ST Monitoring to Detect ACS Events in ICD Patients
Phase: NA
Conditions: Coronary Artery Disease
Sponsor: Abbott Medical Devices

Clinical Investigation Plan Cover Page 
87173 CIP Posting Cover Page Ver B 
Template 
Page 1 of 1 
NCT Number: NCT01424722 
Analyze ST 
ST Monitoring to Detect ACS Events in ICD Patients 
Study Document No: 60026829 
Version J 
Date: 25-Feb-2013 
Sponsor 
St. Jude Medical, Inc. 
15900 Valley View Court 
Sylmar, CA 91342 
USA 

Statistical Analysis Plan 
Cardiac Rhythm Management Division 
STATISTICAL ANALYSIS PLAN 
FOR THE
ST MONITORING TO DETECT ACS EVENTS
IN ICD PATIENTS STUDY 
(Analyze ST)
February 5, 2013 
60027109/J Clinical 
2009, St. Jude Medical, CRMD.  All rights reserved.  No portion of this work may be reproduced in whole or in part without the 
express written permission of St. Jude Medical, CRMD 

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1.0 
INTRODUCTION 
This document contains the statistical analysis plan for the Analyze ST IDE study using St. 
Jude Medical ICD systems.  The Analyze ST study will include the following device models: 
Fortify® ST family of devices
Fortify Assura® St family of devices
Ellipse® family of devices
These devices will be collectively referred to as the Investigational Devices except where 
otherwise specified. All analyses will be carried out on the study endpoints as well as on 
additional data specified in this document.  
2.0 
PURPOSE 
The intent of this study is to demonstrate the safety and effectiveness of the diagnostic ST 
Monitoring Feature in the Investigational Devices.  Effectiveness of the device will be 
evaluated by analyzing the sensitivity of the ST Monitoring Feature to detect clinical events. 
In addition, safety of the ST Monitoring Feature will be evaluated by demonstrating a low 
percentage of patients with false positive events. 
3.0 
INVESTIGATIONAL PLAN 
3.1 Study Design and Patient Follow-up 
This is a prospective, non-randomized, multicenter, pivotal IDE study evaluating the 
Investigational Devices with the ST Monitoring Feature.  The Analyze ST study is 
designed to demonstrate the safety and efficacy of the ST Monitoring Feature in the 
Investigational Devices.  The sensitivity of the ST Monitoring Feature for detecting 
acute coronary syndrome events will be the primary efficacy endpoint.  The primary 
safety endpoint will be assessed by reporting the percentage of patients who 
experience a false positive detection during the 12 months following a 3 month run-
in period. 
The goal of the 3 month run-in period is to: 
1. Identify patients whose EGM rhythm or morphology is unsuitable for chronic
ST monitoring 
2. Provide data collection for review in order to adjust or optimize ST feature
parameters 
Data collection for the purposes of the FDA market approval application will be 
considered to be complete when the primary safety endpoint data are available and at 
least 41 clinical events have occurred.  It is estimated that up to 5,228 patients at 

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approximately 200 centers will be enrolled in the study with a follow up of 12 months 
to meet the primary study endpoints. 
A flow diagram of the study design is below. 

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Study Flow Diagram 

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3.2 Clinical Event Description and CEC Adjudication 
Three types of events are defined in the sections below.  All clinical events will be 
adjudicated by a Clinical Events Committee (CEC) consisting of a blinded panel of 
independent experts. Once the CEC adjudicates the Clinical Events, and per defined 
criteria in section 3.2.2, all Type I ST episodes will be classified as either False 
Positive or True Positive events.  In addition, any Clinical Event that was not 
associated with a Type I ST episode detection will be classified as either False 
Negative or True Negative. 
3.2.1 Clinical Event Committee 
The CEC will include at a minimum, 2 interventional cardiologists and 2 
electrophysiologists.  Physicians on the CEC will not participate in the study 
as investigators and when reviewing events will be blinded to any patient or 
site information.  The purpose of the CEC is to adjudicate all clinical events. 
Specifically: 
Classify clinical events as either an Acute Coronary Syndrome (ACS)
Event, a Precursor Event, or a Non Event.  Non Events will be further 
classified as either a Transient Ischemic Event or a Non Ischemic 
Event.  Review all deaths, and adverse events associated with 
diagnostic testing or procedures performed as a result of a Type I ST 
Episode Detection and determine relationship to system and/or 
procedure. 
Review all baseline surface ECGs to determine the presence or
absence of any conduction abnormality. 
Review all complications and all cardiovascular related adverse events
3.2.2 Clinical Events 
ACS Events 
An ACS event is defined as any of the following: 

Death due to a myocardial infarction

A new Q-wave myocardial infarction on 12-lead ECG

ST elevation myocardial infarction

Biomarker evidence of acute myocardial damage*

Evidence of new plaque rupture by invasive testing (i.e., IVUS) as
adjudicated by the blinded Clinical Events Committee

The presence of TIMI myocardial perfusion grade 0 or 1 consistent with
acute injury of the myocardium from embolization

New surface ECG ST depression or elevation treated with thrombolytic
medication

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
New surface ECG ST depression or elevation with new or progressive
flow-limiting ischemia proven by non-invasive or invasive testing.

Angiographic stenosis ≥70% adjudicated by the blinded Clinical Events
Committee as flow-limiting.

An event that leads to a clinically warranted percutaneous coronary
intervention (PCI) or revascularization as determined by the blinded
Clinical Events Committee.  Clinically warranted is defined as:
o
Angiographically visualized stenosis ≥70% correlating with the
vascular distribution in which a 12-lead surface ECG documents
changes consistent with ischemia or injury in 2 or more contiguous
leads
o
Angiographically visualized stenosis ≥70% correlating with a
vascular distribution shown to have ongoing ischemia by non-
invasive stress testing
o
New or progressive angiographically visualized stenosis ≥70%
correlated with new or progressive anginal symptoms
*NOTE: It is recommended that the “Universal Definition of Myocardial
Infarction” proposed by the Joint ESC/ACCF/AHA/WHF in 2007 be used to 
determine myocardial damage. 
Precursor Events 
A precursor event is defined as clinical symptoms of an impending ACS event 
followed by an ACS event within 10 days. Precursor events alone do not meet 
the ACS event criteria. Multiple precursor events may precede a single ACS. 
All precursor events will be adjudicated by the Clinical Event Committee 
(CEC). Symptoms identified as precursors will be grouped with the 
subsequent ACS event and counted as a single event. Individual precursor 
events will not be included in the statistical endpoint analysis.  
Non Events 
Non Events are defined as any clinical event that does not meet the criteria of 
an ACS Event or a Precursor Event.  These events will be adjudicated by the 
CEC and will be further classified as either Transient Ischemic Events or as 
Non Ischemic Events. 
3.2.3 Classification of Events 
True Positive (TP):  A Type I ST episode detection that occurs up to 72 
hours prior to an ACS Event. 
False Positive (FP):  A Type I ST episode detection that occurs more than 72 
hours prior to an ACS Event or that occurs in the absence of a true ACS 
Event. 

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True Negative (TN):  Absence of a Type I ST episode detection during a Non 
Event. 
False Negative (FN): Absence of a Type I ST episode detection within 72 
hours prior to an ACS Event. 
3.3 Patient Selection 
3.3.1 Inclusion Criteria 
Eligible patients will meet all of the following: 
1. Have an indication for an ICD implantation or pulse generator change
2. Have documented coronary artery disease. Documented coronary artery
disease is defined as having at least one of the following present a)
evidence of a prior MI on ECG and/or cardiac enzymes, b) prior
revascularization (by coronary artery bypass grafting or percutaneous
coronary intervention) c) angina and/or ST-T wave abnormalities
indicative of ischemia on exercise stress test, nuclear stress test, or echo
stress test, or d) coronary artery disease diagnosed by coronary
angiography.
3. Willing and able to comply with protocol requirements, including keeping
all required visits
4. Willing to participate in the study and able to sign an IRB approved
informed consent form
5. Willing and capable of using Merlin@home.
6. Be at least 18 years of age when enrolled in the study
3.3.2 Exclusion Criteria 
Patients will be excluded if they meet any of the following: 
1. Are pacemaker dependent (defined as a need for ventricular pacing ≥ 20%
of the time)
2. Have NYHA Class IV Heart Failure
3. Have persistent or permanent atrial fibrillation
4. Have a known history of intermittent Bundle Branch Block
5. Pregnant or planning a pregnancy during the study participation
6. Have a life expectancy of < 1 year due to any condition
7. Are currently participating in a clinical investigation that includes an
active treatment arm

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3.4 Device Description 
 
The SJM ICD system is intended to provide ventricular anti-tachycardia pacing and 
ventricular defibrillation for automated treatment of life-threatening ventricular 
arrhythmias.  AF Suppression™ pacing is indicated for suppression of paroxysmal or 
persistent atrial fibrillation in patients with the above ICD indication and sinus node 
dysfunction.  In addition, the Investigational Devices have an ST Monitoring Feature 
that has the ability to detect ST shifts, and to record and store the associated high 
fidelity IEGMs during those shifts.  Refer to the User’s Manual for more details. 
 
The pulse generator, along with compatible leads, constitutes the implantable portion 
of the ICD system. 
 
3.5 Evaluation of Safety 
3.5.1 Preliminary Safety Assessment Phase 
An initial assessment of the proportion of patients free from complications 
due to unnecessary procedures resulting from false positive events will be 
conducted on the first 500 patients to complete 6 months of follow-up. 
 
3.5.2 Primary Endpoint 
The primary safety endpoint will evaluate the percentage of patients 
experiencing false positive events with the use of the ST Monitoring Feature.   
 
3.5.3 Secondary Endpoint 
The secondary safety endpoint will evaluate the False Positive Rate (FPR) of 
the ST Monitoring Feature. 
 
3.6 Evaluation of Efficacy 
3.6.1 Primary Endpoint 
The primary efficacy endpoint will evaluate the sensitivity of the ST 
Monitoring Feature to detect clinical events. 
 
4.0 
STATISTICAL METHODS 
4.1 Randomization and Blinding 
This is a prospective, non-randomized, multicenter, pivotal IDE study evaluating the 
Investigational Devices with the ST Monitoring Feature. 
 

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4.2 Data Safety and Monitoring Board 
In order to ensure patient safety throughout the study, an independent DSMB will 
oversee the course of the study.  The DSMB will periodically review safety data 
(percentage of patients with false positive events, False Positive Rate, and study-
related adverse events), false negative events, and any procedures/hospitalizations 
resulting from false positives, even if they do not result in complications.  The 
DSMB will provide a recommendation regarding continuation of the study to the 
Chairman of the Steering Committee for the study, who will in turn inform the 
sponsor.  A copy of any written communication from the DSMB to the Sponsor 
regarding recommended changes to the study status, procedures or to the Informed 
Consent Form will be provided to the FDA during the annual report.  If the DSMB 
recommends substantive changes to the protocol, these communications will be 
provided along with the applicable IDE supplement.  The DSMB will also be 
informed of the Preliminary Safety Assessment and will be provided with the results 
when the report is submitted to the FDA.  The DSMB will consist of at a minimum 2 
cardiologists, 1 electrophysiologist, and 1 statistician.  In order to prevent bias, the 
DSMB committee members will not participate in the study as investigators. 
4.3 Analysis of Safety 
4.3.1 Preliminary Safety Assessment Phase 
An initial assessment of the proportion of patients free from complications 
due to unnecessary procedures resulting from false positive events will be 
conducted on the first 500 patients to complete 6 months of follow-up.  In 
patients with an upgraded Fortify ST device, the 6 months of follow-up 
begins with either their Baseline visit or the Baseline Upgrade visit (during 
which the firmware upgrade occurs).  In patients with Fortify Assura ST and 
Ellipse ST, the 6 months of follow-up begins with the Baseline visit.  For 
those patients with Fortify Assura ST and Ellipse ST, the survival time for 
patients who experience a complication will be calculated as the number of 
days from the Baseline visit (when the Patient Notifier is activated) to the date 
of the procedure-related complication.  For those patients with Fortify ST 
devices, the survival time will be calculated as the number of days from either 
the Baseline visit or the Baseline Upgrade visit (i.e., whichever visit the 
patient received the firmware upgrade) to the date of the procedure-related 
complication is first discovered.  For patients who withdraw without 
experiencing a complication prior to analysis, their survival time will be 
censored at the date of withdrawal.  For patients who have not experienced 
complications at the time of analysis, their survival time will be censored on 
the date of the analysis. 
All patients who have the Patient Notifier turned ON at the Baseline visit or 
the Baseline Upgrade visit and have completed their 6-month follow up visit 
or 6 months of follow up since being upgraded will be included in this 
analysis. 

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Complications related to unnecessary procedures resulting from false positive 
events are defined as any procedure-related or test-related complications that 
occur in a patient in which a Type I ST episode is classified as a false positive 
according to the criteria described in section 3.2.3. All clinical events will be 
adjudicated by an independent and blinded Clinical Event Committee for the 
purposes of determining whether the event was related to ischemia or acute 
coronary syndrome and whether it was procedure or test related 
Complications related to procedures or tests may include, but are not limited 
to: 

Air embolism

Allergic reaction to contrast media

AV fistula

Bleeding

Cardiac tamponade

Contrast nephropathy

Formation of hematomas or cysts

Infection

Myocardial infarction

Peripheral nerve injury

Pneumothorax

Pseudo-aneurysm

Stent thrombosis

Stroke

Thromboemboli

Venous occlusion

Venous or cardiac perforation
Analysis 

A Kaplan-Meier estimate of the proportion of patients free from
complications arising from a false positive event through the 6 month
follow-up visit will be provided with a 95% lower bound on the estimate
using Greenwood’s formula for the variance of the Kaplan-Meier
estimator.  If no events have been observed, then a Clopper-Pearson 95%
exact lower confidence bound for the proportion of patients free from
complications due to unnecessary procedures resulting from false positive
events will be provided.

A tabular presentation of ER visits, doctor office visits, or any medical
care will be presented, stratified by false positive, true positive and false
negative events.

The proportion of patients with false positive events, with the count of
false positive, true positive and false negative events will be provided.  A
preliminary estimate of sensitivity will be calculated.

The proportion of patients with the ST monitoring feature turned off after
the Programming and Baseline visits will be tabulated along with the
reason for the turning off the ST monitoring feature.

Baseline demographics and site enrollment will be tabulated.

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The above analyses will be presented overall and by the following subgroups:  

Coronary artery disease patients with cardiomyopathy

Coronary artery disease patients without cardiomyopathy

Patients with abnormal baseline ECGs, for each of six abnormal subgroup
categories

Patients with normal baseline ECGs

Patients with arrhythmias

Gender

Patients alerted via Merlin.net and patients alerted via device Patient
Notifier
Additional Analysis 
An analysis will be performed that includes all clinical events using a GEE 
logit-link linear model to estimate the sensitivity with a working correlation 
that provides a robust estimator of the variance adjusting for multiple clinical 
events within patients.   
An empirical analysis will be provided for the sensitivity of the ST 
Monitoring Feature to detect clinical events using the estimator described in 
the Primary Analysis section.  The standard error of this empirical estimate 
will calculated as the standard deviation of a bootstrap distribution.  The 
bootstrap distribution will be constructed using 1,000 bootstrap resamples. 
Each bootstrap resample will be performed at the patient level (in order to 
preserve the correlation structure of multiple events within one patient, if the 
occurs), and each resample will have a total sample size equal to the total 
number of evaluable patients.  A two-sided 95% bootstrap confidence interval 
will be provided. 
4.3.2 Primary Safety Endpoint 
The ST Monitoring Feature will be evaluated by the percentage of patients 
with false positive events. The percentage of patients with false positive 
events is calculated as the number of patients who experience false positives 
divided by the number of evaluable patients. A False Positive occurs when a 
clinical event does not occur within 72 hours following a Type I ST episode. 
The hypothesis is formally expressed as follows:  
H0: Percent of patients experiencing a false positive event in 12 months ≥ 15% 
Ha: Percent of patients experiencing a false positive event in 12 months < 15% 
The desired outcome is to reject the null hypothesis at the 2.5% significance 
level.  The null hypothesis will be rejected at the 2.5% significance level if the 

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upper bound of the 95% confidence interval for the percent of patients 
experiencing false positive events is less than 15%.  The upper confidence 
bound will be calculated using the Wilson score interval method. 
Patient Group 
All enrolled patients who have a successful implant or system revision, 
complete the baseline follow up visit and have the ST Monitoring Feature and 
Patient Notifier turned ON will be included in the evaluation of this study 
endpoint.  Data collection towards the study endpoint will begin after the 
Baseline visit. 
Further, the analysis population for the primary safety endpoint will be those 
subjects with the Fortify ST (upgraded), Fortify Assura ST and Ellipse ST.  
Data from subjects with a Fortify ST device prior to being upgraded will not 
be included in this analysis. 
Analysis 
Primary Analysis 
The primary analysis will be a complete case analysis where patients who are 
lost to follow-up before completing their 12 month visit without experiencing 
a false positive event will be considered non-evaluable and omitted from the 
analysis of the endpoint.  Patients experiencing a false positive event and 
withdrawing before the 12 month visit will be included in the analysis. The 
proportion of patients experiencing false positives will be estimated by the 
number of patients experiencing a false positive event divided by the number 
of evaluable patients.   
Imputation Analysis 
A comparison of baseline characteristics of the subjects with missing data and 
those without missing data will be done to determine if there is evidence that 
the data are not missing at random (it is not possible to determine that data are 
missing at random).  If the missing at random assumption is clearly violated 
by these comparisons, it is usually possible to find a sub-group that are not 
missing at random who have to be imputed differently, such as assigning the 
worst score to patients in the sub-group.  If this resolves the missing at 
random difficulty, the sub groups will be given special scores and the 
remaining patients will be imputed as described above. 
This analysis will use the patients from the complete case analysis to perform 
a logistic regression and an imputation procedure to impute false positive 
status for patients who were non-evaluable in the complete-case analysis. The 
imputations are described as follows: A logistic regression will be performed 
using the complete case patients, with the dependent variable dichotomous 

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false positive status and the independent variables for ischemic 
Cardiomyopathy and each of the four categories of non-ischemic 
Cardiomyopathies (Dilated, Hypertrophic, Restrictive and ARVD), age, 
gender, QRS duration  120ms and EF% at the time of enrollment.  The 
estimates of the coefficients and standard errors of the logistic regression will 
be used as the parameters of a multivariate normal distribution that will define 
the population of the logistic regression model parameters. Up to ten random 
samples logistic model parameters will be selected.  For each random set of 
parameters, the non-evaluable patients will have their false positive status 
imputed as having experienced a false positive if their predicted logistic 
model response is >0.5, and not having experienced a false positive event 
otherwise. These imputed datasets will be created using PROC MI in SAS 
V9.2 or greater.  An analysis of the hypothesis will be carried out for each 
complete imputed dataset, and the results will be combined across datasets to 
obtain one overall conclusion using PROC MIANALYZE in SAS V9.2 or 
greater.   
Additional Analysis 
An empirical analysis will be provided for the proportion of patients 
experiencing false positive events using the estimator described in the Primary 
Analysis section.  The standard error of this empirical estimate will calculated 
as the standard deviation of a bootstrap distribution.  The bootstrap 
distribution will be constructed using 1,000 bootstrap resamples.  Each 
bootstrap resample will be performed at the patient level, and each resample 
will have a total sample size equal to the total number of evaluable patients. 
A two-sided 95% bootstrap confidence interval will be provided. 
Subgroup Analysis 
The analysis of the primary safety endpoint will be performed on the 
following the subgroups of patients 

Coronary artery disease patients with cardiomyopathy

Coronary artery disease patients without cardiomyopathy

Patients with abnormal baseline ECGs, for each of six abnormal
subgroup categories

Patients with normal baseline ECGs

Patients with arrhythmias

Gender

Patients alerted via Merlin.net and patients alerted via device Patient
Notifier
Sample Size 
 
 
 
 
 

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optimize ST feature parameters. The analysis with a 3-month run-in period 
 
 
 
 
   
 
 
 
 
 
 
 
 
 
 
   
 
    
 
 
 
  
 
 
 
 
 
4.3.3 Secondary Safety Endpoint 
The ST Monitoring Feature will be evaluated by the False Positive Rate 
(FPR).  The False Positive Rate is calculated as the number of false positives 
per patient-year of follow-up.  A False Positive occurs when there is a Type I 
ST episode that is not followed by a clinical event within 72 hours.  Only ST 
segment shift events that occur beyond the baseline visit will be included in 
this analysis. 
 
FPR =
up
-
follow
 
of
  
years
patient  
  
events
   
positive
  
false
 
of
 #
 
 
The hypothesis is formally expressed as follows: 
 
H0: Expected FPR ≥1.9 per patient-year of follow-up 
Ha: Expected FPR <1.9 per patient-year of follow-up 
 
The desired outcome is to demonstrate that the False Positive Rate is less than 
1.9 events per patient-year.  The null hypothesis will be rejected at the 2.5% 
significance level if the 97.5% upper confidence limit (UCL) for the expected 
FPR is less than 1.9 per patient-year of follow-up. 
 
 

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Patient Group  
All enrolled patients who have a successful implant or system revision and 
have completed the Baseline visit with the ST Monitoring Feature and Patient 
Notifier programmed ON will be included in this endpoint. 
 
Further, the analysis population for the secondary safety endpoint will be 
those subjects with the Fortify ST (upgraded), Fortify Assura ST and 
Ellipse ST devices.  The data from subjects with a Fortify ST prior to being 
upgraded will not be included in this analysis. 
 
 
Analysis 
 
Primary Analysis 
The expected FPR will be estimated by the observed FPR. To avoid 
imbalance in the number of false positives that each patient with false 
positives contributes, the maximum number of false positives from a patient 
that will be counted toward meeting the requirement on the number of false 
positives will be two. In addition, for a single follow up period (i.e. one 
interrogation and device evaluation to the next), if multiple false positive 
events occur, only one event will be counted toward the analysis.  This will 
prevent multiple false positives that occur before the physician has the 
opportunity to evaluate the patient and reprogram the device from contributing 
to an imbalance in the data. For any patients with more than two false 
positives their follow up time will be truncated to the date of the second false 
positive. 
 
The analysis will be carried out where only those false positives counted 
toward meeting the requirement of number of false positives are included.  
That is, if a patient has experienced more than two false positives, only the 
first two false positives of that patient will be included.  
 
The 97.5% upper confidence limit for the expected FPR will be calculated 
based on the confidence interval calculation of a Poisson rate using the exact 
method (Ulm, 1990)6.  The null hypothesis will be rejected at the 2.5% 
significance level if the 97.5% upper confidence limit is less than 1.9 per 
patient-year.   
 
Additional Analyses 
Empirical analyses will be provided for the false positive rate using  
1. the estimator described in the Primary Analysis section, and 
2. the estimator that uses all false positive events.   
The standard error of these empirical estimators will calculated as the standard 
deviation of their bootstrap distributions.  The bootstrap distributions will be 

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constructed using 1,000 bootstrap resamples.  Each bootstrap resample will be 
performed at the patient level (in order to preserve the correlation structure 
between events with a given patient), and each resample will have a total 
sample size equal to the total number of evaluable patients.  The bootstrap 
distributions will be used to estimate two-sided 95% bootstrap confidence 
intervals. 
 
Subgroup Analysis 
 
The analysis of the secondary safety endpoint will be performed on the 
following subgroups of patients 
 Coronary artery disease patients with cardiomyopathy 
 Coronary artery disease patients without cardiomyopathy 
 Patients with abnormal baseline ECGs, for each of six abnormal 
subgroup categories  
 Patients with normal baseline ECGs 
 Patients with arrhythmias 
 Gender 
 Patients alerted via Merlin.net and patients alerted via device Patient 
Notifier 
 
Sample Size  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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4.4 Analysis of Efficacy 
4.4.1 Primary Efficacy Endpoint 
The efficacy endpoint will be evaluated as the sensitivity of the ST 
Monitoring Feature to detect clinical events.  Sensitivity of the ST Monitoring 
Feature to detect clinical events will be calculated as the number of True 
Positive events (as defined in section 3.2.3) divided by the total number of 
ACS clinical events. 
 
Sensitivity = 
events
 
ACS
of
number   
 
Total
  
events
  
TP
  
of
  
#
 
 
A clinical event is considered to be related to the onset of a Type I ST episode 
if the clinical event occurs within 72 hours after the onset of a Type I ST 
episode. 
 
The hypothesis is formally expressed as follows:  
 
H0: Sensitivity  50% 
Ha: Sensitivity > 50% 
 
The desired outcome is to demonstrate that the sensitivity of the ST 
Monitoring Feature is greater than 50%.  The null hypothesis will be rejected 
at the 2.5% significance level if the lower bound of the 95% confidence 
interval for sensitivity is greater than 50%.  The lower confidence bound will 
be calculated using the Wilson score interval method. 
 
Patient Group 
 
All enrolled patients who have a successful implant or system revision, 
complete the Baseline follow up visit and have the ST Monitoring Feature and 
Patient Notifier turned ON, and experience clinical events will be included in 
the evaluation of this study endpoint.  Data collection towards the study 
endpoint will begin after the Baseline visit. 
 
Further, the analysis population for the primary efficacy endpoint will be 
those subjects with the Fortify ST (upgraded), Fortify Assura ST and 
Ellipse ST devices.  The data from subjects with a Fortify ST prior to being 
upgraded will not be included in this analysis. 
 
 
 

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Analysis 
 
Primary Analysis 
The expected sensitivity for ST Monitoring Feature will be estimated by the 
number of true positive events divided by the total number of ACS events.  
 
The 95% confidence limits will be calculated for sensitivity using the Wilson 
score interval method7 for a binomial proportion.  The null hypothesis will be 
rejected if the lower bound of the 95% confidence limit is greater than 50%.  
 
Additional Analysis 
 
An empirical analysis will be provided for the sensitivity of the ST 
Monitoring Feature to detect clinical events using the estimator described in 
the Primary Analysis section.  The standard error of this empirical estimate 
will calculated as the standard deviation of a bootstrap distribution.  The 
bootstrap distribution will be constructed using 1,000 bootstrap resamples.  
Each bootstrap resample will be performed at the patient level (in order to 
preserve the correlation structure of multiple events within one patient, if the 
occurs), and each resample will have a total sample size equal to the total 
number of evaluable patients.  A two-sided 95% bootstrap confidence interval 
will be provided. 
 
Subgroup Analysis 
 
The analysis of the primary efficacy endpoint will be performed on the 
following subgroups of patients 
 Coronary artery disease patients with cardiomyopathy 
 Coronary artery disease patients without cardiomyopathy 
 Patients with abnormal baseline ECGs, for each of six abnormal 
subgroup categories  
 Patients with normal baseline ECGs 
 Patients with arrhythmias 
 Gender 
 Patients alerted via Merlin.net and patients alerted via device Patient 
Notifier 
 
 
Sample Size 
 
 
 
  
 

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The patients to be enrolled in the Analyze ST IDE Study are similar to those 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 the total number of patients required to be enrolled is 5,228. 
 
4.5 Overall sample size and data cut-off 
The total number of patients required for enrollment in order to satisfy the primary 
endpoints and the secondary endpoint is driven by the sample size requirement to 
satisfy the primary efficacy endpoint.  Thus the total sample size required for this 
study is 5,228.  
 
Data collection for the purposes of the FDA market approval application will be 
considered to be complete when the primary safety endpoint data are available and at 
least 41 clinical events have occurred. 
 
Following submission of the clinical data, patients will continue to be followed until 
closure of the study for providing long-term follow up on the Investigational 
Devices. 
 

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4.6 Poolability Analyses 
The poolability across sites will be verified for the safety endpoint, percent of 
patients experiencing a false positive event within 12 months, and for the 
effectiveness endpoint, sensitivity of the ST Monitoring Feature to detect clinical 
events.  Since it is likely that sites will have a wide variation in the number of 
patients enrolled (due to differences in site start-up times and differences in patient 
volumes at the sites), for the purpose of testing poolability, they will be classified 
into the following categories: 
 
 
 
 
 
 
 
To evaluate poolability across sites, separate generalized linear models will be used 
for the safety and efficacy endpoints, as follows:  






p
p
1
log
 = site category, 
 
where p is the expected proportion of patients experiencing a false positive event 
within 12 months (safety) or the sensitivity of the ST Monitoring Feature (efficacy).  
Testing will be conducted at a significance level of 15%.  Poolability will be verified 
for an endpoint if the site category effect is not significant at the 15% significance 
level. 
 
4.7 Additional Analyses 
 
 
The following additional data will be collected during the study: 
 
 Demographic variables include: gender, age, ethnicity, cardiomyopathy 
classification, complete cardiovascular history, arrhythmia history, primary 
ICD indication, and EF% at the time of enrollment and QRS duration at 
baseline 
 ST Diagnostic Data to include: heart rate at onset of the Type I ST episode, 
maximum ST shift during the Type I ST episode, Type I ST episode duration, 
total number of Type I ST episodes detected 
 All diagnostic procedures (tests and interventions) stratified by investigator’s 
assessment of whether the procedure would have been performed in presence 
and absence of ST diagnostic data 

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 Positive Predictive Value (PPV) of the ST Monitoring Feature 
 Negative Predictive Value (NPV) of the ST Monitoring Feature 
 Response rates to Patient Notifier and Merlin.net Type I ST Episode 
detections 
 Cardiac medications (including anti-anginal medications) during clinical 
events 
 CPK Isoenzymes, MB fractions and Troponin values collected during clinical 
events 
 Stress test and 12-lead ECG measurements collected during clinical events 
 Proportion of patients who have the ST Monitoring Feature turned off at every 
study visit from the Programming Visit onwards 
 Adverse events 
 Clinical events 
 Spontaneous arrhythmic episodes 
 Hospitalizations 
 Mortality/Death 
 
4.7.1 Demographic Variables 
Demographic variables will be collected for all patients at the time of 
enrollment and summaries presented.  Continuous variables will be 
presented as mean ± SD, and categorical variables will be tabulated with 
percentages. 
 
4.7.2 ST Diagnostic Data 
ST diagnostic data will be collected and presented for all Type I ST episodes 
for all patients with the Fortify ST (upgraded), Fortify Assura ST and 
Ellipse ST devices.  Additionally, ST diagnostic data from all patients with 
the Fortify ST prior to being upgraded will be collected and presented. 
 
4.7.3 Investigator’s Assessment of Procedures Performed 
All diagnostic procedures (tests and interventions) stratified by 
investigator’s assessment of whether the procedure would have been 
performed in presence and absence of ST diagnostic data 
 
4.7.4 Positive Predictive Value (PPV) 
The PPV will be calculated as the proportion of true positives (according to 
section 3.2.3) to the number of all Type I ST episodes (i.e., combination of 
all true positive and false positive events). 
 
 
 
4.7.5 Negative Predictive Value (NPV) 
The NPV will be calculated as the proportion of true negatives to the 
combination of false negatives and true negatives (according to section 3.2.3)   

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4.7.6 Response Rates to Patient Notifier and Merlin.net Type I ST 
Episode Detections 
The response rates to Type I ST Episode notifications received through the 
Patient Notifier and through Merlin.net will be presented. 
 
4.7.7 Cardiac and Anti-Anginal Medications 
List of concomitant cardiac and anti-anginal medications will be collected at 
the Screening visit, Baseline visit and at each clinical event and will be 
summarized for all patients. 
 
4.7.8 CPK Isoenzymes MB Fractions and Troponin 
Cardiac biomarker laboratory tests will be collected during any clinical event 
as defined by the study protocol.  Results will be determined as positive or 
negative and will be compared to clinical events and to Type I ST episodes. 
 
4.7.9 12-Lead ECG Measurements 
12-lead ECG recordings will be collected at the Baseline visit and during any 
clinically-indicated stress test related to Clinical Events. Results from the 12-
lead ECG recordings along with the patient’s pertinent medical records will be 
adjudicated by the CEC and classified as normal or abnormal.  All ECG 
abnormalities will be classified as a preexisting abnormality or as a new 
finding.  An abnormal 12-Lead ECG is defined as having at least one of the 
following present 1) rhythm other than normal sinus rhythm or sinus 
tachycardia such as atrial fibrillation, atrial flutter, supraventricular 
tachycardia, ventricular tachycardia, or idioventricular rhythm 2) intermittent 
or complete conduction abnormalities resulting in widening of the QRS 
complex (RBBB, LBBB, IVCD, evidence of left ventricular hypertrophy), 3) 
ST-T wave abnormalities (T wave inversions, J point elevation) 4) frequent 
PVCs 5) low voltage QRS complexes indicative of dilated cardiomyopathy or 
COPD, or 6) high voltage QRS complexes indicative of left ventricular 
hypertrophy.  A normal 12-Lead ECG will be defined as one not meeting the 
criteria for an abnormal ECG.   
 
Results of any stress tests performed will be determined as positive or 
negative by the site and will be sent to the CEC for further adjudication  
 
4.7.10 Adverse Events 
All adverse events will be categorized by the investigator as instructed in 
Section 6.0 of the investigational protocol.  Adverse event evaluation will 
include the number of patients who experienced any events, the number of 
events and each event classification.   
 

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4.7.11 Clinical Events 
Clinical events will be summarized for all patients in terms of the number of 
events and number of patients.  The rate of clinical events will be reported per 
patient-year of follow-up along with a 95% confidence interval using Ulm’s 
method. 
 
4.7.12 Spontaneous Arrhythmic Episodes 
All available spontaneous arrhythmic diagnostic episodes detected by the 
ICD, as well as the corresponding stored IEGMs, will be retrieved via device 
interrogation and will be reviewed to evaluate appropriate and inappropriate 
ICD therapies. 
 
4.7.13 Hospitalizations 
Cardiac-related hospitalizations, emergency room visits and surgeries will be 
summarized using the Kaplan-Meier survival method. 
 
4.7.14 Mortality 
The number of deaths will be summarized. The observed mortality rate will be 
summarized using the Kaplan-Meier survival method. 
 
4.7.15 Re-analysis of Endpoints with a 14-day Threshold 
Evaluate primary and secondary endpoints using a 14 day threshold (instead 
of 72 hours) for associating a Type I ST episode with a true ACS event. 
 

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Reference 
 
1. Akinpelu D, Gonzales JM.  Treadmill and Pharmacologic Stress Testing.  eMedicine 
Specialties; Article 160772 
2. Secknus, MA, Marwick TH.  Evolution of Dobutamine Echocardiography Protocols and 
Indication: Safety and Side Effects in 3, 011 Studies Over 5 Years.  JACC 1997; 29; 
1234-1240 
3. Chee TS, Quek SSS, et al.  Clinical Utility, Safety, Acceptability and Complications of 
Transoesophageal Echocardiography (TEE) in 901 Patients.  Singapore Med J; 1995; 36; 
479-483 
4. Di Carli MF, Dorbala S, et al.  Clinical Myocardial Perfusion PET/CT.  J Nucl Med 
2007; 48: 783-793 
5. Barber S. , Jennison C, Symmetric Tests and Confidence Intervals for Survival 
Probabilities and Quantiles of Censored Survival Data, Biometrics, 1999; 55: 430-436 
6. Ulm K.  A simple method to calculate the confidence interval of a standardized mortality 
ratio. American Journal of Epidemiology 1990; 131(2):373-375 
7. Wilson, E.B. (1927) Probable inference, the law of succession, and statistical inference. J. 
Am. Stat. Assoc., 22, 209–212. 
8. Prasad S, Richards D, Saick N, Ong A, Kovoor P. Clinical and Electrocardiographic 
Correlates of Normal Coronary Angiography in Patients Referred for Primary 
Percutaneous Coronary Intervention. Am J Cardiol 2008;102:155-159. 
9. Ornato JP, Menown IB, Peberdy MA, Kontos MC, et al.  Body surface mapping vs 12-
lead electrocardiography to detect ST-elevation myocardial infarction.  Am J Emerg 
Med. 2009 Sep; 27(7):779-84. 
10. Gibbons, Raymond J, Baladay, Gary J, Beasley, John W, Bricker, Timothy, et al. 
ACC/AHA Guidelines for Exercise Testing.  A Report of the American College of 
Cardiology/American Heart Association: Task Force on Practice Guidelines (Committee 
on Exercise Testing).  JACC 1997 Jul; 30(1): 260–315. 
 
 
 
 

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APPENDIX A 
Details of Sample Size Calculations  
 
 
Primary Efficacy Endpoint - False Positive Rate 
 
Power calculations using simulated data 
 
 
 
 
 
 
 
 
 


 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 

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} 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
  
 
 
 
 
 
 
        
 
  
     
 
  
     
 
  
     
 
  
     
 
  
     
 
  
     
 
  
     
 
  
     
 
  
     
 
     
 
     
 

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Secondary Endpoint – Sensitivity of ST Monitoring Feature