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1/29/2020
1
Role of CardioMEMS in Management of Heart Failure
Anand Deshmukh, MD FACP FACC FSCAI FSVMMethodist Jennie Edmundson Hospital
Nebraska Methodist HospitalMethodist Physicians Clinic
Disclosures
• None
Objectives
Heart Failure
• Scope of the problem
• Impact of various strategies to reduce heart failure hospitalization
• Role of CardioMEMS in management of heat failure – a. Technical details
• b. Evidence to assess efficacy and safety
• c. Indications for CardioMEMS placement
• d. Cost efficacy
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Heart failure Scope of the problem
Heart Failure is a Growing Global Clinical Burden• UNITED STATES
5
1. AHA 2016 Statistics at a Glance, 2016.
2. Krumholz HM, et al. Circ Cardiovas Qual Outcomes, 2009.
3. Heidenreich PA, et al. Circ Heart Failure, 2013.
HIGH INCIDENCE, HIGH PREVALENCE, AND POOR PROGNOSISdespite advances in the treatment of heart failure over the past few decades.
PREVALENCE 2.2%Prevalence1
5.7mHF patients1
Projected to increase to > 8M people ≥ 18 years of age with HF by 20301
INCIDENCE915,000
people ≥ 45 years of age are newly diagnosed each year with HF.1
MORBIDITY AND MORTALITY
For AHA/ACC stage C/D patients diagnosed with HF:
50% Readmitted within
6 months.2
50% Will die within
5 years.3
*Study projections assumes HF prevalence remains constant and continuation of current hospitalization practices
Heart Failure is a Growing Economic Burden
HOSPITALIZATIONS AND READMISSIONS COSTS
> 1,100,000hospitalizations
for HF1
> 3,000,000hospitalizations
include HF as a contributor.2
Total medical costs for HF are projected to
increase to $70B
by 2030, a 2x increase from 2013.*
50% of the costs are
attributed to hospitalization.6~5 days
average length of hospital stay3
~25%all-cause readmission within 30 days; ~50% within 6 months.4,5
Despite advances in medical therapies to treat heart failure, the hospitalization rate has not changed significantly from 2000. As a result, heart failure continues to be a
MAJOR DRIVER OF OVERALL HEALTH CARE COSTS.
UNITED STATES
1. CDC NCHS National Hospital Discharge Survey, 2000-10.
2. Blekcer et al. J Am Coll Cardiol, 2013.
3. Yancy et al. J Am Coll Cardiol, 2006.
4. Wxler DJ, et al. Am Heart J, 2001.
5. Krumholz HM, et al. Circ Cardiovas Qual Outcomes, 2009.
6. Yancy CW, et al. Circulation, 2013.
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• EACH EVENT ACCELERATES DOWNWARD SPIRAL OF MYOCARDIAL FUNCTION
With each subsequent HF-
THE GOAL:Maintain fluid volume to avoid
acute decompensation and hospitalization
HF HOSPITALIZATION is a valid endpoint for measuring
decompensation
Goal of Heart Failure Management: SLOW DISEASE PROGRESSION BY PREVENTING DECOMPENSATION
7Gheorghiade MD, et al. Am J. Cardiol, 2005.
Acute Event
TIME
MYO
CA
RD
IAL
FUN
CTI
ON
Kaplan-Meier cumulative mortality curve all-cause mortality after each subsequent hospitalization for HF.
Long-term Mortality Risk Increases with Multiple Hospitalizations
8• Setoguchi S, Stevenson LW, Schneeweiss S, Am Heart J, 2007;154:260-264.
1st admission(n = 14,374)
2nd admission(n = 3,358)
3rd admission(n = 1,123)
4th admission(n = 417)
Strategies to Reduce Heart Failure Hospitalization
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Pathophysiology of Heart Failure
Neurohormonal Consequences of Hemodynamic Failure WHAT HAPPENS AS PA PRESSURE RISES?
11Adapted from Jaski BE, “Basics of Heart Failure A Problem Solving Approach”
Pulmonary Artery Pressure
Left Heart Failure Right Heart Failure
Left Atrial Pressure Cardiac Output Right Atrial Pressure
Dyspnea
Orthopnea
Pulmonary Edema
Peripheral Edema
Fatigue
Confusion
Renal Insufficiency
Heptic Insufficiency
Renal Insufficiency
Peripheral Edema
Neurohormonal Activation
WORSENING DYSPNEA LEADING TO HOSPITALIZATION
Increased PulmonaryArtery Pressures
FluidRetention
FluidRedistribution
Vascular Resistance
Pathogenesis of Worsening Heart FailureROLE OF HEMODYNAMIC MONITORING
12
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THE GOAL:Predict gradual
decompensation leading to acute decompensation
Current HF Management Tools Designed to Predict Decompensation
FACE-TO-FACE
EVALUATION
PARAMETER SURROGATE FOR:
Symptoms (PND, orthopnea, etc.)
LVEDP, RAP
JVP RAP
HJR RAP
S3 LVEDP
Rales LVEDP
Daily weightBody volume (LVEDP, RAP)
BNP and NT-proBNP PCWP
Intrathoracicimpedance
PCWP
Heart rate variability
Cardiac autonomic control
13
Weight Change is Not a Reliable Indicator of Rising Pressure or Impending Decompensation
14
• 1. Data based on Zile MR, et al. Circulation, 2008. Presented at FDA Advisory Panel, October 9, 2013.
• 2. Lewin J, et al. Eur J HF, 2005.
• 3. Abraham WT, et al. Cong Heart Failure, 2011.
WEIGHT GAIN SENSITIVITY SPECIFICITY
2 kg weight gain over 48-72 hrs2 9% 97%
2% weight gain over 48-72 hrs2 17% 94%
3 lbs in 1 day or 5 lbs in 3 days3 22.5% -
NO CORRELATION – Daily weights do not correlate with filling pressures
Clinical Examinations are not Reliable for Assessing Rising Pressure – Poor Sensitivity and Specificity
VARIABLE ESTIMATE OF SENSITIVITY (%) SPECIFICITY (%) PPV (%) NPV (%)
JVP
EDEMARAP
48
10
78
94
60
55
69
60
PULSE PRESSCardiac Index
27 69 52 44
S3
DYSPNEA
RALES
PCWP
36
50
13
81
73
90
69
67
60
54
57
48
15
• Table adapted from Capomolla S, et al. Eur J Heart Failure, 2005.
N = 366
Clinical examination has LIMITED RELIABILITY in assessing filling pressures.
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Non-hemodynamic-based Remote Monitoring does not Reduce HF Hospitalization
TRIAL N PARAMETER MONITORED
IMPACT ON HF HOSPITALIZATION JOURNAL
TELE-HF1 1,653 Signs/symptoms, daily weights None The New England Journal of Medicine, 2010
TIM-HF2 710 Signs/symptoms, daily weights None Circulation, 2011
TEN-HMS3 426 Signs/symptoms, daily weights, BP,
nurse telephone support None Journal of the American College of Cardiology, 2005
BEAT-HF4 1,437Signs/symptoms, daily weights, nurse communications None American Heart Association, 2016
INH5 715 Signs/symptoms, telemonitoring, nurse coordinated DM None Circulation Heart Failure, 2012
DOT-HF6 335Intrathoracic impedance with patient alert Increased Circulation, 2011
Optilink7 1,002 Intrathoracic impedance None European Journal of Heart Failure, 2011
REM-HF8 1,650Remote monitoring via ICD, CRT-D or CRT-P None
European Society of Cardiology, 2017
MORE CARE9 865 Remote monitoring of advanced
diagnostics via CRT-D None European Journal of Heart Failure, 2016
Total 8,793
16
• 1. Chaudhry SI, et al. N Engl J Med, 2010.
• 2. Koehler F, et al. Circulation, 2011.
• 3. Cleland JG, et al. J Am Coll Cardiol, 2005.
• 4. Ong MK, et al. JAMA Intern Med, 2016.
• 5. Angermann DE, et al. Circ Heart Fail, 2012.
• 6. van Veldhuisen DJ, et al. Circulation, 2011.
• 7. Brachmann J, et al. Eur J Heart Fail, 2011.
• 8. Cowie MR, ESC, 2016.
• 9. Boriani G, et al. Eur J Heart Fail, 2016.
MULTIPLE TRIALS, > 8,500 PATIENTS:No reduction in HF hospitalization
Reactive and Inexact
Current Parameters for Managing HF are Reactive and Inexact
17• Adamson PB, et al. Curr Heart Fail Reports, 2009.
Hemodynamically Stable Decompensation
HOSPITALIZATION
Autonomic Adaptation
Time Preceding Hospitalization (Days)
-30 -20 -10 0
Weight Change
Symptoms
Presymptomatic Congestion
Filling Pressure Increase
Intrathoracic Impedance
Change
Proactive and Actionable
Monitoring for Increased Filling Pressures is Proactive and Actionable, and Predictive of Acute
Decompensation
18• Adamson PB, et al. Curr Heart Fail Reports, 2009.
Hemodynamically Stable Decompensation
HOSPITALIZATION
Autonomic Adaptation
Time Preceding Hospitalization (Days)
-30 -20 -10 0
Intrathoracic Impedance
Change
Filling Pressure Increase
Weight Change
Symptoms
Presymptomatic Congestion
Reactive and Inexact
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Monitoring Pulmonary Artery Pressures,Proactive and Actionable
19• Adamson PB, et al. Curr Heart Fail Reports, 2009.
GAIN IN TIME
Proactive and Actionable
Reactive and Inexact
Hemodynamically Stable Decompensation
HOSPITALIZATION
Autonomic Adaptation
Time Preceding Hospitalization (Days)
-30 -20 -10 0
Weight Change
Symptoms
Presymptomatic Congestion
Hemodynamic Congestion
Clinical Congestion
Intrathoracic Impedance
Change
Filling Pressure Increase
CardioMEMS™ HF System
20
A PERSONALIZED, PROACTIVE APPROACH TO MANAGE HEART FAILURE BY MONITORING PULMONARY ARTERY (PA) PRESSURE
27382-SJM-MEM-0814-0012(1)a(10) | Item approved for global use.
TECHNICAL DETAILS
CardioMEMS
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Microelectrical Mechanical System (MEMS)No lead or battery, no need for replacement
22
CardioMEMS™ HF System Components
23
• PA Sensor
Patient Electronics System
Over-the-wire Sensor Delivery System
Hospital Electronics System
CardioMEMS™ HF System Implementation
25
Sensor insertedvia right heart catheterization
Patients take daily sensor reading from the comfort of their home
Clinician reviews data and contacts patient as necessary
Data wirelessly transmitted to clinician’s website
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DirectTrend™ Viewer is customizable to view SPECIFIC TRENDS ON A PER PATIENT BASIS
Merlin.net™ PCN Enables Trend-based Heart Failure Management
26
3/18/2016Bumex 2 mg bid+ Eplerenone 25 mg bidMacitenten 10 mg daily
9/8/2015Bumex 2 mg dailyHydrazine 10 mg tidSpironolactone 25 mg daily
6/5/2017Bumex 2 mg tidEplerenone 100 mg bidMacitenten 10 mg dailyMetolazone 1.25 mg daily prn
Case Example HFpEF-PAH
27Used with permission from Dr. Jacob Abraham, Providence, St. Vincent’s
EVIDENCE REVIEW – CHAMPION TRIAL
CardioMEMS
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Monitoring with CardioMEMS™ HF System Leads to Reduction in Mean PA Pressure from Baseline• PART 1: RANDOMIZED ACCESS
29• Abraham WT, et al. Lancet, 2011.
SECONDARY ENDPOINT: Targeting PA pressures and titrating medications results in reduction of mean PA pressure over time.
PA M
ean
Pre
ssu
re A
UC
(m
mH
g d
ays)
Primary Efficacy Endpoint Met with Significantly Reduced Heart Failure Hospitalization
• PART 1: RANDOMIZED ACCESS
30• Abraham W, et al. Lancet, 2016.
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
0 90 180 270 360 450 540 630 720 810 900 990 1080
Cu
mu
lati
ve H
azar
d R
ate
Days From Implant
33% RELATIVE RISK REDUCTION IN HF HOSPITALIZATIONS:TREATMENT GROUP VS. CONTROL GROUP
TREATMENT
CONTROL
No. at Risk
CONTROL 280 267 254 241 210 175 131 101 62 27 12 5 0
TREATMENT 270 262 246 235 197 164 125 105 75 38 8 3 0
p < 0.0001
All Secondary Endpoints Met
TREATMENT(N = 270)
CONTROL(N = 280)
P-VALUE
SECONDARYENDPOINTS
Change from baseline in PA mean pressure (mean AUC [mmHg x days])
-156 33 0.008
Number and proportion of patients hospitalized for HF (%)
55 (20%) 80 (29%) 0.03
Days alive and out of hospital for HF (mean ± SD)
174.4 ± 31.1
172.1 ± 37.8
0.02
Quality of life (Minnesota Living with Heart Failure Questionnaire, mean ± SD)
45 ± 26 51 ± 25 0.02
31
• *Total of 8 DSRCs including 2 events in Consented not implanted patients (n = 25)
• Abraham WT, et al. Lancet, 2011.
PART 1: RANDOMIZED ACCESS
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Both Primary Safety Endpoints Met
32
• 1167 patient-years of follow-up• 8 device/system-related complications (DSRC) • 0.007 DSRC per patient-year• All DSRC occurred within 30 days of implant• No sensor failures
No. at Risk 570 525 497 474 446 420 395 363 326 300 283 253 127 10 1
0 90 180 270 360 450 540 630 720 810 900 990 1080 1170 1260
Days from Implant Procedure
Free
do
m f
rom
Dev
ice/
Syst
em R
elat
ed C
om
plic
atio
ns
(%)
Treatment Group, HFpEF
Control Group, HFpEF
Prospective Subgroup Analysis: HFpEF PATIENTS MANAGED WITH THE CardioMEMS™ HF SYSTEM
SHOW SIGNIFICANT REDUCTION IN HF Hospitalization
33
Avg. 18 months follow-up50% RRR, p < 0.0001
50 % reduction in HF Hospitalization
• Adamson PB, Abraham WT, Bourge RC, et al. Circ Heart Fail, 2014 Nov;7(6):935-44.
The CHAMPION Trial Subgroup Analyses: REDUCTION OF HF HOSPITALIZATION IN PATIENT GROUPS
WITH COMMON COMORBIDITIES
34
1. Adamson, et al. Circ Heart Fail, 2016.
2. Adamson, et al. Circ Heart Fail, 2014.
3. Abraham, et al. ACC, 2015.
4. Abraham, et al. HRS 2015.
5. Strickland WL, et al. J Am Coll Cardiol, 2011.
6. Criner G, et al. Eur Respir J, 2012.
7. Martinez F, et al. Eur Respir J, 2012.
8. Benza R, et al. J Card Fail, 2012.
9. Miller AB, et al. J Am Coll Cardiol, 2012.
10. Abraham, et al. J Card Fail, 2014.
Sub-Group or Comorbidityn
(control)n
(treatment)Follow-up
Period (months)
Reduction of HF Hospitalization Rate in
Treatment Group vs. control
Medicare population1 125 120 18 49%, p < 0.0001
HFpEF2 56 59 18 50%, p < 0.0001
HFrEF following GDMT3 174 163 17 43%, p < 0.0001
CRT-D or ICD following GDMT4 146 129 18 43%, p < 0.0001
History of myocardial infarction5 137 134 15 46%, p < 0.001
COPD6,7 96 91 15 41%, p = 0.0009
Pulmonary hypertension8 163 151 15 36%, p = 0.0002
AF9 135 120 15 41%, p < 0.0001
Chronic kidney disease10 150 147 15 42%, p = 0.0001
Patients with common HF comorbidities and patients in important subgroups HAVE CONSISTENT REDUCTION IN HF HOSPITALIZATIONS with PA pressure-guided therapy.
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NNT to Prevent One HF Hospitalization for PA Pressure Monitoring and Medical Intervention Alone
• PART 1: RANDOMIZED ACCESS
35
• 1. Packer M, et al. Circulation, 2002.
• 2. Pitt B, et al. N Engl J Med, 1999.
• 3. Cleland JG, et al. N Engl J Med, 2005.
• 4. Hjalmarson A, et al. JAMA, 2000.
• 5. The SOLVD Investigators. N Engl J Med, 1991.
• 6. Zannad F, et al. N Engl J Med, 2011.
• 7. Digitalis Investigation Group. N Engl J Med, 1997.
• 8. Cohn JN, et al. N Engl J Med, 2001.
• 9. Young JB, et al. Circulation, 2004.
• 10. Adamson, P. et al. HFSA, 2016.
INTERVENTION TRIALMEAN DURATION OF RANDOMIZED
FOLLOW-UP
ANNUALIZED REDUCTION IN HF Hospitalization
RATES
NNT/YEAR TOPREVENT 1 HF
HOSPITALIZATION
Beta-blocker1 COPERNICUS 10 months 33% 7
Aldosterone antagonist2 RALES 24 months 36% 7
CRT3 CARE-HF 29 months 52% 7
Beta-blocker4 MERIT-HF 12 months 29% 15
ACE inhibitor5 SOLVD 41 months 30% 15
Aldosterone antagonist6 EMPHASIS-HF 21 months 38% 16
Digoxin7 DIG 37 months 24% 17
Angiotensin receptor blocker8 Val-HeFT 23 months 23% 18
Angiotensinreceptor blocker9 CHARM 40 months 27% 19
PA pressure monitoring10 CHAMPION 18 months 33% 4
PA pressure monitoring led to lower NNT to prevent one hf-related hospitalization vs. other therapies
Mortality
De
ath
s/Pa
tie
nt-
yr
p = 0.0293
Retrospective Subgroup Analysis:HFrEF PATIENTS SHOW SYNERGY BETWEEN OPTIMAL GDMT
AND HEMODYNAMIC CARE
36
HF
Ho
spit
aliz
atio
n/P
atie
nt-
yr
p = 0.0002
HF Hospitalization
p = 0.0002
De
ath
s/Pa
tie
nt-
yr
p = 0.0052
HF Hospitalization Mortality
Partial GDMT “Optimal” GDMT
33 % reduction
37 % reduction
43 % reduction
57 % reduction
*The CardioMEMS™ HF System is not labeled for a reduction in mortality
Givertz M, et al. J Am Coll Cardiol, 2017.
TreatmentControlTreatmentControl
HF
Ho
spit
aliz
atio
n/P
atie
nt-
yr
CardioMEMS- Impact of Quality of Life (NorthwellHealth)
SIGNIFICANT IMPROVEMENT IN FUNCTIONAL CLASS AND QoL IN PATIENTS IMPLANTED WITH THE CardioMEMS™ HF SYSTEM
37Alam A, et al. Abstract presented at ACC, 2016.
6-minute walk: Avg. increase of 96 meters at 90 days versus no increase in the SoC group
0
100
200
300
400
CardioMEMS™ PA Sensor (n = 34) Control (n = 32)
Dis
tan
ce (
m)
Baseline
30 days
90 days
0
20
40
60
80
100
CardioMEMS (n = 34) Control (n = 32)
Sco
re Baseline
90 days
KCCQ: 3-fold greater improvement in scores
p < 0.001 compared to baseline
p < 0.001 p = 0.003
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CardioMEMS- Impact on Survival Prospective Subgroup Analysis:
HFrEF PATIENTS SHOWS SIGNIFICANT REDUCTION IN HF Hospitalization AND STRONG TREND TOWARDS IMPROVED SURVIVAL*
38
*The CardioMEMS™ HF System is not labeled for a reduction in mortality
Givertz M, et al. J Am Coll Cardiol, 2017.
Survival Probability
Kaplan-Meier Survival Analysis
Clinical Outcomes
Rat
es
Eve
nts
/Pat
ien
t-yr
TreatmentControl
0.69
0.24
Mortality RateHF Hospitalization Rate
0.49
0.18
p = 0.0013
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
0
28 % reduction
p = 0.06
Surv
ival
Pro
bab
ility
(%
)
No. at RiskCONTROL 234 209 173 102 45 7 0TREATMENT 222 202 161 105 62 7 0
32 % reduction
Treatment
Control
CardioMEMS- Impact on Survival Subgroup Analysis:HFrEF PATIENTS WITH CRT-D FOLLOWING GDMT
39Abraham, et al. HRS 2015.
64% reduction (p = 0.028)
CardioMEMS- Indications
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Indications for CardioMEMS™ HF System?
THE CARDIOMEMS™ HF SYSTEM IS INDICATED FOR THESE PATIENTS1:
NYHA Class III heart failure
One heart failure hospitalization in the past 12 months
PATIENTS WHO MOST COMMONLY RECEIVE THE CARDIOMEMS™ HF SYSTEM ARE THOSE ON GDMT AND THOSE WHO EXHIBIT ANY OF THE FOLLOWING1:
□ Fluid volumes are hard to know or manage□ Physical assessment is challenging□ Is a patient with HFpEF or HFrEF□ Compliant with heart failure medical care□ Would benefit from remote monitoring
if they live far from clinic
CardioMEMS- Cost Efficacy
Treatment Costs CHAMPION TRIAL
• Treatment group
• Average quality adjusted life expectancy of 2.506 QALYs
• Total cost of $ 68,919
• Control group
• Average quality adjusted life expectancy of 2.200 QALYs
• Total cost $ 64, 637
Abraham WT, et al. Lancet, 2011.
Incremental cost effectiveness ratio of integrating PA sensor into standard of care for management of heart failure was $ 13, 979 per QALY gained
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Real-world Use of the CardioMEMS™
HF System:ASSOCIATED HF HOSPITALIZATION COSTS
$28,870
$47,690
$18,360
$34,500
$0K
$10K
$20K
$30K
$40K
$50K
$60K
$70K
$80K
6-MONTH COHORT 12-MONTH COHORT
Pre-Implant Post-Implant
-$10,510
-$13,190
Large (N = 1114) retrospective cohort study using the CardioMEMS™ HF System patients from CMS database
Desai, AS, et al. J Am Coll Cardiol, 2017;69(19):2357–65.
44
SUMMARY – CARDIOMEMS PA SENSOR
. 45
HEART FAILURE HOSPITALIZATION COSTS3
LOWER
DECREASE
MORTALITY4,5**
*Includes a 48% reduction in heart failure hospitalizations,1 a 58% reduction in all-cause 30-day readmissions,8 and a 78% reduction in heart failure-specific 30-day readmissions.8
**CardioMEMS™ HF System is not indicated for a reduction in mortality. Based on retrospective cohort studies using the CardioMEMS HF System patients from CMS database.
QUALITY OF LIFE AND FUNCTIONAL CAPACITY1,2
REDUCE
IMPROVE
Patients benefit REGARDLESS OF EF OR GENDER6,7
H
HEART FAILURE HOSPITALIZATIONS1,3*
1. Abraham WT, et al. The Lancet, 387(10017), 453-461.
2. Jermyn R, et al. Clinical Cardiology. doi: 10.1002/clc.22643.
3. Desai AS, et al. J Am Coll Cardiol, 2017;69(19):2357–65.
4. Abraham, et al. Presented at ACC 2018
5. Givertz MM, et al. J Am Coll Cardiol 2017; 70:1875–86.
6. Adamson PB, et al. Circulation: Heart Failure, 7(6), 935-944.
7. Heywood JT, et al. Circulation 2017;135: 1509–17.
8. Adamson, et al. Circulation Heart Failure 2016;115.002600.
98.6%FREEDOM FROM DEVICE OR SYSTEM COMPLICATIONS(p < 0.0001)1
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