistance of eligible participants without a known history of atrial fibrillation or atrial 
flutter.  
Participants who download the Apple Heart Study app and meet the eligibility criteria will 
enroll on a metered basis, whereby a maximum number of participants will be allowed to 
enroll, and then proceed to consent. Enrollment will initially be weighted heavily towards 
participants who are at least 65 years of age. Those who are not enrolled immediately will be 
placed in a “waiting period”, and notified via a notification in the Apple Heart Study app when 
their opportunity to enroll is available. Participants will be required to provide signed informed 
consent; once enrolled they will complete a short questionnaire to collect demographic 
information and medical history, after which the monitoring period will commence. 
Monitoring 
During the monitoring period, upon the detection of a series of irregular tachograms, and based 
on the IPNA, the Apple Heart Study app will notify the participant that an irregular rhythm was 
identified.  When notified of a pulse irregularity, participants will be asked to contact the 
telemedicine technology services company, American Well Corporation (together with Online 
Care Group, the “Study Telehealth Provider”) administered within the app that will manage the 
participant’s study follow-up throughout study participation.  Following the first notification, 
the participant will be reminded daily to contact the Study Telehealth Provider via the app. 
This reminder will be repeated each day until the participant contacts the Study Telehealth 
Provider, for a maximum period of 14 days. The first contact made by the participant to the 
Study Telehealth Provider will constitute Study Visit #1. After 14 days from the initial 
notification, no further reminders will be sent by the app. The participant will become part of 
the fall-out subgroup if they do not contact the Study Telehealth Provider and complete Study 
Visit #1 within 30 days of receiving the first notification. These participants in the fall-out 
subgroup who call after 30 days will still be able to initiate Visit #1 with the Study Telehealth 
Provider and undergo remaining study procedures.  
During Study Visit #1 (voice/video), participants will undergo a virtual medical evaluation 
including an assessment for symptoms, medical history, and medication use. Participants with 
urgent symptoms (chest pain, shortness of breath, fainting/losing consciousness) will be 

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Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
directed to an urgent care clinic or emergency room for medical evaluation. Such participants 
who are directed to either emergency care or urgent care will also be included in the fall-out 
subgroup. 
 
Participants without urgent symptoms who received a notification and who confirm that they 
are not currently on an anticoagulant therapy or are on an anticoagulant therapy that started 
after enrollment in the study will then be offered an ambulatory ECG monitor (ePatch, 
BioTelemetry, Inc., Conshohocken, PA). The participants will be mailed the ambulatory ECG 
monitor, which the participant will then be requested to wear for up to 7 days. The minimum 
analyzable time acceptable for analysis is one hour. The participant will then mail the 
ambulatory ECG monitor back to BioTelemetry, which will generate a standard technical 
report that will be read by BioTelemetry’s technical readers. This report will then be finally 
adjudicated by board certified clinicians in a double-adjudication fashion, and a final report 
will be made available to the Study Telehealth Provider by BioTelemetry. 
 
A second follow-up visit (telephone/video), Study Visit #2, will occur with the Study 
Telehealth Provider once the ambulatory ECG monitor results are available.  If AF or any other 
arrhythmias have been detected in reviewing the ambulatory ECG monitor data, or if there are 
other non-urgent symptoms needing further evaluation, the Study Telehealth Provider will 
direct the participant to their primary health care provider, or other health care provider as 
deemed appropriate by the Study Telehealth Provider.  The report and visit summary will be 
made available to the participant and also to participant’s physician or health care provider, if 
during Study Visit #1, the participant provides his/her physician information and permission to 
send that physician a copy of the report.  For participants who do not have an established 
primary health care provider, the Study Telehealth Provider will encourage and offer advice in 
establishing a primary care provider per standard Study Telehealth Provider protocol. 
 
Patient Reported Outcomes (PROs) 
 
90 days after the irregular pulse notification, only those participants who received an irregular 
pulse notification will receive a separate app notification to complete the patient reported 
outcomes (PRO) questionnaire within the app. These outcomes will include whether or not the 
participant contacted a primary health care provider and what additional treatments or 
diagnostic tests they underwent. They will also be asked questions related to measures of 
anxiety related to the notification.  Participants will receive reminders via notifications from 
the app to complete the 90-day PROs prior to the due date. 
 
All enrolled participants, regardless of whether or not they received an irregular pulse 
notification, will receive an End Of Study (EOS) PRO questionnaire towards the end of the 
study. Those who do not receive a notification will receive the EOS PRO on September 1, 
2018. Those who do receive a notification will receive the EOS PRO on January 2, 2019.This 

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17 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
questionnaire will be administered through a website, and participants will have until the end 
of study to complete. Participants will receive reminders via notifications from the app to 
complete the EOS PROs prior to the due date. This questionnaire will include questions on 
whether or not they were diagnosed with AF, started an anticoagulant medication, had any new 
symptoms during the monitoring period including palpitations, dizziness, fatigue, or had any 
major gastrointestinal or cerebrovascular bleeding. For those who indicated a new diagnosis of 
AF, further questions regarding additional treatments or diagnostic tests will be asked. 
 
 
 
 
4.2 Rationale for Study Design 
 
The study aims to estimate how frequently AF is diagnosed on the basis of a confirmatory 
ambulatory ECG monitoring in participants who receive an irregular pulse notification, and to 
validate the concordance of the spot tachograms and the IPNA algorithm with cardiac 
arrhythmias detected by simultaneous ambulatory ECG monitoring. To reach the required 
number of participants who receive a clinical diagnosis and undergo simultaneous ambulatory 
ECG patch monitoring, a large number of participants will need to be enrolled, given the 
relatively low rate of undiagnosed AF in our target population. 
 
 
 

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18 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
5.0 STUDY POPULATION 
5.1 Inclusion Criteria 
1. Possession of the following at time of eligibility screening, ascertained from automatic
hardware/software/device pairing check:
I.
iPhone (5s or later) with iOS version 11.0 or later defined as iPhone model/iOS
version used to complete screening eligibility.
II. Apple Watch (Series 1 or later) with watchOS version 4.0 or later defined as Apple
Watch model/watchOS paired with iPhone used to complete screening eligibility.
2. Age ≥ 22 years at time of eligibility screening, ascertained from self-reported date of birth.
3. Current resident of the United States at time of eligibility screening, defined by self-
reported state of residence within the 50 states of the United States or District of Columbia.
4. Proficient in written and spoken English, defined by self-report of comfort reading, writing,
and speaking English on iPhone.
5. Valid phone number associated with iPhone, ascertained from self-report.
6. Valid email address, ascertained from self-report.
5.2 Exclusion Criteria 
1. Self-reported diagnosis of Atrial Fibrillation at the time of consent.
2. Self-reported diagnosis of Atrial Flutter at the time of consent.
3. Currently on anticoagulation therapy, as self-reported at the time of consent.

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19 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
6.0 STUDY DEVICE 
Device Name: Apple Heart Study app 
The Apple Heart Study app is a mobile medical app that analyzes pulse rate data.  The app 
identifies episodes of irregular heart rhythms consistent with atrial fibrillation and other 
arrhythmias. 
Device Description:  
The Apple Heart Study app is an application that analyzes heart rate (HR) and beat-to-beat data 
captured by the Apple Watch photoplethysmogram (PPG) sensor.  The Apple Heart Study app 
uses this data to identify irregular heart rhythms consistent with atrial fibrillation and other 
arrhythmias.  Analysis is initiated when the Apple Heart Study app successfully retrieves 
approximately one minute of beat-to-beat intervals, defined as a tachogram, derived from the 
Apple Watch PPG HR sensor through HealthKit, a data repository on a user’s iPhone.  
In practice, tachograms are collected and stored at selected times throughout the day when a 
user appears to be still enough for a successful reading to be taken.  If, and when, the Apple 
Heart Study app retrieves a tachogram and subsequently classifies it as “irregular”, it shifts into 
a “confirmation mode” and begins requesting, and analyzing, tachograms on a more frequent 
basis until it is able to confirm sustained irregularities or the confirmation cycle is otherwise 
ended. 
Upon completion of a positive confirmation cycle within a 48-hour period, the Apple Heart 
Study app provides a notification to the user on their Apple Watch and subsequently on their 
iPhone app. 
While the app is able to identify irregular heart rhythms consistent with atrial fibrillation and 
other arrhythmias, the app is not intended to diagnose atrial fibrillation, and any irregular 
readings or subsequent notifications displayed by the app should be confirmed by ECG and/or 
by a clinician.  The app is not intended to be used on an on-demand basis and should not be 
used to guide medical therapy decisions. 
The Apple Heart Study app is not intended as an implant but rather is stand-alone software that 
runs on general purpose platforms (the Apple iPhone and Apple Watch).  The Apple Heart 
Study app is also not claimed or otherwise represented to be for a use in supporting or 
sustaining human life.  The Apple Heart Study app is further not intended for use in 
diagnosing, curing, mitigating or treating disease, as the app is not an atrial fibrillation 
diagnostic device and should not be used to guide medical therapy decisions.  Finally, the 
Apple Heart Study app does not present a potential for serious risk to the health, safety, or 
welfare of a participant as the app only serves as a method to detect irregular heart rhythms and 

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20 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
notify users of sustained pulse irregularities that must ultimately be confirmed by an ECG 
and/or a clinician. 
 
 
 
 

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21 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
7.0 STUDY PROCEDURES 
 
 
 
Figure 1. Study Timeline 
 
7.1 Eligibility Determination and Enrollment 
 
The potential participant will first download the Apple Heart Study app. The app will 
automatically ensure compatibility with the iPhone iOS version and Watch version. If 
compatible, the participant will be able to continue forward in the app. An overview of the 
study will be displayed in the app. 
 
The participant will then advance to a screen for study enrollment, where they will confirm 
whether they meet general participation requirements. The participant will be asked questions 
based on study inclusion and exclusion criteria. The app will automatically determine 
eligibility based on the responses provided. If the participant is determined to be eligible, they 
may continue to the “waiting period”, based on the enrollment metering schema and study 
infrastructure capacity, until it is time for them to consent and enroll. The waiting period for 
each participant will end once they are able to enroll based on the enrollment metering schema 
and study infrastructure capacity. After the waiting period, before the potential participant can 
initiate the consenting process, the participants will be asked to re-confirm their eligibility. 
Upon responding, they will be presented with an in-app consent and authorization form to be 
read and signed if they agree to participate.  
 
The study anticipates a very large volume of participants to be screened and consented in the 
initial days following study opening. There is a potential risk of overwhelming the study 
infrastructure if all participants are allowed to enter the study monitoring phase instantly.  
 
To maintain operational efficiency, the study will use an enrollment metering schema, whereby 
participants who are eligible for inclusion may be delayed in consent and enrollment (baseline 
characterization, and initiation into the monitoring portion of the study). Participant safety will 
be monitored through interim checks (see Section 11.5 below). 
 

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22 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
Enrollment metering will be adaptable based on study and clinical bandwidths, with metering 
instituted by invitation to consent. Once consent is obtained, enrollment and initiation of 
monitoring for pulse irregularity will commence. Initial enrollment will be heavily weighted 
towards enrollment of a population more likely to be at risk for undiagnosed AF, such as those 
over age 65 years. 
 
Pre-planned enrollment metering strategy will include two enrollment waves: 
  
1. Wave 1: Weighted enrollment  
 
During the first two weeks that the study is open, approximately 1000 new participants 
aged > 65 years will be enrolled per week, and approximately 700 participants aged 22-
64 years will be enrolled per week.   
 
2. Wave 2: Open enrollment 
 
Two weeks after the start of Wave 1, enrollment metering of all eligible participants 
will be based on notification rates and as study infrastructure allows. 
 
 
7.1.1. Expected Enrollment and Study Participant Timeline 
 
 
 
Figure 2. Participant Level Flow Chart 
 
We expect to reach our full enrollment target within the first nine months following study 
opening on November 29, 2017. Participants will be able to enroll between November 29, 
2017, and August 1, 2018.   
 

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23 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
On August 1, 2018, enrollment will close. On September 1, 2018, no further irregular pulse 
notifications will be sent. Monitoring will end on September 1, 2018 in participants who never 
received a notification, and the EOS PRO will become available to this group. 
Participants who receive a notification of an irregular pulse from their app will continue to be 
monitored until the end of study for the purpose of data collection for the concordant Apple 
Watch and ECG patch monitoring analyses. A 90-day PRO will become available 90 days after 
notification, no later than December 1, 2018.  The EOS PRO will become available to the 
notification subgroup on January 2, 2019.  
All PROs will be due by end of study on January 31, 2019. After this date, all monitoring will 
end, the American Well line will be closed and no further data will be collected. 
7.2 Enrollment: Consent, Baseline Demographics and Medical History Collection 
The Apple Heart Study (AHS) is an app-based research study utilizing the ResearchKit open 
source framework on the iOS platform. As in other mobile-mediated research studies, the 
informed consent process in the AHS is conducted remotely in a completely self-administered 
setting with no required contact with the research team prior to consent and enrollment. 
The approach to informed consent for the AHS has been adapted accordingly to ensure the 
ethical requirement of informedness, i.e. that participants are adequately informed about the 
research before participation, is met.  Potential candidates as well as enrolled participants will 
be able to contact an AHS hotline (available 24/7 at 1-844-606-1609) anytime and have the 
ability to ask questions and request clarifications at any time prior to or during the study.  This 
hotline will be open from the study start date until study closure.  
Participants who successfully pass the eligibility criteria will be directed to a page requesting 
their consent to participate. Participants will be asked to read and sign the study informed 
consent and authorization document within the app if they agree and are willing to participate.  
A copy of the signed study consent and authorization document will be available for review 
and download to the participant via the app.  The participant will be considered ‘enrolled’ from 
this point and the study app monitoring of Apple Watch PPG sensor data will begin thereafter. 
After consenting to participate, the participant will be directed to complete a brief 
questionnaire to collect self-reported baseline demographics and medical history.  

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24 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
7.3 Overall Procedures for Enrolled Participants: Monitoring Initiation and Patient 
Reported Outcomes 
 
After completing the baseline demographics and medical history questionnaires within the app, 
the participant will wear their Apple Watch as per normal usage with the IPNA analyzing 
intermittent passively collected PPG pulse data, with two possible outcomes:   
 
1. No pulse irregularities that meet the IPNA notification threshold are identified from the 
time monitoring begins (after consenting) to September 1, 2018. 
 
or; 
 
2. Pulse irregularities are identified by the IPNA that meet notification threshold during 
the study. The participant is then notified via the app of this irregularity. Participants 
who receive a notification during the study will enter the positive notification workflow 
[see 7.4.1 Monitoring Workflow - Positive Notification]. 
 
All study participants who do not actively withdraw, and who do not receive an irregular pulse 
notification, will be invited to complete a web-based EOS PRO survey on September 1, 2018 
and participants can complete this survey any time before January 31, 2019 [see 7.5 PRO 
Instruments]. 
 
7.4 Monitoring Flow 
 
7.4.1 Monitoring Flow - Positive Notification 
 
After the participant receives a pulse irregularity notification within the Apple Heart Study 
App: 
 
1. The app notification will provide a button for the participant to connect with the Study 
Telehealth Provider. Participant will be instructed to contact the Study Telehealth 
Provider and be informed that they will receive no further irregular pulse 
notifications, even if pulse irregularity that meets IPNA notification threshold occurs at 
any time point until the study end.  
 
2. If the participant does not connect with the Study Telehealth Provider within 24 hours 
of receiving the original notification, the participant will continue to receive in-app 
reminder notifications daily for 14 consecutive days following the initial notification. 
The reminder will include an alert indicating a possible irregular pulse and that they 
should connect with the Study Telehealth Provider.  The first connection with the Study 

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25 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
Telehealth Provider will constitute Study Visit #1 [see 7.4.2 Study Telehealth Provider 
Service Workflow]. 
 
3. If no connection is made with the Study Telehealth Provider within 30 days, participant 
will be placed in a fall-out subgroup. After 14 days, the app on participant’s phone will 
send no further reminder notifications or irregular pulse notifications. Those in the fall-
out subgroup will receive the positive-notification PRO survey at 90 days following 
initial notification and EOS PRO on January 2, 2019.  
 
The study team may contact participants who receive the irregular pulse notification in order to 
remind participants to connect with the Study Telehealth Provider. 
 
 
 
 
7.4.2 Study Telehealth Provider Service Workflow 
 
American Well (Boston, MA) is a healthcare technology company that developed the 
telehealth platform being used to support study visits. The American Well technology supports 
mobile-based interactions between patients and providers during the study, in which both the 
participant and provider can see and hear each other through American Well’s proprietary 
videoconferencing capabilities. Virtual visits can be conducted using a wireless or network 
connection, meaning a study participant can initiate a visit from anywhere. American Well’s 
platforms are a SaaS (Software as a Service) offering—this means all operational hardware and 
support software is housed and maintained within American Well data centers and is serviced 
by the American Well Hosting Operations department. American Well is a PCI- and HIPAA-
compliant, HITRUST-certified, federally recognized security platform. 
  
The Online Care Group (OCG) is American Well’s clinical partner.  OCG providers are 
responsible for conducting the study required assessments at visit #1 and #2.  All OCG 
physicians are licensed, board certified, and have 10-15 years of experience in a brick-and-
mortar practice, and have undergone a vigorous training on American Well’s platform.  
Additionally, the OCG has an internal credentialing process that meets all standards as dictated 
by the National Committee for Quality Assurance. The Online Care Group’s staff physician-
led credentialing committee (comprised of a chief medical officer, staff physician, and director 
of behavioral health) reviews and approves all practitioners before they are permitted to 
practice on the American Well System.  
 
Study Telehealth Provider Team, a term used throughout this protocol, relates to physicians 
from the OCG, Level 1 agents operating the 24-hour hotline and the Network Operating Center 
(NOC) staff who coordinates efforts to initiate shipment of the ambulatory ECG monitoring 

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26 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
patch and facilitates the communication of patch report results and clinical summaries to the 
participant. All these groups provide services through American Well platform. 
 
After the participant connects with the Study Telehealth Provider team, they will undergo: 
 
1. Study Visit #1:  
 
The participant will be asked about cardiovascular clinical signs and symptoms. If the 
Study Telehealth Provider concludes that the participant has a medical emergency, the 
Study Telehealth Provider will follow its emergency protocol and either instruct the 
participant and/or a family member, if available, to call emergency medical services 
(EMS) or will call on the participant’s behalf if the participant and/or a family member 
are unable to contact EMS. Those with emergent symptoms will be moved to the fall-
out subgroup and still receive a positive-notification PRO survey at 90 days. These 
participants will not receive the ambulatory ECG monitors. 
 
Once emergency symptoms have been ruled out, the telehealth clinician will perform a 
standard review of medical history, confirm that the subject is not on anticoagulant 
therapy or is on anticoagulant therapy that started after enrollment in the study, and 
perform a virtual review of physical symptoms. The information obtained will assure 
that the Study Telehealth Provider Data Collection variables [see 7.4.3 Study 
Telehealth Provider Data Collection] are obtained. The Study Telehealth Provider will 
provide the participant information about the ePatch to those who have confirmed that 
they are not on anticoagulant therapy or are on anticoagulant therapy that started after 
enrollment in the study, answer any questions the participant might have and contact 
BioTelemetry to initiate the order and shipment of the ambulatory ECG monitor 
(ePatch). After the ambulatory ECG monitor has been worn by the participant for up to 
7 days and returned back to BioTelemetry, BioTelemetry will perform data extraction 
and an initial interpretation of the ambulatory ECG findings by trained ECG 
technicians. The ECG technician review will determine if the participant has any 
serious or potentially life-threatening abnormality. Although extremely rare, this 
includes sustained ventricular tachycardia or ventricular fibrillation, high-degree heart 
block, and long pauses. If one of these life-threatening arrhythmias is identified, then 
the participant will be contacted and directed to local emergency care or advised how to 
seek local emergency care. Best attempt will be made to send the ECG report to 
participant’s emergency care provider.  
 
After confirmation that a participant’s ambulatory ECG data does not have any of these 
life-threatening arrhythmias, the ambulatory ECG study will be processed into the 
adjudication workflow. The adjudication workflow is described in a separate charter.  
  

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27 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
The adjudication process will result in generation of a final adjudicated report. Once the 
adjudicated report is complete, it will be issued to the Study Telehealth Provider.  
When the Study Telehealth Provider receives this final adjudicated report from 
BioTelemetry, the participant will be notified by way of a secure email that their patch 
report is ready and will be instructed to contact the Study Telehealth Provider to 
conduct Study Visit #2.  
 
2. Study Visit #2:  
 
The Study Telehealth Provider will review the ambulatory ECG monitoring report with 
the participant and make any necessary recommendations to the participant.  The Study 
Telehealth Provider will then refer participants with AF, any clinically relevant cardiac 
arrhythmias, or any non-urgent symptoms requiring follow up detected on patch 
monitoring to their primary health care provider for further treatment and diagnostic 
testing. For participants without established primary health care providers, the Study 
Telehealth Provider will offer referral per standard Study Telehealth Provider protocols. 
The ambulatory ECG monitoring report and visit summary will be made available to 
the participant and also to participant’s physician or health care provider, if the 
participant provides the Study Telehealth Provider information of participant’s 
physician and permission to send that physician a copy of the report. Any referral visits 
will be conducted outside of the study, at the discretion of the participant, and at the 
cost of the participant. 
 
The research team may contact participants to ensure that participants complete all study-
related visits and procedures or for other purposes as deemed necessary by the investigators. 
 
 
7.4.3 Study Telehealth Provider Data Collection 
 
Study Visit #1:  
 
The following data elements will be collected during visit intake or during the visit: 
 
1. Demographics 
2. Past medical history 
3. Medications 
4. Symptoms 
5. Clinical assessment 
6. Complaints 
 
Study Visit #2:  

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28 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
 
The following data elements will be collected:   
 
1. Symptoms during ECG monitoring period 
2. Actions taken by participant since initial visit 
3. Clinical assessment 
4. Complaints 
 
7.4.4 BioTelemetry ePatch Monitoring 
 
 
 
The BioTelemetry ePatch Monitor will be used for ambulatory ECG monitoring. The battery 
life with a single channel recording is 7 days. The participant will be instructed to wear the 
ePatch for up to 7 days. However, the data collected from a participant will be considered 
adequate for a participant with a minimum analyzable time of 1 hour.  
 
BioTelemetry will send participants, via courier, an ambulatory ECG monitoring kit containing 
one sensor and two adhesive patches. If the adhesive patch is no longer functional, the sensor 
can be moved to the backup adhesive patch. At the end of the recording period, the participant 
will be required to mail the monitor back to BioTelemetry using the supplied prepaid mailer. 
 
Study Visit #1: 
 
During Study Visit #1, participants will receive brief instructions on ePatch, get any of their 
questions on ePatch answered and be notified that an ePatch will be mailed to them within 
approximately 5 days.  
 
In the event it is discovered that the participant never received the ePatch due to a shipping 
error or became lost in transit, then BioTelemetry will issue a second ePatch to that participant. 
Any subsequent loss of ePatches will not be replaced. 
 
After Initial Visit: 

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29 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
 
Approximately 14-20 days after the Visit #1 it is expected that most participants will have 
completed wearing the patch for up to 7 days and will have returned the patch to BioTelemetry 
via a provided tracked USPS mailer.  The ambulatory ECG monitor should be received by 
BioTelemetry within 45 days from the date of Study Visit #1. Those who return patches 
beyond 45 days will be included in the fall-out subgroup, however they will still be eligible for 
a follow-up visit with the Study Telehealth Provider. Those who never return ePatch will also 
be placed in the fall-out subgroup. 
 
Study Visit #2:  
 
Once the ePatch has been received by BioTelemetry and the final report has been adjudicated, 
BioTelemetry will issue a notification to the Study Telehealth Provider. The Study Telehealth 
Provider will notify the participant by way of a secure email that their patch report is ready and 
will be instructed to contact the Study Telehealth Provider for Study Visit #2. This visit will 
occur approximately 60 days following Visit #1, but will vary depending on the time it takes 
the participant to wear and return the ePatch. During this visit, results of ambulatory ECG 
monitoring will be reviewed and further clinical care options will be discussed. The report and 
visit summary will be made available to the participant and also to participant’s physician or 
health care provider, if the participant provides the Study Telehealth Provider information of 
participant’s physician and permission to send that physician a copy of the report.  
 
 
7.5 PRO Instruments 
 
7.5.1 90-Day PRO 
 
Participants who receive an irregular pulse notification will be notified by alert via the Apple 
Heart Study app to complete the 90-day PRO questionnaire at 90 days following their irregular 
pulse notification. The questionnaire will be administered through the Apple Heart Study app, 
and the participant will have until January 31, 2019, to complete it. Participants will receive 
reminders via notifications from the app to complete the EOS PROs prior to the due date. 
Questions will ask if the participant followed up with the Study Telehealth Provider and/or a 
non-study health care provider, received an AF diagnosis, was evaluated in-person by a non-
study health care provider, the type of non-study health care provider and/or specialists, 
received additional cardiac testing, received other clinical arrhythmia diagnoses, and whether 
the participant experienced any anxiety as a result of participation. 
 
7.5.2 End of Study (EOS) PRO 
 

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30 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
For those who do not receive an irregular pulse notification, the End of Study (EOS) PRO will 
become available to complete on September 1, 2018.  All enrolled participants who received an 
irregular pulse notification during the monitoring period, prior to September 1, 2018, will be 
notified instead on January 2, 2019 to complete the EOS PRO questionnaire.  The EOS PRO 
will be available via a link in the app to a website where the EOS PRO questionnaire will be 
administered. Participants will have up until January 31, 2019, to complete this questionnaire. 
Participants will receive reminders via notifications from the app to complete the EOS PROs 
prior to the due date.  Questions will cover whether, during the study period, the participant 
received a diagnosis of AF, they received treatment for their AF, and whether the participant 
experienced any anxiety as a result of participation. 
 

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31 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
7.6 Time and Events Schedule  
 
 
 
Evaluation 
 
Screening 
and 
Eligibility 
 
Consent 
and 
Enrollment 
Study Visit 
#1 
 (< 30 days 
after 
notification) 
Study Visit 
#2 
~60 days 
after Visit 
#1 
90 Day  
PRO 
End of 
Study 
PRO 
All Participants 
Inclusion/ 
Exclusion Criteria 
X 
 
 
 
 
 
Informed Consent 
X 
X 
 
 
 
 
Demographics/ 
Medical History 
 
X 
 
 
 
 
Survey 
Completion 
 
 
 
 
 
X 
Notification Subgroup 
Virtual Review of 
Medical History / 
Physical 
Symptoms 
 
 
X 
 
 
 
Ambulatory ECG 
Monitor - 
Introduction/ 
Shipment 
 
 
X 
 
 
 
Ambulatory ECG 
Monitor - Results 
Review 
 
 
 
X 
 
 
Arrhythmia 
Recommendations 
for PCP referral 
 
 
 
X 
 
 
Survey 
Completion 
 
 
 
 
X 
 
 
 
 
 

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32 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
7.7 Fall-out Subgroup 
 
The fall-out subgroup will include participants who received a notification, but provide 
incomplete data for various reasons. The reasons may include: 
 
1. Failure to call Study Telehealth Provider within 30 days after notification. 
 
2. Urgent symptoms discovered during Study Visit #1 virtual medical evaluation by Study 
Telehealth Provider requiring immediate direction to EMS (urgent care clinic or 
emergency room) for medical care. 
 
3. Failure to return an ePatch within 45 Days after Visit #1. 
 
 
 

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33 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
8.0 STUDY OUTCOMES 
 
1. Atrial fibrillation > 30 seconds ascertained by ambulatory ECG monitoring, 
 
2. Concordant AF (any duration) detected simultaneously by spot tachogram from PPG 
based pulse irregularities and ambulatory ECG monitor.  
 
3. Concordant AF (any duration) detected simultaneously by positive IPNA from PPG 
based pulse irregularities and ambulatory ECG monitor.  
 
4. Self-reported participant contact with health care provider within 3 months after 
irregular pulse notification. 
 
5. Patient reported outcomes (PRO) collected: 
 
1. 90 days after notification of pulse irregularity, and/or 
2. At the end of study (EOS). 
 
 
 
 
 

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34 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
9.0 ADVERSE  EVENTS REPORTING 
 
All suspected adverse events (AEs) will be reported to the Study Safety Monitoring Desk by 
the Study Telehealth Provider Team. The Study Safety Monitoring Desk will review suspected 
AEs and determine whether they are adverse device effects (ADEs). 
 
9.1 Definitions and Classification 
 
Term 
Definition 
Reference 
Adverse Event 
(AE) 
Any untoward medical occurrence, unintended 
disease or injury, or untoward clinical signs 
(including abnormal laboratory findings) in 
participants, users or other persons, whether or not 
related to the investigational device. 
ISO 14155-1 
Adverse Device 
Effect (ADE) 
Adverse event related to the use of an investigational 
medical device. 
 
Notes: This definition includes adverse events 
resulting from insufficient or inadequate instructions 
for use, deployment, implantation, installation, or 
operation, or any malfunction of the investigational 
medical device. This definition includes any event 
resulting from use error or from intentional misuse of 
the investigational medical device. 
ISO 14155-1 
Serious Adverse 
Event (SAE) 
Adverse event that 
a) Led to death, 
b) Led to serious deterioration in the health of the 
participant, that either resulted in 
1) A life-threatening illness or injury, or 
2) A permanent impairment of a body 
structure or a body function, or 
3) In-patient or prolonged hospitalization, 
or 
4) Medical or surgical intervention to 
prevent life-threatening illness or injury 
or permanent impairment to a body 
structure or a body function, 
c) Led to fetal distress, fetal death or a congenital 
abnormality or birth defect 
ISO 14155-1 

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35 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
Unanticipated 
Adverse Device 
Effect (UADE) 
Any serious adverse effect on health or safety or any 
life-threatening problem or death caused by, or 
associated with, a device, if that effect, problem, or 
death was not previously identified in nature, 
severity, or degree of incidence in the investigational 
plan or application (including a supplementary plan 
or application), or any other unanticipated serious 
problem associated with a device that relates to the 
rights, safety, or welfare of participants.  
21 CFR 
812.3(s) 
 
 
9.2 Adverse Events (AEs) 
 
Adverse events that will be collected do not have to be related to use of the investigational 
device, ePatch, iPhone, or Apple Watch. The Study Safety Monitoring Desk is responsible for 
determining whether the adverse event is associated with the investigational device, and would 
therefore be considered an “adverse device effect.”  
 
Possible AEs related to participation in the study, but not related to use of the investigational 
device, include the following: 
 
● Skin rash due to wearing the ambulatory ECG monitor (ePatch); 
● Skin itchiness due to wearing the ambulatory ECG monitor (ePatch); 
● Blister due to wearing the ambulatory ECG monitor (ePatch); 
● Skin rash on wrist due to wearing the Apple Watch;  
● Pressure artifacts on wrist due to wearing the Apple Watch. 
 
The following occurrences are not to be regarded as AEs: 
 
● Underlying (pre-existing) symptoms or diseases, unless there is an increase in 
severity or frequency during the course of the investigation; 
● Receipt of an IPNA notification;  
● Detection of atrial fibrillation or other irregular heartbeat through the IPNA and 
confirmation by ePatch; 
● Pre-planned procedure(s); 
● Complaint about iPhone or Apple Watch functionality;  
● Failure of the participant to regularly wear the Apple Watch or to wear the ePatch as 
described by the Study Telehealth Provider.  
● Apple Heart Study app functionality issues related to poor wifi or cellular 
connectivity or user error 
 

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be reproduced, published, or disclosed to others without written authorization from Apple Inc. 
36 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
9.3 Adverse Device Effects (ADEs) 
 
ADEs are those effects determined by the Study Safety Monitoring Desk to be related to use of 
the investigational device, the Apple Heart Study app.  
 
Anticipated ADEs include the following: 
 
● Signs or symptoms related to participation in the study, including those determined to 
be related to the Apple Heart Study app.  The common signs and symptoms include 
stress and anxiety and associated symptoms that may include dizziness, depression, 
palpitations, tremors, sleep difficulty and shortness of breath. 
 
 
9.4 Recording of Adverse Events (AEs) and Adverse Device Effects (ADEs) 
 
All suspected AEs will be recorded by the Study Telehealth Provider Team during the 
scheduled virtual visits as well as at any time point during the study where the participant or 
their representative contacts the Study Telehealth Provider to report such an event.  The Study 
Safety Monitoring Desk personnel will assess suspected AEs for classification as suspected 
ADEs. All suspected AEs and ADEs will be tracked by the Study Safety Monitoring Desk 
personnel and all suspected ADEs will be reviewed and classified by the Study Safety Monitor.  
 
9.5 Recording of Serious Adverse Events (SAEs) 
 
All suspected SAEs will be recorded by the Study Telehealth Provider Team during the 
scheduled virtual visits as well as at any time point during the study where the participant or 
their representative contacts the Study Telehealth Provider to report such an event.  The Study 
Safety Monitoring Desk personnel will track all SAEs and all SAEs that are potentially ADEs 
will be reviewed and classified by the Study Safety Monitor.  
 
9.6 Reporting of Serious and Unanticipated Adverse Device Effects (UADEs) 
 
For this non-significant risk (NSR) study, the Investigators will be responsible for reporting 
any unanticipated adverse device effects (UADEs), as required by the IRB’s procedures and in 
conformance with FDA regulatory requirements. Reporting requirements as per 21 CFR 
812.150 will be followed for this study. 
 
All UADEs shall be reported to the sponsor and reviewing IRB as soon as possible, but no later 
than 10 working days after the Study Safety Monitoring Desk’s confirmation of the event as an 
UADE. IRB reporting will be performed according to governing IRB requirements. 
 

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37 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
The Principal Investigators are responsible for informing the IRB of any UADE and submit a 
copy of the report to the sponsor within 5 working days. 
 
The study sponsor will conduct an evaluation of a UADE under 812.46(b) and report the 
results of such evaluation to FDA within 10 working days after the sponsor first receives notice 
of the effect.   
 
 

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required by applicable laws and regulations. The information in this document is the property of Apple Inc. and may not 
be reproduced, published, or disclosed to others without written authorization from Apple Inc. 
38 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
10.0 WITHDRAWAL 
 
Every participant should be encouraged to remain in the study until they have completed the 
protocol-required follow-up period. If the participant withdraws prematurely from the study, 
the reason for withdrawal should be documented. Possible reasons for premature withdrawal 
may include, but are not limited to the following:  
 
● Withdrawal of consent: participant decides to withdraw from the study for any reason. 
This may be concluded if/when a participant taps the withdraw button within the app or 
asks to be withdrawn. 
● Investigators believe it is in the best interest of the participant to discontinue the study, 
for any reason. 
 
Withdrawal Process: 
 
Participants will have the option to withdraw from the study by tapping a “Withdraw from 
Study” button within the app. This will disable notifications and will result in a cessation of 
data collection.  If a participant calls the Study Telehealth Provider requesting withdrawal from 
the study, the Study Telehealth Provider will instruct the participant how to initiate withdrawal 
on the app. It will not be possible for any party other than the study participant themselves to 
withdraw from the study. In the few cases where the participant has received a notification, and 
has initiated contact with the Study Telehealth Provider, and thereafter selects “Withdraw from 
Study” on the app, they may still receive follow-up communication from the Study Telehealth 
Provider.  In order to stop further communication, these participants would need to inform the 
Study Telehealth Provider Team that they wish to be withdrawn.   
 
Once withdrawn, participants would be able to re-enroll only by reinstalling the application, 
but will be considered a new study participant without linkage to their prior data. 
 
The following will be considered lost-to-follow-up: 
 
● Death of the participant 
● Lost/stolen iPhone and/or Apple Watch 
 
 
 

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39 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
11.0 STATISTICAL CONSIDERATIONS  
 
11.1 Analysis Sets 
 
The Full Analysis Set (FAS) will consist of all participants who are enrolled in the study. 
The Notification Analysis Set (NAS) will consist of all participants who receive a IPNA. This 
analysis set is equivalent to the Notification Subgroup. The co-primary AF endpoint will be 
collected from these participants to evaluate Objective 1. 
The ECG Analysis Set (EAS) will consist of all participants who receive an ambulatory ECG 
monitor, wear it for a minimum amount of time providing a minimum analyzable time of 1 
hour, and self-report no history of AF prior to the time of consent. This analysis set includes all 
participants in the ambulatory ECG monitor subgroup who wear their patch providing at least 1 
hour of analyzable time.  The co-primary tachogram endpoint will be collected from these 
participants to evaluate Objective 2. All tachogram- and alert-level outcomes will be estimated 
from this analysis set during times when tachograms are being recorded by Apple Watch 
during simultaneous, analyzable ECG monitoring.  The ambulatory ECG monitor recordings 
will be measured during the entire period the patch is worn. 
 
 
11.2 Endpoints and Definitions 
 
11.2.1 Co-Primary Endpoints 
 
1. AF of greater than 30 seconds duration detected on ambulatory ECG monitoring for a 
participant who received an irregular pulse watch notification.  
2. Simultaneous ambulatory ECG monitoring indicating an irregular rhythm consistent 
with AF during time intervals when the spot tachogram is positive for an irregular pulse 
among those who received a notification. Each participant contributes multiple 
observations for this endpoint. 
 
11.2.2 Secondary Endpoints 
 
1. Simultaneous ambulatory ECG monitoring indicating an irregular rhythm consistent 
with AF when the IPNA based on multiple tachograms is positive for an irregular pulse 
among those who received a notification. These positive IPNA triggers will not result 
in additional notifications to participant, but will be available for analyses.  Each 
participant contributes multiple observations for this endpoint. 
2. Self-reported contact with a health care provider within 3 months following an irregular 
pulse watch notification.  

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40 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
11.2.3 Tertiary Endpoints 
1. Arrhythmias, other than AF, detected on an ambulatory ECG monitor that can also
result in an irregular pulse. These include sinus arrhythmia, frequent premature atrial
contractions, frequent premature ventricular contractions, intermittent heart block,
multifocal atrial tachycardia and atrial tachycardia with variable conduction.
2. AF of greater than 6 minutes, 1 hour, 6 hours, and 24 hours duration detected on
ambulatory ECG monitor following an irregular pulse watch notification.
3. Self-reported initiation of therapies for AF, including anticoagulant, rate-controlling
and antiarrhythmic therapy.
4. Self-reported electrical or chemical cardioversion by a health care provider.
11.3 Statistical Approaches 
11.3.1 Estimating Positive Predictive Value (PPV) in the First Objective 
We have designed the study to estimate the proportion of participants age 65 or older 
diagnosed with AF within a 5% margin of error. In other words, we have designed the study so 
the 97.5% confidence interval around the estimate will have a width of 10%. Our analysis will 
include the participants 65 or older in the NAS. There is no hypothesis testing for the co-
primary outcomes. We use 97.5% confidence intervals to account for the co-primary outcomes. 
11.3.2 Estimating PPV of the Spot Tachogram to Address the Second Objective 
We assume that each tachogram measured on a participant is independent of other intervals 
measured from that participant. In sensitivity analyses, we will evaluate the impact of this 
assumption. From the available intervals, we will randomly select 10 intervals per participant 
in the EAS to ensure each participant contributes a comparable period of data on which to 
evaluate concordance. All intervals will be used in participants who have fewer than 10 
intervals available. 
We will conclude that the algorithm may be promising if the PPV is extremely high. Our 
hypothesis is that the proportion of intervals that are true positives out of the total intervals 
where the spot tachogram is positive for an irregular pulse will be at least 0.75 in participants 
65 or older. We will design our study so that we will have ~99% power to detect whether the 
lower bound of a 97.5% confidence interval is greater than 0.70 and the upper bound is at least 
0.75 if the PPV is truly 0.75. The power will increase if the PPV is higher than 0.75 in reality. 

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41 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
11.3.3 Secondary and Tertiary Analyses 
All secondary and tertiary outcomes will be analyzed as proportions with 95% confidence 
intervals. Outcomes measured at the tachogram- or alert-level will be analyzed in the EAS 
while self-reported contact with a health care provider and initiation of therapies or 
cardioversion will be analyzed in the NAS. The self-reported outcomes will also be analyzed in 
the FAS. 
11.3.4 Sensitivity and Sub-Analyses 
As a sensitivity analysis, the estimates for the co-primary outcomes will be repeated for 
participants of all ages.  
The proportions and 97.5% confidence intervals used to analyze the co-primary outcomes will 
be performed separately by age (<55, 55-64, ≥65), AF burden, type of AF and non-AF 
irregular rhythms. Additionally, we will perform chi-squared tests to test whether the PPV 
proportions differ by age or burden. 
To better understand the performance of the IPNA across the participant population, we will 
construct separate 95% confidence intervals around the proportion of participants diagnosed 
with AF according to tertiles of spot tachogram PPV observed in the secondary objective. 
11.4 Handling of Missing Data 
All participants who receive a positive IPNA will be included in the analysis of the co-primary 
endpoint indicating AF after positive IPNA regardless of whether they receive and wear the 
ambulatory ECG monitor. Participants who do not have at least an hour of analyzable wear 
time from the ambulatory ECG monitor will be considered to have missing data. Multiple 
imputation methods will be used to account for the participants who are missing the AF 
endpoint.  
In analyses where the tachogram or an IPNA is the unit of analysis, participants who have at 
least one tachogram recorded during the simultaneous ECG monitoring will be including in the 
analyses. We will use any available tachograms and no data will be considered missing.   
Multiple imputation methods will be used in the analyses of patient reported outcomes to 
account for an expected small proportion of participants who do not complete all questions. 

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42 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
11.5 Interim Checks 
A series of interim checks will be performed. 
Throughout the course of the study, the number of irregular pulse watch notifications occurring 
per age subgroup will be checked. A check will be performed 2 weeks after the first participant 
is enrolled (see Figure 1. Study Timeline). If a high number of alerts is observed (greater than 
10%), enrollment may be paused or throttled downward in any age subgroup (<40, 40-54, 55-
64, ≥65). If the number of notifications observed is less than the study infrastructure capacity, 
the numbers of participants invited to enroll from the “waiting period” may be increased. 
An interim check will be performed upon completion of the first 100 ambulatory ECG 
monitors in any of the four age subgroups (see Figure 1 Study Timeline). The interim check 
will be performed for each subgroup regardless of how many patches are received in other age 
subgroups. We estimate the check to occur at approximately 6-8 weeks after the first 
participant enrolled to check the following: 
1. At least 50% of participants notified of an irregular pulse are ultimately wearing and
returning the ambulatory ECG monitor. A low rate of ambulatory ECG monitor use
would result in an increase in the rates of invitations to enrollment in any age subgroup.
2. Percentage of atrial fibrillation noted on ambulatory ECG monitoring is greater than
1%. A detection of atrial fibrillation less than 1% will prompt a cessation of enrollment
in any corresponding age subgroup.
3. Percentage of non-clinically relevant irregular rhythms is greater than 90%. If the vast
majority of rhythms detected on ambulatory ECG monitoring are due to other irregular,
non-AF arrhythmias, such as sinus arrhythmia, frequent PACs and frequent PVCs, this
will prompt a cessation of enrollment in any corresponding age subgroup.
The co-primary endpoints will be evaluated after 503 participants aged ≥65 have completed 
their virtual visit and have at least 1 hour of ambulatory ECG monitor data recorded, i.e. at 
least 503 participants who are in the EAS.  
These interim analyses are not designed to evaluate ultimate efficacy or futility and do not 
impact the Type I error as we will not be examining the final positive predictive values of the 
co-primary endpoints using this interim analysis. 
A much higher than anticipated rate of notifications and subsequent ePatch evaluations may 
result in marginal benefit of additional participant enrollment. The following will be set as 

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43 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
maximum targets for ePatch monitoring. Exceeding these limits will trigger either a throttling 
downward or cessation of enrollment: 
 
1. Completion of 5,000 ePatches in total in either participants ≥ 65 or participants aged 
22-64 will result in cessation of enrollment in the corresponding age group. 
 
2. Completion of > 100 ePatches per week in either participants ≥ 65 or participants aged 
22-64 will result in a throttling downward of enrollment invitations in the 
corresponding age groups. 
 
 
11.6 Sample Size and Power Considerations 
 
We anticipate identifying 750 participants age 65 or older who qualify for an ePatch during the 
initial study period of 3 months. Among these, we anticipate a clinical diagnosis will be 
available on 503 participants. The proportion of participants with clinically important AF will 
be estimated and a 97.5% confidence interval will be constructed around the estimate. 
Similarly, a 97.5% confidence interval will be constructed for the estimated proportion of 
participants with clinically important AF among those who receive an irregular pulse watch 
notification of all ages. With 503 participants, we will have sufficient observations to estimate 
the proportion with a margin of error of 5% or smaller, regardless of what the true proportion 
is. 
Our decision rule for concluding the IPNA is promising to address Objective 2 is sensible 
given the amount of data with which we will rule our algorithm as promising or in need of 
greater refinement. With 3000 observed intervals where ePatch and tachogram data is available 
in participants 65 or older, we will have at least ~98% power to rule out a PPV of 0.70 or lower 
(using the decision rule and assumptions described in Section 11.3.2). 
If we assume that we will sample 10 intervals from each person with an ePatch, then we will 
need 300 participants with ePatches to get 3000 observed intervals, which is well below the 
503 participants required for the AF co-primary endpoint.  
We are assuming that 1% of participants 65 and older will get a notification and receive an 
ePatch, which corresponds to 75,000 participants older than 65 needed to enroll in the study to 
achieve sufficient power. We additionally plan to enroll approximately 425,000 participants 
aged less than 65 during the study period. We are making the conservative assumption that ~2 
participants out of 1000 in the younger age group will qualify to receive an ambulatory ECG 
monitor, from which we expect 503 participants to have data available from their ambulatory 
ECG monitor.  
 
 

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44 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
12.0 TRAINING 
 
To ensure accurate, complete, and reliable data, the Stanford study team in conjunction with 
sponsor, will provide instructional material to Study Telehealth Provider, BioTelemetry, ECG 
Adjudicating Clinicians and other study personnel as appropriate. 
 
13.0 STEERING COMMITTEE AND DATA AND SAFETY 
MONITORING BOARD  
 
A Steering Committee (SC) will be commissioned to monitor the practical aspects of the study 
and to provide independent scientific guidance regarding the protocol, implementation, 
execution and analysis. SC will perform periodic review of the study progress, recruitment 
figures, data, data quality, analysis and results. SC will resolve any differences within the 
research team or between research team and the sponsor on the data management or study 
procedures and will provide recommendations for modifications to the protocol if needed. 
 
An independent Data and Safety Monitoring Board (DSMB) will be appointed and will report 
to the Steering Committee.  The DSMB will be responsible for safeguarding the interests of the 
participants and for reviewing the overall conduct of the clinical study. The DSMB charter will 
be prepared to detail precise roles and responsibilities and procedures and interactions with the 
Steering Committee. 
 
  
14.0 ETHICAL AND REGULATORY CONSIDERATIONS 
This study will be conducted in accordance with FDA regulations (21 CFR Parts 50, 54, 56 and 
812). 
  
 
 14.1 Institutional Review Board/Medical Ethics Committee  
  
The protocol must be submitted to the appropriate Institutional Review Board (IRB) and 
written approval must be obtained prior to enrolling any participants. Yearly approvals for the 
continuation of the study must be obtained by the Investigator. 
  
 

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45 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
14.2   Informed Consent and HIPAA Authorization   
 
The Informed Consent will be provided within the study app and will employ ResearchKit 
electronic consent framework for the signature view to obtain signed and dated informed 
consent and HIPAA authorization prior to enrollment. Signed consent forms will be stored on 
an encrypted server which is 21 CFR Part 11 compliant. The protocol and informed consent 
form must be approved by the reviewing IRB prior to commencement of the study. Any 
subsequent revisions to the informed consent form must also receive IRB approval prior to use.  
 
 
14.3 Confidentiality of participants  
 
Participant confidentiality will be maintained throughout the clinical study in a way that 
ensures the information can always be tracked back to the source data. For this purpose, a 
unique participant identification code (ID number) will be used that allows identification of all 
data reported for each participant. The ID number will be randomly generated. 
 
Participant information collected in this study will comply with the standards for protection of 
privacy of individually identifiable health information. The Sponsor, investigators and all study 
affiliates will make every reasonable effort to protect the confidentiality of the participants 
participating in this study. Participant records may be released to governing regulatory 
authorities, if requested. In all cases, caution will be exercised to assure the data are treated 
confidentially and that the participant’s privacy is protected. 
 
15.0 HUMAN SUBJECTS PROTECTION  
 
15.1 Research participant Selection and Justification of Exclusions  
There will be no exclusion from participation in the study on the basis of ethnicity or race. 
Participants younger than 22 years of age will be excluded from the study, as the target 
population is adults ≥ 22 years. Participants who are not proficient in written English will be 
excluded as this will prohibit informed consent as well as completion of any necessary data 
collection forms. 
 
 
15.2 Compensation to participants  
 
There will be no direct monetary remuneration to study participants.  

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46 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
 
16.0 RECORD KEEPING/REPORTING 
 
16.1 Data Collection  
 
The study will create 21 CFR Part 11 compliant data flows for relevant study sources to 21 
CFR Part 11 compliant servers housing information on participant demographics, baseline 
health history, data on watch PPG detected pulse irregularities, ambulatory ECG monitor 
results, Adverse Events and 90-day PRO. 
 
 
16.2 Study Documentation  
Study documentation includes but is not limited to all consent forms, app screens, app based 
screening forms, PROs, ambulatory ECG monitor reports, and regulatory documents (e.g., 
signed protocol and amendments, IRB correspondence and approval, approved and signed 
participant consent forms, Statement of Investigator form, etc.). The investigator will prepare 
and maintain complete and accurate study documentation in compliance with applicable 
federal, state, and local laws, rules, and regulations. 
 
 
 
 
 
 
 

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47 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
 
 
 
 
17.0 REFERENCES  
 
1.      Miyasaka Y, Barnes ME, Gersh BJ, et al. Secular trends in incidence of atrial fibrillation 
in Olmsted County, Minnesota, 1980 to 2000, and implications on the projections for 
future prevalence. Circulation. 2006;114(2):119-125. 
2.      Andrade J, Khairy P, Dobrev D, Nattel S. The clinical profile and pathophysiology of 
atrial fibrillation: relationships among clinical features, epidemiology, and mechanisms. 
Circ Res. 2014;114(9):1453-1468. 
3.      Wolf PA, Abbott RD, Kannel WB. Atrial fibrillation: a major contributor to stroke in the 
elderly. The Framingham Study. Arch Intern Med. 1987;147(9):1561-1564. 
4.      Writing Group M, Mozaffarian D, Benjamin EJ, et al. Heart Disease and Stroke 
Statistics-2016 Update: A Report From the American Heart Association. Circulation. 
2016;133(4):e38-360. 
5. 
van Walraven C, Hart RG, Singer DE, et al. Oral anticoagulants vs aspirin in nonvalvular 
atrial fibrillation: an individual patient meta-analysis. JAMA. 2002;288(19):2441-2448. 
6.      Lin HJ, Wolf PA, Benjamin EJ, Belanger AJ, D'Agostino RB. Newly diagnosed atrial 
fibrillation and acute stroke. The Framingham Study. Stroke. 1995;26(9):1527-1530. 
7.      Engdahl J, Andersson L, Mirskaya M, Rosenqvist M. Stepwise screening of atrial 
fibrillation in a 75-year-old population: implications for stroke prevention. Circulation. 
2013;127(8):930-937. 
8.      Cullinane M, Wainwright R, Brown A, Monaghan M, Markus HS. Asymptomatic 
embolization in participants with atrial fibrillation not taking anticoagulants: a 
prospective study. Stroke. 1998;29(9):1810-1815. 
9.    Meschia JF, Bushnell C, Boden-Albala B, et al. Guidelines for the primary prevention of 
stroke: a statement for healthcare professionals from the American Heart 
Association/American Stroke Association. Stroke. 2014;45(12):3754-3832. 
10.    Kirchhof P, Benussi S, Kotecha D, et al. 2016 ESC Guidelines for the management of 
atrial fibrillation developed in collaboration with EACTS. Eur Heart J. 
2016;37(38):2893-2962. 
11. Turakhia MP, Shafrin J, Bognar K, et al. Economic Burden of Undiagnosed Nonvalvular 
Atrial Fibrillation in the United States. Am J Cardiol. 2015;116(5):733-739. 
12.    Lowres N, Neubeck L, Salkeld G, et al. Feasibility and cost-effectiveness of stroke 
prevention through community screening for atrial fibrillation using iPhone ECG in 
pharmacies. The SEARCH-AF study. Thromb Haemost. 2014;111(6):1167-1176. 
13.    Svennberg E, Engdahl J, Al-Khalili F, Friberg L, Frykman V, Rosenqvist M. Mass 
Screening for Untreated Atrial Fibrillation: The STROKESTOP Study. Circulation. 
2015;131(25):2176-2184. 
14.    Tung CE, Su D, Turakhia MP, Lansberg MG. Diagnostic Yield of Extended Cardiac 
Patch Monitoring in Patients with Stroke or TIA. Front Neurol. 2014;5:266. 

Confidential 
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required by applicable laws and regulations. The information in this document is the property of Apple Inc. and may not 
be reproduced, published, or disclosed to others without written authorization from Apple Inc. 
48 
Apple Heart Study 
Protocol Version: 8.0, Date: March 20, 2018 
15.
Gladstone DJ, Spring M, Dorian P, et al. Atrial fibrillation in patients with cryptogenic
stroke. N Engl J Med. 2014;370(26):2467-2477.

Statistical Analysis Plan
Study Official Title: Apple Heart Study: Assessment of Wristwatch-Based
Photoplethysmography to Identify Cardiac Arrhythmias
ClinicalTrials.gov Identifier: NCT03335800
Document Date: 09 Nov 2018

Statistical Analysis Plan 
Study Name 
Apple Heart Study 
Version Number 1.6 
Date 
9 November 2018 
Apple Heart Study 
Assessment of Wristwatch-Based Photoplethysmography 
to Identify Cardiac Arrhythmias

Statistical Analysis Plan 
Apple Heart Study 
Version 1.6 
9 November 2018
2 
SIGNATURE PAGE 

Statistical Analysis Plan 
Apple Heart Study 
Version 1.6 
9 November 2018
3 
TABLE OF CONTENTS 
PAGE 
1. Study Details __________________________________________________________ 6 
1.1 Study objectives ___________________________________________________________ 6 
1.2 Study design ______________________________________________________________ 6 
1.3 Number of Participants Needed to Address Objectives _____________________________ 7 
2. Endpoints _____________________________________________________________ 9 
2.1 Primary Endpoints _________________________________________________________ 9 
2.2 Secondary Endpoints _______________________________________________________ 9 
2.3 Tertiary Endpoints _________________________________________________________ 9 
3. Analysis Sets __________________________________________________________ 10 
4. Analysis Methods ______________________________________________________ 11 
4.1 General Principles ________________________________________________________ 11 
4.2 Study Population _________________________________________________________ 12 
4.3 Analysis Methods _________________________________________________________ 16 
4.4 Tertiary Endpoints ________________________________________________________ 19 
4.5 Definitions ______________________________________________________________ 23 
4.6  Handling of Missing Data __________________________________________________ 25 
4.7  Potential Limitations and Mitigation Strategies _________________________________ 25 
5. Interim Checks ________________________________________________________ 27 
6. Validation Plan _______________________________________________________ 29 
6.1  Reproducibility Plan on Sub-Study Analysis ___________________________________ 29 
6.2 Replication on Final AHS Study Data _________________________________________ 30 
A1. Appendix: AHS Sub-Study Protocol and SAP _______________________________ 30 

Statistical Analysis Plan  
Apple Heart Study 
Version 1.6 
9 November 2018 
4 
LIST OF ABBREVIATIONS  
The following abbreviations and special terms are used in this Statistical Analysis Plan (SAP). 
Abbreviation or special term 
Explanation 
AE 
Adverse Event 
AF 
Atrial Fibrillation and Atrial Flutter 
ARR 
Arrhythmia 
CI 
Confidence Interval   
EAS 
ECG Analysis Set 
ECG 
Electrocardiography 
FAS 
Full Analysis Set 
IPN 
Irregular Pulse Watch Notification  
IPNA 
Irregular Pulse Watch Notification Algorithm 
NAS 
Notification Analysis Set 
PAC 
Premature Atrial Contractions 
PCP 
Primary Care Provider 
PPG 
Photoplethysmography 
PPV 
Positive Predictive Value 
PRO 
Patient Reported Outcome 
PVC 
Premature Ventricular Contractions 
SAE 
Serious Adverse Event 
SAP 
Statistical Analysis Plan 
 

Statistical Analysis Plan 
Apple Heart Study 
Version 1.6 
9 November 2018
5 
Revision history 
Revision 
Date 
Section/Page 
Changes Made -- Reasons for the 
Change 
1 
4/19/18 
Throughout document 
Added table shells 
2 
4/19/18 
Section 1.1/Page 6 
Updated text of Objective 3 to be 
consistent with protocol v8.0 
3 
4/19/18 
Section 1.2/Page 7 
Defined ECG acronym in text 
4 
4/19/18 
Section 2.3, 4.4/Page 
9, 18 
Updated tertiary endpoint to be consistent 
with protocol v8.0 
5 
4/19/18 
Section 3/Page 10 
Updated definitions of analysis sets for 
clarification and to reflect protocol 
amendment in v8.0 
6 
4/19/18 
Section 4.3/Page 17 
Clarified analysis sets in tertiary analyses 
7 
4/19/18 
Section 4.4/Page 20 
Updated definition of fall-out subgroup to 
be consistent with protocol v8.0 
8 
4/19/18 
Section 5/Page 25 
Updated interim checks text to be 
consistent with protocol v8.0 
9 
5/24/18 
Section 4.2/Page 14 
Updated categories in Table 2 to be 
consistent with options available in app 
10 
5/24/18 
Section 6/Page 27 
Added validation plan and appendix 
containing sub-study protocol and SAP 
11 
5/31/18 
Section 4.4/Page 19 
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INTRODUCTION 
This statistical analysis plan (SAP) is a comprehensive and detailed description of the 
strategy, rationale and statistical techniques that will be used to assess and evaluate the ability 
of the Irregular Pulse Watch Notification Algorithm (IPNA) to identify atrial fibrillation and 
atrial flutter (AF) and guide subsequent clinical evaluation. 
1. STUDY DETAILS 
1.1 Study objectives 
Objective 1a: To measure the proportion of participants aged ≥ 65 with irregular pulse watch 
notifications who have demonstrable AF as confirmed by ambulatory electrocardiographic 
patch monitoring. 
 
Objective 1b: To measure the proportion of all participants with irregular pulse watch 
notifications who have demonstrable AF as confirmed by ambulatory electrocardiographic 
patch monitoring. 
 
Objective 2: To characterize the concordance between pulse irregularity determined using 
spot tachograms (approximately one minute of beat-to-beat intervals) and AF detected by 
simultaneous ambulatory electrocardiographic patch monitoring.  
 
Objective 3:  To estimate the rate of initial contact with a health care provider within 3 
months after an irregular pulse notification. 
 
1.2 Study design 
This will be a prospective, single arm, experimental study using participants wearing an Apple 
Watch with the Apple Heart Study app. Using observable variations in photoplethysmogram 
(PPG) signal intensity, changes in blood flow can be measured and beat-to-beat pulse 
measurements can be made. During normal sinus rhythm, there is minimal variation in pulse. 
However, during AF, the beat-to-beat variability increases significantly. Therefore, a PPG 
signal can be used to differentiate between a regular pulse and an irregular pulse that may be 
indicative of AF. 
An algorithm has been developed by Apple to identify periods of irregular pulse based on 
PPG signal variation as measured by the Irregular Pulse Notification Algorithm (IPNA) within 
the Apple Heart Study app. The algorithm’s analysis is initiated when the Apple Heart Study 
app successfully retrieves approximately one minute of beat-to-beat intervals, defined as a 
tachogram, derived from the Apple Watch PPG HR sensor through HealthKit, a data 
repository on a user’s iPhone. If, and when, the Apple Heart Study app retrieves a tachogram 

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and subsequently classifies it as “irregular”, it shifts into a “confirmation mode” and begins 
requesting, and analyzing, tachograms on a more frequent basis until it is able to confirm 
sustained irregularities or the confirmation cycle is otherwise ended. Upon completion of a 
positive confirmation cycle within a 48-hour period, the Apple Heart Study app provides a 
notification (IPN) to the user on their Apple Watch and subsequently on their iPhone app. 
 
Participants without urgent symptoms who receive an irregular pulse notification will be 
offered an ambulatory electrocardiographic (ECG) monitor (ePatch). Participants will be 
requested to wear the ePatch for 7 days.  An independent team of board certified clinicians 
will adjudicate the technical report generated from the ePatch monitoring to identify periods 
of AF and other rhythm irregularities. Additionally, this team will adjudicate the raw ECG 
data that is matched to the time period of the individual tachograms.  
 
Participants who receive an irregular pulse notification (IPN) will receive an additional 
request to enter participant reported outcomes (PRO) three months after the notification. All 
participants, regardless of whether they received an irregular pulse notification (IPN), will 
receive an end-of-study PRO questionnaire at the end of the study, which is anticipated to be 
approximately one year after initial Apple Heart Study App availability. 
 
1.3 Number of Participants Needed to Address Objectives 
The minimum number of ePatches needed was calculated based on our desire to estimate the 
proportions in Objectives 1a and 1b such that the 97.5% confidence interval around the 
estimate is no wider than 0.10 in both age groups (< 65 and ≥ 65). We derived the number of 
enrolled participants and the number of tachograms needed from the number of ePatches 
required to achieve our desired precision in Objectives 1a and 1b. 
The feasibility of our study relies on an assumption that 1% of participants 65 and older will 
receive a notification and that approximately ⅔ of those receiving a notification will return 
their ePatch and receive a clinical diagnosis. This corresponds to 75,000 participants older 
than 65 needed to enroll in the study to achieve sufficient precision. We anticipate identifying 
at least 750 participants age 65 or older who qualify for an ePatch during the initial study 
period of 3 months. Among these participants, we anticipate a clinical diagnosis (via 
adjudication of the ECG patch) will be available on 503 participants. The proportion of 
participants age 65 or older with clinically important AF will be estimated and a two-sided 
97.5% confidence interval will be constructed for the probability of clinically important AF in 
this population (Objective 1a). 
We are making the conservative assumption that ~2 participants out of 1000 in the younger 
age groups (total of all participants in <40, 40-54, 55-64) will qualify to receive an ePatch, 
from which we expect at least 503 participants to have data available from their ePatch. A 
two-sided 97.5% confidence interval will be constructed among all participants for the 
probability of observing clinically important AF among all adults who receive an irregular 

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pulse watch notification (Objective 1b). With 503 participants, we will have sufficient 
observations to estimate the probability with a confidence interval width of 0.10 or smaller, 
regardless of what the true proportion is. 
Objective 2 will be devoted to evaluating the concordance between irregularity identified by 
the spot tachograms and that detected by the ePatch. We will conclude that the algorithm 
produces clinically meaningful alerts if the PPV is high, where ePatch is considered the gold 
standard against which to gauge performance of the spot tachograms. We expect that the 
proportion of intervals that are true positives out of the total intervals where the spot 
tachogram is positive for an irregular pulse will be at least 0.75 in participants 65 or older.  
Our decision rule for concluding the IPNA is sufficiently concordant with ePatch is that the 
lower bound of a two-sided 97.5% confidence interval is greater than 0.70 and the upper 
bound is at least 0.75. The same decision rule will be applied to analyses performed on 
participants of all ages.  
Our decision rule is sensible given the amount of data with which we will rule our algorithm 
produces clinically meaningful alerts. The properties of our decision rule are based on 
observing 3000 tachograms where the ePatch is concurrently available in participants 65 or 
older. The same decision rule will be applied to analyses performed on participants of all ages. 
We evaluated the properties of our decision rule using 1000 simulated data sets each with 
3000 tachograms. We assumed 2250 (75%) tachograms were concordant with the ambulatory 
ECG monitoring and constructed the 97.5% confidence intervals using an asymptotic 
Gaussian approximation. With 3000 observed tachograms where ePatch is concurrently 
available in participants 65 or older, we will have at least 98% power to detect whether the 
lower bound of a 97.5% confidence interval is greater than 0.70 and the upper bound is at least 
0.75 if the PPV is truly 0.75.  
While this is not a traditional hypothesis test, we have set 0.75 as the threshold to be met or 
exceeded in order to determine if the algorithm produces meaningful alerts. This threshold 
was chosen as a clinically meaningful parameter for the individual tachogram concordance. 
This threshold will be applied to analyses performed on participants 65 or older and to 
analyses including all ages. 
Our enrollment plan will allow us to evaluate the appropriate number of tachograms from the 
appropriate number of participants.  Specifically, we will randomly sample at least 10 positive 
tachograms from each person with an ePatch, requiring at most 300 participants with positive 
tachograms recorded while wearing ePatches to provide 3000 observed intervals, which is 
well below the 503 participants required for the AF co-primary endpoint. Based on 
preliminary data, an average of 4 tachograms per day are expected to be collected in 
participants with regular rhythms and a higher number in participants with irregular rhythms. 
Hence, we expect to have at least 10 positive tachograms observed during the simultaneous 
ECG monitoring period lasting approximately 7 days in most participants being monitored.  

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2. ENDPOINTS 
2.1 Primary Endpoints 
The co-primary endpoints of the study are   
● An indicator for whether AF of greater than 30 seconds duration was detected on 
ambulatory ECG monitoring for a participant who received an irregular pulse notification. 
(AF after IPN) 
 
● Simultaneous ambulatory ECG monitoring indicating an irregular rhythm consistent with 
AF during time intervals when the spot tachogram is positive for an irregular pulse among 
those who received a notification. This endpoint will be measured during time intervals 
when the watch provides tachogram data and the participant has patch data recorded. Each 
participant contributes multiple observations for this endpoint. (ePatch+) 
 
2.2 Secondary Endpoints 
The secondary variables are 
● Simultaneous ambulatory ECG monitoring indicating an irregular rhythm consistent with 
AF of greater than 30 seconds duration when the IPNA based on multiple tachograms is 
positive for an irregular pulse among those who received a notification. These positive 
IPNA triggers will not result in additional notifications to participant, but will be available 
for analyses.  Each participant contributes one observation. (IPNA+) 
● Self-reported contact with a health care provider within 3 months following an irregular 
pulse notification. (PCP PRO after IPN) 
 
2.3 Tertiary Endpoints  
● An indicator for the presence of arrhythmias other than AF detected on ambulatory ECG 
monitoring that can also result in an irregular pulse. Arrhythmias considered include sinus 
arrhythmia, frequent premature atrial contractions (PAC), frequent premature ventricular 
contractions (PVC), intermittent heart block, multifocal atrial tachycardia, and atrial 
tachycardia with variable conduction. Definitions of each arrhythmia are provided in 
Section 4.4. (ARR after IPN) 
● AF of greater than 6 minutes, 1 hour, 6 hours, and 24 hours duration detected on 
ambulatory ECG monitoring following an irregular pulse watch notification. (AFtime after 
IPN) 
● Self-reported initiation of therapies for AF, including anticoagulant, rate-controlling and 
anti-arrhythmic therapy. (therapies) 

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● Self-reported electrical or chemical cardioversion by a health care provider. 
(cardioversion) 
3. ANALYSIS SETS 
The Full Analysis Set (FAS) will consist of all participants who are enrolled in the study. 
The Notification Analysis Set (NAS) will consist of all participants who receive a IPNA. This 
analysis set is equivalent to the Notification Subgroup. The co-primary AF endpoint will be 
collected from these participants to evaluate Objective 1. 
The ECG Analysis Set (EAS) will consist of all participants who receive an ambulatory ECG 
monitor, wear it for a minimum amount of time providing a minimum analyzable time of 1 
hour, self-report no history of AF prior to the time of consent, and who were not associated 
with a technical issue arising from the AHS app preventing linkage of the patch data with the 
tachogram data.  The identification of the subjects to be removed from the EAS will be 
finalized prior to data analysis. This analysis set includes all participants in the ambulatory 
ECG monitor subgroup who wear their patch providing at least 1 hour of analyzable time.  
The co-primary tachogram endpoint will be collected from these participants to evaluate 
Objective 2. All tachogram- and alert-level outcomes will be estimated from this analysis set 
during times when tachograms are being recorded by Apple Watch during simultaneous, 
analyzable ECG monitoring.  The ambulatory ECG monitor recordings will be measured 
during the entire period the patch is worn. 
 
Analyses performed at the tachogram level will further restrict the EAS to participants who 
began wearing their patch within 14 days of shipment. 
 
Table 1 
Analysis Sets and the Unit of Analysis to be Used for Each Endpoint 
Endpoint 
Analysis set 
Unit of analysis 
Concurrent 
AF after IPN [primary] 
EAS 
participant 
not concurrent 
ePatch+ [primary] 
EAS 
tachogram 
concurrent 
IPNA+ [secondary] 
EAS 
participant 
concurrent 
PCP PRO after IPN [secondary] 
NAS 
participant 
not concurrent 
ARR after IPN [tertiary] 
EAS 
participant 
not concurrent 

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AFtime after IPN [tertiary] 
EAS 
participant 
not concurrent 
Therapies [tertiary] 
NAS, FAS 
participant 
not concurrent 
Cardioversion [tertiary] 
NAS, FAS 
participant 
not concurrent 
 
 
Note: The concurrent column indicates whether the estimate is based on measures recorded 
simultaneously. 
4. ANALYSIS METHODS 
4.1 General Principles 
Method for Constructing Confidence Intervals 
We will construct confidence intervals using the asymptotic Gaussian approximation. For 
proportions near 1 or 0, a potential drawback of this method is confidence intervals containing 
values outside of the range [0,1]. If we encounter confidence intervals with bounds outside of 
the [0,1] range we will instead construct the confidence intervals using the BCa method of 
creating a bootstrap confidence interval. 
Incomplete Dates 
If only the year of a date is given (YY), then the date shall be set to ‘YY0701’. If only the year 
and month of a date is given (YYMM), then the date shall be set to ‘YYMM15’. 
Descriptive Statistics 
Numerical variables will be summarised using standard summary statistics including the 
number of participants, mean, standard deviation, median, 10th and 90th percentile and range 
(i.e., minimum and maximum) as appropriate.  For categorical data, proportions will be 
presented in a frequency table format.   
Multiple Patches per Participant 
In rare instances where a single user ID is associated with data available from more than one 
patch, only data from the final patch will be used in statistical analyses. 

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4.2 Study Population 
Participant Disposition 
The number and percent of participants who completed the study, discontinued from the 
study, and reasons for discontinuation from the study will be summarized by age group and 
overall, for the NAS and FAS.  
 
NAS 
FAS 
22-39   N 
Completed the study #,% 
Discontinued from study 
#,% 
Reasons for discontinuation 
 
 
40-54   N 
Completed the study #,% 
Discontinued from study 
#,% 
Reasons for discontinuation 
 
 
55-64   N 
Completed the study #,% 
Discontinued from study 
#,% 
Reasons for discontinuation 
 
 

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65+      N 
Completed the study #,% 
Discontinued from study 
#,% 
Reasons for discontinuation 
 
 
Overall N 
Completed the study #,% 
Discontinued from study 
#,% 
Reasons for discontinuation 
 
 
 
 
The number and percent of participants who withdrew from the study will be summarized by 
age group and overall, for the NAS and EAS.  
 
Withdrawals 
 
N NAS 
% NAS 
N EAS 
% EAS 
22-39 
 
 
 
 
40-54 
 
 
 
 
55-64 
 
 
 
 
65+ 
 
 
 
 
Overall 
 
 
 
 

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Participants having protocol deviations will be summarized using the FAS population. 
 
N FAS 
N PDs 
PDs/FAS 
22-39 
 
 
 
40-54 
 
 
 
55-64 
 
 
 
65+ 
 
 
 
 
 
  
 
 
 
 
Demographic and Other Baseline Characteristics 
Demographic and other baseline characteristics will be summarized by age and overall using 
the FAS and the EAS. No statistical test will be performed for comparison of any baseline 
measurement by age group. 
All summaries of continuous characteristics will be based on non-missing observations and 
the percent of participants missing values will be reported. For categorical characteristics, 
percents will be calculated out of the total number of participants in the data set, overall and 
by treatment group (i.e., each denominator includes the number of participants with 
missing/unknown values for the variable), where the percentage missing will also be reported. 

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Table 2 
Summaries of Demographic and Other Characteristics at Baseline.     
Characteristic 
Summarized as  Categories 
Age 
Categorical and 
Continuous 
<40, 40-54, 55-64, >= 65 years 
Gender 
Categorical    
Female 
Male 
Non-binary 
Race 
Categorical 
White 
Hispanic, Latino, or Spanish origin 
Black or African American 
Asian 
American Indian or Alaska Native 
Middle Eastern or North African 
Native Hawaiian or other Pacific Islander 
Some other race, ethnicity, or origin 
Prefer not to respond 
BMI 
Categorical and 
Continuous  
<30 kg/m2 and ≥30 kg/m2   
Medical History 
Categorical 
Hypertension 
Diabetes mellitus 
Myocardial infarction 
Heart failure 
Stroke or transient ischemic attack 
Peripheral arterial disease 
Average number of 
cigarettes smoked per 
day 
Categorical 
None 
1-10 
11-20 
21-40 
41 or more 
Rather not say 

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Average number of 
alcoholic beverages 
consumed per week 
Categorical 
Less than 1 
1-5 
6-9 
10 or more 
Rather not say 
 
 
Medications  
Medications reported during study visit 1 will be summarized using the FAS by drug category 
or generic drug name by age group.  
Drug Category or 
Name 
N 
Responding 
% 
Responding 
(of FAS) 
% 
Responding 
(of NAS) 
N on Medication(%)* 
Beta blockers 
 
 
 
 
Calcium channel 
blockers 
 
 
 
 
Aspirin 
 
 
 
 
Anticoagulants 
 
 
 
 
 
* Percent calculated as percent of participants who responded to whether they used the 
corresponding drug type. 
 
4.3 Analysis Methods  
Analysis of the Co-primary Endpoint Addressing Objective 1 
We have designed the study to estimate the proportion of participants age 65 or older 
diagnosed with AF within a 0.10 confidence interval width. This proportion will be estimated 

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as the number of participants who receive an IPN and have AF confirmed via adjudication of 
the ambulatory ECG monitoring divided by the number of participants who receive an IPN 
and who have analyzable ECG patch data. In other words, we have designed the study so the 
97.5% confidence interval around the probability of AF diagnosis among those 65 and older 
who receive a notification will have a width of 10%. Our analysis set will be the participants 
65 or older in the EAS. We will repeat the analysis to include participants of all ages in the 
EAS to address Objective 1b. 
 
 
N EAS 
N IPN and AF diagnosis  IPN and AF diagnosis/EAS  
97.5% CI  
65+ 
 
 
 
 
 
 
 
There is no hypothesis testing for the co-primary objectives. We use 97.5% confidence 
intervals to account for having two primary objectives. 
Analysis of the Co-primary Endpoint Addressing Objective 2 
We assume that each tachogram measured on a participant is independent of other intervals 
measured from that participant. In sensitivity analyses, we will evaluate the impact of this 
assumption. From the available intervals, we will sample intervals as follows:   
1. Randomly sample 10 intervals per participant in the EAS to ensure each participant 
contributes a comparable period of data on which to evaluate concordance. We ignore 
whether the tachograms are positive or not in this step. All intervals will be selected in 
participants who have fewer than 10 intervals available.  
2. Sum the number of positive tachograms sampled. 
a. Sample from the unsampled positive tachograms until that participant has 25 
positive tachograms or until all positive tachograms for that participant have 
been sampled if that participant has less than 25 positive tachograms. 
3. Sample 1 silent IPN per participant that contains the full series of >= 5 tachograms and 
select all tachograms corresponding to that silent IPN for adjudication. 
 
This proportion will be estimated as the number of tachograms indicating an irregular rhythm 
where AF is present as confirmed via adjudication of the ambulatory ECG monitoring divided 
by the number of tachograms indicating an irregular rhythm sampled from the period of time 
when the participant provides analyzable ECG patch data.  

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N Irregular 
tachograms 
N Irregular 
rhythm on ECG  
Irregular rhythm on 
ECG/ Irregular 
tachograms  
97.5% CI 
22-39 
 
 
 
 
40-54 
 
 
 
 
55-64 
 
 
 
 
65+ 
 
 
 
 
 
 
 
Secondary and Tertiary Analyses  
 
All secondary and tertiary endpoints will be analyzed as proportions with 95% confidence 
intervals. Endpoints measured using data collected from the ambulatory ECG monitoring will 
be analyzed in the EAS while self-reported contact with a health care provider and initiation 
of therapies or cardioversion will be analyzed in the NAS. The self-reported outcomes (90-day 
after notification of pulse irregularity and end of study PROs) will also be analyzed in the 
NAS and FAS, respectively. Generalized linear regression techniques will be employed to 
evaluate the variation observed in secondary and tertiary endpoints by subgroups described by 
age, race, gender, and family history. 
● Simultaneous ambulatory ECG monitoring indicating an irregular rhythm consistent with 
AF of greater than 30 seconds duration when the IPNA based on multiple tachograms is 
positive for an irregular pulse among those who received a notification. These positive 
IPNA triggers will not result in additional notifications to participant, but will be available 
for analyses.  Each participant contributes one observation. (IPNA+) 
 
 
N EAS 
N IPNA+ Irregular tachogram on 
ECG (within the alert 
timeframe) 
Irregular tachogram on 
ECG (within the alert 
timeframe)/IPNA+ 
95% CI  
22-39 
 
 
 
 
 
40-54 
 
 
 
 
 

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55-64 
 
 
 
 
 
65+ 
 
 
 
 
 
 
 
● Self-reported contact with a health care provider within 3 months following an irregular 
pulse notification. (PCP PRO after IPN) 
 
N NAS 
N Self-reported 
contact 
Self-reported 
contact/NAS 
95% CI 
22-39 
 
 
 
 
40-54 
 
 
 
 
55-64 
 
 
 
 
65+ 
 
 
 
 
●  
 
4.4 Tertiary Endpoints  
● An indicator for the presence of arrhythmias other than AF detected on ambulatory ECG 
monitoring that can also result in an irregular pulse. Arrhythmias considered include sinus 
arrhythmia, frequent premature atrial contractions (PAC), frequent premature ventricular 
contractions (PVC), intermittent heart block, multifocal atrial tachycardia, and atrial 
tachycardia with variable conduction. Definitions of each arrhythmia are provided in 
Section 4.4. (ARR after IPN) 
 
 
N EAS 
N ARR on 
ECG 
N Alerts 
Alert/ARR on 
ECG  
95% CI  
65+ 
 
 
 
 
 
 
 
● AF of greater than 6 minutes, 1 hour, 6 hours, and 24 hours duration detected on 
ambulatory ECG monitoring following an irregular pulse watch notification. (AFtime after 
IPN) 

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● Self-reported initiation of therapies for AF, including anticoagulant, rate-controlling and 
anti-arrhythmic therapy. (therapies) 
● Self-reported electrical or chemical cardioversion by a health care provider. 
(cardioversion) 
 
 
Sensitivity and Sub-analyses  
As a sensitivity analysis, a per-protocol analysis will be performed for the primary endpoints 
excluding participants with protocol deviations. 
 
Proportions along with 97.5% confidence intervals will be used to analyze the co-primary 
objectives and will be presented separately by age (<40, 40-54, 55-64, 65+), sex, race, medical 
history, type of AF, and non-AF irregular rhythms. Frequency of notifications will be 
estimated separately by age, sex, race, and medical history in the FAS. These analyses will 
also be performed on participants of all ages combined. 
 
To better understand the performance of the IPNA across the participant population, we will 
perform a subgroup analysis to understand the proportion estimated in Objective 1a and 1b 
according to the burden of AF. We will consider three approaches to split the participants into 
tertiles, each capturing AF burden or a related measure.  
● We will split the participants into tertiles based on AF burden obtained from their 
ambulatory ECG monitoring.  
● We will calculate each participant’s PPV by calculating the proportion of their 10 
sampled positive tachograms that are concordant with the ambulatory ECG monitoring 
and split the participants into tertiles according to the PPV calculated. 
● We will split the participants into tertiles based on the time until AF appears on their 
ambulatory ECG monitoring.  
For each approach, we will construct separate 95% confidence intervals around the probability 
of being diagnosed with AF in each tertile. These analyses will help us to understand how the 
estimates addressing Objective 1a and 1b differ according to AF burden. 
 
We will summarize the self-reported contact with a health care provider, use of subsequent 
therapies for AF, and reason for not following up with a health care provider within 3 months 
after notification among participants who receive a notification but do not receive an ePatch. 
 
To understand the sensitivity of our findings to the assumptions about missing data due to 
short wear times, we will vary the requirement that participants with less than 1 hour of wear 
time be considered as missing their ECG data. We will conduct additional sensitivity analyses 
considering the following alternative minimum wear times: 6 hours, 1 day, 2 days, and 5 days. 
Such analyses may provide insight into whether performance of the IPNA varies by a minimal 

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observational time, which may or may not have a correlation to characteristics of clinical 
relevance including burden of AF. 
 
To evaluate the uncertainty introduced by sampling tachograms in the co-primary endpoint, 
we will perform additional analyses to understand the variability in the estimated confidence 
intervals across various samples. Because only sampled tachograms will be adjudicated by 
clinicians, we will use the results of the BioT overreads in place of the adjudicated results. We 
will repeat the tachogram sampling in 10,000 bootstrap resamples and calculate the 
confidence interval in each replicate to generate a distribution of confidence intervals based on 
the resamples. We will graphically display the distribution of confidence intervals and will 
summarize the upper and lower bounds of the confidence intervals to characterize the 
uncertainty in our estimated confidence intervals. 
 
Adverse Events 
A participant will be counted once for a reported AE even if the participant had multiple 
occurrences of that AE. We will summarize the proportion of participants reporting anxiety in 
the FAS and the NAS and will summarize the proportion of participants reporting rash in the 
NAS and EAS. AEs reported with an action taken of “Investigational product permanently 
stopped” will be summarized by age group and overall in participants who receive 
notifications, in participants who do not receive notifications, and overall. All AEs will be 
collected; however, these AEs are of most interest to the study device (anxiety) and are 
highest risk in the study (rash).  
 
 
N FAS 
% FAS 
N NAS 
% NAS 
#AEs Anxiety 
 
 
 
 
#AEs Rash 
 
 
 
 
 
 
The participant incidence of all serious adverse events will be presented for each analysis set 
by age group and overall.  

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N SAEs 
N unique 
participants with 
SAEs 
SAEs/participants with 
SAEs 
22-39 
 
 
 
40-54 
 
 
 
55-64 
 
 
 
65+ 
 
 
 
Overall 
 
 
 
 
 
 
Analysis of Fall-Out Subgroup 
The fall-out subgroup (a subset of the NAS) will include participants who received a 
notification, but provide incomplete data for various reasons or delay in providing data. The 
reasons for inclusion in the fall-out subgroup are: 
 
● Failure to call Study Telehealth Provider within 30 days after notification. 
● Urgent symptoms discovered during Study Visit #1 virtual medical evaluation by 
Study Telehealth Provider requiring immediate direction to EMS (urgent care clinic or 
emergency room) for medical care. 
● Failure to return an ePatch within 45 Days after Visit #1. 
 
We will estimate the proportion who self-report contact with a health care provider within 3 
months after notification and subsequent therapies for AF in the fall-out subgroup. 
Furthermore, we will summarize the self-reported reasons for not following up with a health 
care provider in the fall-out subgroup. 
Analysis to Determine Minimum Requirements for Wear Time of the ePatch  
An analysis will be conducted to identify the minimum amount of wear time of the ePatch 
required to identify most cases of AF. For all participants positively determined to have AF 

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during their observation time via ePatch, we will graphically depict the time at which AF was 
first detected over time. In addition, for all patients with an IPN in the EAS, time to AF will 
be derived as a right-censored variable where the variable is equal to the minimum of the time 
until the first AF event or the length of time the ambulatory ECG patch is worn. Participants 
who do not have any AF events during their patch wear time will be right-censored at the end 
of their patch wear.  
Our objective will be to identify the amount of wear time needed to capture 90% of AF events 
occurring during the 7 day wear period. To that end, we will graphically depict the AF-free 
curve using Kaplan-Meier methods. The time when 90% of AF events have occurred will be 
estimated from the curve along with a 95% confidence interval calculated using Greenwood’s 
formula. 
Device Sensitivity Analysis 
We will perform an analysis to estimate the sensitivity (i.e. the true positive rate) of the device 
in detecting irregularities consistent with AF. In the analysis, we will estimate the proportion 
of participants who have an IPNA positive for an irregular rhythm consistent with AF during 
the period when they are undergoing simultaneous ambulatory ECG monitoring among 
participants with AF confirmed by ECG. These positive IPNA triggers will not result in 
additional notifications to participant, but will be available for analyses.  Each participant 
contributes one observation in this analysis. We expect that the device sensitivity may be low. 
The low sensitivity is expected because tachograms are retrieved only when available from the 
Apple Watch platform; the Heart Study app does not have the ability to control the collection 
and storage of tachograms and relies on the platform to do this. 
 
4.5 Definitions  
 
Irregular Arrhythmias 
AF is defined as irregular QRS complexes with no clearly discernible p-waves lasting 30s or 
more ever during the ECG monitoring. In tertiary analyses, we consider definitions requiring 
longer periods of AF, up to 24 hours.  
Sinus arrhythmia is defined as a beat-to-beat variation lasting at least 120ms with discernible 
sinus p-waves ever during the ECG monitoring. 
Frequent PACs are defined as p-waves that are observed before the predicted time interval. A 
participant is considered to have frequent PACs if they average 30 or more PACs/hour during 
the ambulatory ECG monitoring.  

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Frequent PVCs are defined as wide QRS complexes without preceding p-waves. A participant 
is considered to have frequent PVCs if their (total number of PVCs/total number of 
beats)*100% is ≥ 5% and very frequent PVCs if ≥ 15% during the ambulatory ECG 
monitoring. (See the next subsection for criteria used to indicate presence of PACs and PVCs 
at the tachogram-level.) 
Intermittent heart block is defined as the presence of p-waves that are not followed by a QRS 
complex and are not preceded by a gradually prolonging PR interval. No minimum amount of 
time is required. 
Multifocal atrial tachycardia is defined as an irregular, narrow complex tachycardia with 
discernable preceding p-waves preceding the QRS complex that are of at least two different 
morphologies, lasting at least 30 seconds. 
  
Atrial tachycardia with variable conduction is defined as an irregular narrow complex 
tachycardia with one predominant p-wave morphology lasting at least 30 seconds.  The p-
waves are followed by QRS complexes with varying ratios, from one QRS for every p-wave, 
to one QRS for multiple p-waves.  The p-waves are a distinct morphology from typical flutter 
waves.  
  
Tachogram Level Concordance 
For AF, the ambulatory ECG monitoring will be considered to be concordant with a positive 
tachogram if there is at least 30 seconds of AF observed on the ambulatory ECG monitor 
during the tachogram and the 1 minute recorded before and after the tachogram. The 
participant-level definition described above for sinus arrhythmia, intermittent heart block, 
multifocal atrial tachycardia, and atrial tachycardia with variable conduction will be applied to 
the period of ambulatory ECG monitoring during the tachogram and the 1 minute recorded 
before and after the tachogram. The 1 minute buffer is to ensure that clock drift between the 
Watch and ECG patch does not invalidate the “simultaneous” nature of the comparison. 
For frequent PACs, the ambulatory ECG monitoring will be considered to be concordant with 
a positive tachogram if there are 3 or more PACs observed on the ambulatory ECG monitor 
during the tachogram and the 1 minute recorded before and after the tachogram. For frequent 
PVCs, the ambulatory ECG monitoring will be considered to be concordant with a positive 
tachogram if there are 3 or more PVCs observed on the ambulatory ECG monitor during the 
tachogram and the 1 minute recorded before and after the tachogram. Very frequent PVCs 
occur when 9 or more PVCs are observed. 
Tachogram level concordance will only be estimated for participants who began wearing the 
ECG patch within 14 days of shipment so that clock drift between the Watch and ECG patch 

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does not exceed the 1 minute buffer described above and invalidate the “simultaneous” nature 
of the comparison. 
Notification Level Concordance 
The ambulatory ECG monitoring will be considered to be concordant with a positive IPNA if 
30 seconds of AF is observed on the ambulatory ECG monitor during any of the 5-6 
tachograms recorded during the period triggering the notification and the 1 minute recorded 
before and after each of the tachograms. 
4.6  Handling of Missing Data  
 
In analyses where the endpoint is measured using data collected from the ambulatory ECG 
monitoring, participants who have at least one hour of analyzable wear time during the 
simultaneous ECG monitoring will be included in the analyses (EAS). We will use any 
available tachograms and no data will be considered missing.   
 
Multiple imputation methods will be used in the analyses of patient reported outcomes to 
account for an expected small proportion of participants who do not complete all questions. 
 
4.7  Potential Limitations and Mitigation Strategies  
 
We have identified several potential limitations in our planned analyses and have planned 
various sensitivity analyses and alternate approaches to understand and mitigate the impact of 
these limitations on our findings. The ePatch is not worn at the time of the initial notification 
and we may not detect AF on the subsequent ambulatory ECG monitoring, particularly in 
participants with low burden AF. We additionally expect that some participants will wear their 
ePatch for a period shorter than 7 days. We acknowledge that several factors may contribute 
to an overestimated or underestimated proportion of the true AF in participants who receive an 
irregular pulse notification. We describe above sensitivity analyses to evaluate the sensitivity 
of our estimate to the minimum wear time for inclusion in the analysis (described in Section 
4.3). 
 
In particular, we anticipate several biases that may impact the estimate of the true PPV.  
 
• Patch Wear Bias: We anticipate that not all participants will wear their patches for the 
full 7 day wear period. We acknowledge that wear periods shorter than 7 days and a 
study design where the ePatch is worn during a period that follows the initial 
notification (and not simultaneously) will likely contribute to an underestimated true 
proportion of AF in participants who receive an IPN because the AF that triggered the 
initial notification may not be detected during the subsequent ambulatory ECG 

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monitoring. To evaluate the degree that the true proportion may be underestimated, we 
will compare the proportion of patients with AF as estimated in Objective 1a and 1b 
(the first primary endpoint below) with the proportion of concordant intervals as 
estimated in the first secondary endpoint. Furthermore, we will evaluate the sensitivity 
of our estimates addressing Primary Objectives 1 and 2 to the minimum wear time for 
inclusion in the analysis (described in Section 4.3).  
 
• Missing Data Bias: For some participants, the IPN will occur but no subsequent 
analyzable ECG monitoring data will be available (e.g., participant requires urgent 
care, participant doesn’t return patch).  Because these participants will not provide 
ambulatory ECG monitoring data, they will not be included in analyses to estimate the 
proportions in Primary Objectives 1 and 2 . Their exclusion may bias the estimates up 
or down. Participants who require urgent care are presumably more likely to have AF 
and their exclusion would lead to an underestimate. On the other hand, participants 
who do not return patch may be less sick and their exclusion would result in an 
overestimate of the proportion of participants with AF. This bias is an inherent 
limitation of an observational study. 
 
• Observation Period Bias: It is possible that participants may receive an IPN but the 
subsequent ECG monitoring may not be of sufficient length to observe AF. If this bias 
is present, we would expect to see the Kaplan-Meier plot in the analysis to determine 
minimum requirements for wear time of the ePatch continue to increase through the 
maximum wear time observed (as opposed to a Kaplan-Meier plot that plateaus prior 
to the maximum wear time observed). 
 
• Spectrum Bias: Varying lengths of watch wearing across participants could lead us to 
identify more paroxysmal than persistent AF. In a tertiary analysis, we aim to 
understand the sensitivity of our findings to the definition of AF based on observing at 
least 60 seconds of AF. We consider AF lasting at least 6 minutes, 1 hour, 6 hours, and 
24 hours as alternative definitions. 
 
• Gold Standard Bias: It is possible that an IPN may occur during the simultaneous 
ambulatory ECG monitoring but the ECG incorrectly indicates no AF is present. We 
aim to mitigate this bias by using an FDA-cleared device and implementing a clinical 
adjudication process to over-read both the ePatch report and individual tachogram 
time-point on the raw ECG data.  
 
Analyses performed at the tachogram level assume that the tachograms within the same 
participant are independent; however, this assumption may be violated because the 
tachograms are samples from an underlying process. We will evaluate our assumption of 
independence using the Wald-Wolfowitz run test to evaluate whether the sequence of positive 
tachograms within participants is longer than expected. If the test indicates that the 

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assumption may be violated (as indicated by a p-value less than 0.05), we will consider 
alternate methods to account for the non-independence of tachograms, including statistical 
methods that incorporate the correlation within a participant and a sampling approach to select 
tachograms that are farther apart in time and hence expected to be less correlated.  
5. INTERIM CHECKS 
A series of interim checks will be performed.  
 
Throughout the course of the study, we will check the number of irregular pulse watch 
notifications occurring per age subgroup. If a high number of notifications is observed (greater 
than 10%), enrollment may be paused or throttled downward in any age subgroup (<40, 40-54, 
55-64, ≥65), as informed by the empirical findings. If the number of notifications observed is 
less than the study infrastructure capacity, the numbers of participants invited to enroll from 
the “waiting period” may be increased. 
 
 
N FAS 
N IPN 
Alert Rate (IPN/FAS) Greater than 
10%? 
<40 
 
 
 
 
40-54 
 
 
 
 
55-64 
 
 
 
 
65+ 
 
 
 
 
 
 
 
An interim check will be performed upon completion of the first 100 ambulatory ECG 
monitors in each of the four age subgroups. The interim check will be performed for each 
subgroup regardless of how many patches are received in other age subgroups. We estimate 
the first check to occur at approximately 6-8 weeks after the first participant enrolled to check 
the following: 
 
1) At least 50% of participants notified of an irregular pulse are ultimately wearing and 
returning the ambulatory ECG monitor.  A low rate of ambulatory ECG monitor use would 
result in an increase in the rates of invitations to enrollment in any age subgroup. 
 

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2) Percentage of AF noted on ambulatory ECG monitoring is greater than 1%.   A detection of 
AF less than 1% will prompt a cessation of enrollment in any corresponding age subgroup.  
 
3) Percentage of non-clinically relevant irregular rhythms is greater than 90%. If the vast 
majority of rhythms detected on ambulatory ECG monitoring are due to other irregular, non-
AF arrhythmias, such as sinus arrhythmia, frequent PACs and frequent PVCs, this will prompt 
a cessation of enrollment in any corresponding age subgroup. 
 
The co-primary endpoints will be evaluated after at least 503 participants aged ≥65 have at 
least 1 hour of ambulatory ECG monitor data recorded, i.e. at least 503 participants who are in 
the EAS.  
 
N 
EAS 
N 
IPN 
N AF 
diagnosis 
IPN and AF 
diagnosis/EAS 
(97.5% CI) 
N 
Irregular 
rhythm 
on ECG 
N Irregular 
tachograms 
Irregular 
rhythm on 
ECG/# 
Irregular 
tachograms 
(97.5% CI) 
22-39  
 
 
 
 
 
 
40-54  
 
 
 
 
 
 
55-64  
 
 
 
 
 
 
65+ 
 
 
 
 
 
 
 
 
 
 
 
These analyses are designed to maintain trial integrity and patient safety and not designed to 
evaluate ultimate efficacy or futility and do not impact the Type I error as we will not be 
examining the positive predictive values of the co-primary endpoints using this interim 
analysis. 
 
A much higher than anticipated rate of notifications and subsequent ePatch evaluations may 
result in marginal benefit of additional participant enrollment. The following will be set as 
maximum targets for ePatch monitoring.  Exceeding these limits will trigger either a throttling 
downward or cessation of enrollment: 
 

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1) Completion of 5,000 ePatches in total in either participants ≥ 65 or participants aged 
22-64 will result in cessation of enrollment in the corresponding age group. 
2) Completion of  > 100 ePatches per week in either participants ≥ 65 or participants aged 
22-64 will result in a throttling downward of enrollment invitations in the 
corresponding age groups. 
 
6. VALIDATION PLAN 
6.1  Reproducibility Plan on Sub-Study Analysis 
 
Stanford will follow the methods described in the AHS Sub-Study SAP (SSSAP) with the 
goal of reproducing Apple’s results using the data collected per the AHS Sub-Study Protocol. 
The Sub-Study is limited to the sub-study participants as of approximately June 22, 2018. This 
reproducibility plan encompasses all primary and secondary endpoints described in Section 5 
of the SSSAP (primary efficacy endpoint, secondary efficacy endpoint, and the primary safety 
endpoint). 
The reproduction will include reproducing the sampling of the tachograms. Apple will provide 
Stanford with the seed used to generate the pseudorandom numbers used to select the sampled 
tachograms. Stanford will apply the seed to the data provided by Apple to check that the 
tachograms sampled match the sample used by Apple in the Sub-Study analysis. Apple will 
provide Stanford with the sampled tachograms used by Apple in the Sub-Study analysis for 
verification.  
Next, we will compare 1) the number of tachograms classified as AF according to the spot 
tachogram algorithm and 2) the number of tachograms classified as AF by both the spot 
tachogram algorithm and the paired ECG strip is classified as AF. If both of these counts 
match, the PPV has been reproduced. If either count does not match, Stanford will share the 
list of tachograms identified as being AF by the spot tachogram algorithm and in the paired 
ECG strips with Apple to identify the source of the discrepancy. This process will be repeated 
for the secondary efficacy endpoint looking at the PPV of the alerts. 
Next, a 97.5% lower confidence bound will be calculated for the primary efficacy endpoint of 
spot tachogram-level PPV for AF following the methods outlined in Section 9.3 of the 
SSSAP. If the lower bound for the spot tachogram-level PPV exceeds 70%, the null 
hypothesis described in the SSSAP will be rejected. For the PPV of the alerts, a two-sided 
exact 95% confidence interval will be computed per Section 9.3 of the SSSAP. Stanford will 

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compare all confidence interval bounds and the results of the hypothesis test with Apple. If 
any discrepancies are found, the two groups will discuss to identify the discrepancy.  
Finally, the number of serious adverse device events (ADEs) and the number and percent of 
participants experiencing ADEs will be calculated. If any of the counts or the percent do not 
match, Stanford will share their list of ADEs and participants experiencing ADEs with Apple 
to identify the source of the discrepancy. 
 
6.2 Replication on Final AHS Study Data  
 
Stanford will repeat the analyses described in the reproducibility plan using the final Apple 
Heart Study data set. The results of the analyses will be compared with the results based on 
the adjudicated patches received by approximately June 22, 2018. If discrepancies are found, 
the results will additionally be displayed separately using data obtained before and after June 
22, 2018 to demonstrate the difference between the two time periods. 
The results will also be compared with the results obtained using the methods described in 
earlier sections of this SAP. If a discrepancy is observed here, additional investigations will be 
undertaken to identify the methodological source of the discrepancy between the two 
approaches. 
A1. APPENDIX: AHS SUB-STUDY PROTOCOL AND SAP