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Telemedicine in the Management
of Congestive Heart Failure
David Bello MD
Chief, Cardiology
Orlando Regional Medical Center
Founder, HeartBuds
Telemedicine in Chronic Disease Management
CMS Story: higher quality, less readmissions, less
cost
Goals of Pilot
 Higher patient satisfaction
 Higher quality
 Less Cost
 Less readmissions
US-2000480 A EN (08/14) | This document is approved for US use only.
Physiologic Monitoring
for Heart Failure Management
US-2000480 A EN (08/14) | This document is approved for US use only.
Contents
 Heart Failure (HF)
 Prevalence, incidence, mortality and hospitalization rates
 Economic burden of HF and Medicare reform initiatives
 Physiologic Monitoring
 Worsening HF/Physiologic markers of decompensation
 Weight, blood pressure, symptoms
 Impedance
 Clinical evaluations
 Hemodynamic Monitoring for Heart Failure Management
 Managing pressures in the heart failure patient
 CardioMEMS™ HF System
 CHAMPION clinical trial
6
Heart Failure
 Prevalence, Incidence, Mortality and Hospitalization Rates
 Economic Burden of HF and Medicare Reform Initiatives
US-2000480 A EN (08/14) | This document is approved for US use only.
Heart Failure – A Growing Global Concern
Prevalence and Incidence
 Overall 2.1% prevalence: 5.1M
heart failure patients in 20101
 825,000 people ≥ 45 years of age
are newly diagnosed each year
with HF1
 15 M heart failure patients in the
ESC 51-member countries2
 Overall 2-3% prevalence2
Mortality
 For AHA/ACC stage C/D patients
diagnosed with HF:
 30% will die in the first year. 3-5
 60% will die within 5 years.5
8
1. AHA 2014 Statistics at a Glance, 2014
2. The European Society of Cardiology, ESC HF Guideline, 2008
3. Curtis et al, Arch Intern Med, 2008.
4. Roger et al. JAMA, 2004.
5. Cowie et al, EHJ, 2002.
6. Heidenreich PA et al. Circ Heart Failure 2013.
HF prevalence in the US is projected to increase 46% from 2012 to 2030,
resulting in > 8M people ≥ 18 years of age with HF.6
US-2000480 A EN (08/14) | This document is approved for US use only.
Heart Failure Is Associated with High Hospitalization
and Readmission Rates
 In 2010, there were 1 million
hospitalizations in the US with
HF as the principal diagnosis1
 Hospitalization rate did not change
significantly from 20001
 Average length of hospital stay
 Approximately 5 days (US)2
 11 days (Europe)3
 HF is also associated with high
readmission rates:
 ~25% all-cause readmission
within 30 days and ~50%
within 6 months5
1. CDC NCHS National Hospital Discharge Survey, 2000-2010
2. Yancy et al. JACC, 2006.
3. Cleland et al. EuroHeart, 2003.
4. Krumholz HM, et al. Circ Cardiovas Qual Outcomes 2009.
5. Wexler DJ, et al. Am Heart J 2001.
Graph from www.health.org.uk. Bridging the gap: Heart Failure, 2010.
Data from Organization for Economic Cooperation and Development, 2009.
9
1. CDC NCHS National Hospital Discharge Survey, 2000-2010
2. Yancy et al. JACC, 2006.
3. Cleland et al. EuroHeart, 2003.
4. Krumholz HM, et al. Circ Cardiovas Qual Outcomes 2009.
5. Wexler DJ, et al. Am Heart J 2001.
1. CDC NCHS National Hospital Discharge Survey, 2000-2010
2. Yancy et al. JACC, 2006.
3. Cleland et al. EuroHeart, 2003.
4. Krumholz HM, et al. Circ Cardiovas Qual Outcomes 2009.
5. Wexler DJ, et al. Am Heart J 2001.
US-2000480 A EN (08/14) | This document is approved for US use only.
Worsening Heart Failure Leading to HF
Hospitalizations Contributes to Disease Progression
With each subsequent HF-related admission, the patient leaves the hospital
with a further decrease in cardiac function.
Graph adapted from: Gheorghiade MD, et al. Am J. Cardiol. 2005
10
US-2000480 A EN (08/14) | This document is approved for US use only.
Economic Burden of HF Will Continue to Rise
Through 2030*
 The AHA estimates that the total medical costs for HF are projected
to increase to $70B by 2030  a 2-fold increase from 2013.1
 50% of the costs are attributed to hospitalization.2
11
Graph: Heidenreich PA, et al. Circulation Heart Failure 2013.
*Study projections assumes HF prevalence remains constant and continuation of current hospitalization practices
1. Heidenreich PA, et al. Circulation Heart Failure 2013.
2. Yancy CW, et al. Circulation 2013.
US-2000480 A EN (08/14) | This document is approved for US use only.
Economic Risks of HF Readmissions in the US
Medicare’s Hospital Readmissions Reduction program penalizes
hospitals that have above average all-cause readmissions within
30 days following HF discharge.
1. Dharmarajan K, et al. JAMA. 2013;309(4):355-363.
2. Linden A, Adler-Milstein J. Health Care Finance Rev. 2008;29(3):1-11.
3. CMS Hospitals Readmissions Reductions Program of the Patient Protection and Affordable Care Act (PPACA), 2010.
24.8%national average 30-day
readmissions rate1,2
Fiscal Year 2013 2014 2015+
% payment withholding up to 1% up to 2% up to 3%
Percent withholding of all inpatient Medicare payments will
increase to up to 3% by 2015 and beyond.3
12
Physiologic Monitoring
 Worsening Heart Failure/Physiologic Markers of Decompensation
 Weight, Blood Pressure, Symptoms
 Impedance
 Clinical Evaluations
US-2000480 A EN (08/14) | This document is approved for US use only.
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
Increases in Pressure Start the Cycle of Worsening
Heart Failure
14
Adapted from Jaski BE, “Basics of Heart Failure A Problem Solving Approach”
 


US-2000480 A EN (08/14) | This document is approved for US use only.
Time Course of Decompensation
Physiologic Markers of Acute Decompensation
15
* Graph adapted from Adamson PB, et al. Curr Heart Fail Reports, 2009.
US-2000480 A EN (08/14) | This document is approved for US use only.
Physiologic Markers of Acute Decompensation
16
* Graph adapted from Adamson PB, et al. Curr Heart Fail Reports, 2009.
US-2000480 A EN (08/14) | This document is approved for US use only.
Current HF Management Is Inadequate For
Identifying and Managing Congestion Leading
to Decompensation
 90% of HF hospitalizations present with symptoms of pulmonary congestion.1,2
 Post hoc analysis of 463 acute decompensated HF patients from DOSE-HF and CARRESS-HF trials showed:
 40% of patients are discharged with moderate to severe congestion.3
 Of patients decongested at discharge, 41% had severe or partial re-congestion by 60 days.3
1. Adams KF, et al. Am Heart J. 2005
2. Krum H and Abraham WT. Lancet 2009
3. Lala A, et al. JCF 2013
Identifying congestion early will lead to early treatment,
prevent hospitalizations and slow the progression of HF.
17
60%
40%
Congestion state at discharge
Absent or mild
congestion
Moderate to
severe congestion
59%24%
17%
Congestion state of patients discharged
without congestion at 60 day follow-up3
Maintained
decongestion
Partial recongestion
Relapse to severe
congestion
US-2000480 A EN (08/14) | This document is approved for US use only.
TELE-HF Trial: Telemonitoring of Weight and
Symptoms Do Not Reduce Readmission or Death
 Randomized study of 1653 patients
 Primary endpoint: Readmission for any reason or death from any cause
within 180 days after enrollment
 Control group = Standard-of-care (no telemonitoring)
 Treatment group = telemonitoring of symptoms and weight
 Results: No difference in number of deaths, readmissions or days in hospital
Chaudhry SI, et al. N Engl J Med, 2010.
0
10
20
30
40
50
60
Re-hospitalization Death
%ofPatients
Telemonitoring of Symptoms
and Weight group
Standard-of-care Group
p = 0.39
p = 0.86
18
US-2000480 A EN (08/14) | This document is approved for US use only.
TIM-HF Trial: Telemonitoring of Weight and Blood
Pressure Do Not Reduce Readmission or Mortality
 Randomized study of 710 patients
 Primary Endpoint: Total Mortality
 Control Group: Standard-of-care (no telemonitoring)
 Treatment Group: Telemonitoring of weight and BP information
 Results: No difference in all-cause death or HF hospitalizations
Koehler F et al, Circulation 2011.
End Point
Telemonitoring
n = 354 (%)
Usual care
n = 356 (%)
HR
(95% CI)
p
All-cause
mortality
15.3 15.4 0.97 (0.67-1.41) 0.87
Cardiovascular-
related mortality
11.3 12.9 0.86 (0.56-1.31) 0.49
All-cause
readmission
54.2 50.3 1.12 (0.91-1.37) 0.29
19
US-2000480 A EN (08/14) | This document is approved for US use only.
1. Abraham WT, et al. Congest Heart Fail, 2011.
2. Conraads VM, et al. EHJ, 2011.
3. Yu CM, et al. Circulation, 2005.
4. St. Jude Medical. Bradycardia and Tachycardia Devices Merlin® Patient Care System Help Manual, 2012.
Sensitivity of Impedance
 Intra-thoracic impedance has been shown to be more sensitive than
weight changes.1
 Impedance still has a high false-positive rate1-3 when used to predict
acute events.
Note:
 Results from FAST1 and MID-HeFT3 are not included in the table above as these studies
used a broader definition of True Positive and therefore cannot be compared to the results
from SENSE-HF.
 Definition for True Positive was comparable but not the same in the calculations for Sensitivity,
FP/pt/yr, and PPV% between SENSE-HF and DEFEAT-PE, therefore these numbers should not
be directly compared.
20
Study FP/pt/yr PPV % Sensitivity %
SENSE-HF2 1 4.7 20.7-42.1
DEFEAT-PE4 0.96 16.07 26.6%
US-2000480 A EN (08/14) | This document is approved for US use only.
1. Whellan DJ, et al. JACC, 2010.
2. Cowie MR, et al. EHJ 2013.
Impedance Monitoring Combined with Multiple
Device-Derived Diagnostics May Be Used in
Risk Stratification
Study Description Implication
PARTNERS-HF1
Impedance monitoring combined
with device diagnostics
High (> 100) fluid index threshold identified
patients at a 3.9-fold risk of HF hospitalization
with pulmonary congestion (p < 0.0001)
HF Risk Score2
Development and validation of combining
multiple device-derived diagnostic parameters
into a single-dynamic HF risk score
HF risk score may be used to triage patients at
a higher risk for HF events in the next 30 days
21
US-2000480 A EN (08/14) | This document is approved for US use only.
Clinical Examination has Limited Reliability in
Assessing Filling Pressures
Data from clinical evaluations has poor sensitivity and predictive value
in determining hemodynamic profile.
22
* Table adapted from Capomolla S, et al. Eur J Heart Failure, 2005.
Capomolla, 2005. N = 366
Variable
Estimate
of
Sensitivity
(%)
Specificity
(%)
PPV
(%)
NPV
(%)
JVP
Edema
RAP 48
10
78
94
60
55
69
60
Pulse Press Cardiac Index 27 69 52 44
S3
Dyspnea
Rales
PCWP 36
50
13
81
73
90
69
67
60
54
57
48
Hemodynamic Monitoring for
Heart Failure Management
 Managing Pressures in the Heart Failure Patient
 CardioMEMS™ HF System
 CHAMPION Clinical Trial
US-2000480 A EN (08/14) | This document is approved for US use only.
Managing Pressures in the Heart Failure Patient
Pressures Patient
When patients are stable  Their pressures remain very stable over time.
When patient’s decompensate  Pressures increase, leading to exacerbation.
The pressures return to baseline
when the exacerbation is treated
and volume returns to normal
 Pressures reflect the underlying volume state
in HF patients.
 Strongly supports the hypothesis that
measuring those pressures frequently or
continuously using implantable devices and
managing those pressures may be a superior
management strategy.
Managing to targeted
pressure ranges
 Can reduce overall pressures and ultimately
lead to a reduction in HF events.
24
Adamson PB, et al. Curr Heart Fail Reports, 2009
US-2000480 A EN (08/14) | This document is approved for US use only.
COMPASS Trial Sub-Analysis
Higher Chronic PA Pressures Increase the Risk of HF Events
Stevenson L et al. Circ Heart Fail 2010;3:580-587
25
US-2000480 A EN (08/14) | This document is approved for US use only.
Pulmonary Artery
Pressure Sensor
Patient
Electronics
System
CardioMEMS™
HF Website
CardioMEMS™ HF System
26
US-2000480 A EN (08/14) | This document is approved for US use only.
CardioMEMS™ HF System
The pulmonary artery pressure
sensor is implanted via a right
heart catheterization procedure
via femoral vein approach.
27
Target location for pulmonary
artery pressure sensor
US-2000480 A EN (08/14) | This document is approved for US use only.
CHAMPION Clinical Trial: The Effect of Pulmonary
Artery Pressure-Guided Therapy on HF
Hospitalizations vs. Standard of Care
Patients with moderate NYHA class III HF for at least 3 months, irrespective of LVEF
and a HF hospitalization within the past 12 months were included in the study.
Abraham WT, et al. Lancet, 2011.
550 Pts w/CMEMS Implants
All Pts Take Daily readings
Treatment
270 Pts
Management Based on
PA Pressure +Traditional Info
Control
280 Pts
Management Based on
Traditional Info
26 (9.6%) Exited
< 6 Months
15 (5.6%) Death
11 (4.0%) Other
Primary Endpoint: Rate of HF Hospitalization
26 (9.6%) Exited
< 6 Months
20 (7.1%) Death
6 (2.2%) Other
Secondary Endpoints:
 Change in PA Pressure at 6 months
 No. of patients admitted to hospital for HF
 Days alive outside of hospital
 QOL
28
US-2000480 A EN (08/14) | This document is approved for US use only.
CHAMPION Clinical Trial: Managing to
Target PA Pressures
Abraham WT, et al. Lancet, 2011.
550 Pts w/CMEMS Implants
All Pts Take Daily readings
Treatment
270 Pts
Management Based on
PA Pressure +Traditional Info
Control
280 Pts
Management Based on
Traditional Info
26 (9.6%) Exited
< 6 Months
15 (5.6%) Death
11 (4.0%) Other
Primary Endpoint: rate of HF Hospitalization
26 (9.6%) Exited
< 6 Months
20 (7.1%) Death
6 (2.2%) Other
Secondary Endpoints included:
 Change in PA Pressure at 6 months
 No. of patients admitted to hospital for HF
 Days alive outside of hospital
 QOL
PA pressures were managed to target goal
pressures by physicians with appropriate
titration of HF medications.
Target Goal PA Pressures:
 PA Pressure Systolic 15 – 35 mmHg
 PA Pressure diastolic 8 – 20 mmHg
 PA Pressure mean 10 – 25 mmHg
29
US-2000480 A EN (08/14) | This document is approved for US use only.
Abraham WT, et al. Lancet, 2011.
CHAMPION Clinical Trial: PA Pressure-guided
Therapy Reduces HF Hospitalizations
30
Patients managed with PA pressure data had significantly fewer
HF hospitalizations as compared to the control group.
US-2000480 A EN (08/14) | This document is approved for US use only.
CHAMPION Trial: Both Primary Safety Endpoints
and All Secondary Endpoints Were Met at 6 months
Treatment
(n = 270)
Control
(n = 280)
P-value
Primary
Safety
Endpoints
Device related or system-related
complications
3 (1%) 3 (1%)
Total 8 (1%)* < 0.0001
Pressure-sensor failures 0 0 < 0.0001
Secondary
Endpoints
Change from baseline in PA mean
pressure (mean AUC [mm Hg 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
* Total of 8 DSRCs including 2 events in Consented not implanted patients (n = 25)
Abraham WT, et al. Lancet, 2011.
31
US-2000480 A EN (08/14) | This document is approved for US use only.
CHAMPION Clinical Trial: The Number Needed
to Treat (NNT) to Prevent One HF-related
Hospitalization is Lower vs. Other Therapies
Intervention Trial
Mean Duration
of Randomized
Follow-Up
Annualized Reduction
in HF Hospitalization
Rates
NNT per year to
Prevent 1 HF
Hospitalization
Beta-blocker COPERNICUS 10 months 33% 7
Aldosterone antagonist RALES 24 months 36% 7
CRT CARE-HF 29 months 52% 7
Beta-blocker MERIT-HF 12 months 29% 15
ACE inhibitor SOLVD 41 months 30% 15
Aldosterone antagonist EMPHASIS-HF 21 months 38% 16
Digoxin DIG 37 months 24% 17
Angiotensin
receptor blocker
Val-HeFT 23 months 23% 18
Angiotensin
receptor blocker
CHARM 40 months 27% 19
PA pressure
monitoring
CHAMPION 17 months 33% 4
32
US-2000480 A EN (08/14) | This document is approved for US use only.
CHAMPION Clinical Trial: PA Pressure-Guided
Therapy Improves Outcomes in CRT Patients1 and
in Patients with Preserved Systolic Function2
33
1. Weiner et al. Heart Rhythm, 2011 Additional data on file..
2. Adamson et al. JCF Nov 2010.
0%
10%
20%
30%
40%
50%
60%
with CRT without CRT HFpEF
RelativeRiskReduction
HF Hospitalization Reduction
(6 mos follow-up)
P = 0.0080 vs. controlP = 0.0071 vs. control
preserved EF (≥ 40%)
P < 0.0001 vs. control
US-2000480 A EN (08/14) | This document is approved for US use only.
Pulmonary Artery Pressure
Medication Changes based on Pulmonary
Artery Pressure (p < 0.0001)
Pulmonary Artery Pressure Reduction
(p = 0.008)
Reduction in Heart Failure Hospitalizations
(p < 0.0001)
Quality of Life Improvement
(p = 0.024)
Managing pressures to
target goal ranges:
 PA Pressure systolic 15–35 mmHg
 PA Pressure diastolic 8–20 mmHg
 PA Pressure mean 10–25 mmHg
Summary: CHAMPION Clinical Trial
34
Abraham WT, et al. Lancet, 2011.
US-2000480 A EN (08/14) | This document is approved for US use only.
Summary: Managing Pressures to Maintain Health
and Manage Acute Events
Enables proactive
and personalized
HF management 1-3
May be used in
risk stratification,
but not actionable4-7
Unreliable, late, and
indirect markers8,9
* Graph adapted from Adamson PB, et al.
Curr Heart Fail Reports, 2009.
1. Steimle AE, et al. Circulation, 1997.
2. Abraham WT, et al. Lancet, 2011
3. Ritzema J, et al. Circulation, 2010.
4. Abraham WT, HFSA, 2009.
5. Conraads VM, et al. EHJ, 2011.
6. Whellan DJ, et al. JACC, 2010.
7. van Veldhuisen DJ, et al.
Circulation, 2011.
8. Chaudry SI, et al. NEJM 2010
9. Anker SD, et al. AHA 2010
35
US-2000480 A EN (08/14) | This document is approved for US use only.
Heart Failure
36
 Telemonitoring with hemodynamic monitoring has
shown no benefits in the absence of interventional
guidelines
 Telemonitoring without hemodynamics have shown
limited benefits in management of heart failure
patients
US-2000480 A EN (08/14) | This document is approved for US use only.
Telemonitoring with Hemodynamic Guidance
37
US-2000480 A EN (08/14) | This document is approved for US use only.
Virtual Clinic
38
US-2000480 A EN (08/14) | This document is approved for US use only.
Hospital-Cardiac Rehab
39
US-2000480 A EN (08/14) | This document is approved for US use only.
Telemedicine: Partnership
40
US-2000480 A EN (08/14) | This document is approved for US use only.
Home Monitoring Pharmacy Partnership
41
US-2000480 A EN (08/14) | This document is approved for US use only.
EMS Partners- Home Health- Partners-Urgent Care
42
US-2000480 A EN (08/14) | This document is approved for US use only.
Telemedicine Kit
43
US-2000480 A EN (08/14) | This document is approved for US use only.
Believe in Physical Exam
44
US-2000480 A EN (08/14) | This document is approved for US use only.
The Vision
45
=
US-2000480 A EN (08/14) | This document is approved for US use only.
Concepts
46
US-2000480 A EN (08/14) | This document is approved for US use only.
Industrial & Mechanical Design
Leverage Standard Manufacturing Processes
47
US-2000480 A EN (08/14) | This document is approved for US use only.48
US-2000480 A EN (08/14) | This document is approved for US use only.49
US-2000480 A EN (08/14) | This document is approved for US use only.

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Bello presentation[2]

  • 1. Telemedicine in the Management of Congestive Heart Failure David Bello MD Chief, Cardiology Orlando Regional Medical Center Founder, HeartBuds
  • 2. Telemedicine in Chronic Disease Management CMS Story: higher quality, less readmissions, less cost
  • 3. Goals of Pilot  Higher patient satisfaction  Higher quality  Less Cost  Less readmissions
  • 4. US-2000480 A EN (08/14) | This document is approved for US use only.
  • 5. Physiologic Monitoring for Heart Failure Management
  • 6. US-2000480 A EN (08/14) | This document is approved for US use only. Contents  Heart Failure (HF)  Prevalence, incidence, mortality and hospitalization rates  Economic burden of HF and Medicare reform initiatives  Physiologic Monitoring  Worsening HF/Physiologic markers of decompensation  Weight, blood pressure, symptoms  Impedance  Clinical evaluations  Hemodynamic Monitoring for Heart Failure Management  Managing pressures in the heart failure patient  CardioMEMS™ HF System  CHAMPION clinical trial 6
  • 7. Heart Failure  Prevalence, Incidence, Mortality and Hospitalization Rates  Economic Burden of HF and Medicare Reform Initiatives
  • 8. US-2000480 A EN (08/14) | This document is approved for US use only. Heart Failure – A Growing Global Concern Prevalence and Incidence  Overall 2.1% prevalence: 5.1M heart failure patients in 20101  825,000 people ≥ 45 years of age are newly diagnosed each year with HF1  15 M heart failure patients in the ESC 51-member countries2  Overall 2-3% prevalence2 Mortality  For AHA/ACC stage C/D patients diagnosed with HF:  30% will die in the first year. 3-5  60% will die within 5 years.5 8 1. AHA 2014 Statistics at a Glance, 2014 2. The European Society of Cardiology, ESC HF Guideline, 2008 3. Curtis et al, Arch Intern Med, 2008. 4. Roger et al. JAMA, 2004. 5. Cowie et al, EHJ, 2002. 6. Heidenreich PA et al. Circ Heart Failure 2013. HF prevalence in the US is projected to increase 46% from 2012 to 2030, resulting in > 8M people ≥ 18 years of age with HF.6
  • 9. US-2000480 A EN (08/14) | This document is approved for US use only. Heart Failure Is Associated with High Hospitalization and Readmission Rates  In 2010, there were 1 million hospitalizations in the US with HF as the principal diagnosis1  Hospitalization rate did not change significantly from 20001  Average length of hospital stay  Approximately 5 days (US)2  11 days (Europe)3  HF is also associated with high readmission rates:  ~25% all-cause readmission within 30 days and ~50% within 6 months5 1. CDC NCHS National Hospital Discharge Survey, 2000-2010 2. Yancy et al. JACC, 2006. 3. Cleland et al. EuroHeart, 2003. 4. Krumholz HM, et al. Circ Cardiovas Qual Outcomes 2009. 5. Wexler DJ, et al. Am Heart J 2001. Graph from www.health.org.uk. Bridging the gap: Heart Failure, 2010. Data from Organization for Economic Cooperation and Development, 2009. 9 1. CDC NCHS National Hospital Discharge Survey, 2000-2010 2. Yancy et al. JACC, 2006. 3. Cleland et al. EuroHeart, 2003. 4. Krumholz HM, et al. Circ Cardiovas Qual Outcomes 2009. 5. Wexler DJ, et al. Am Heart J 2001. 1. CDC NCHS National Hospital Discharge Survey, 2000-2010 2. Yancy et al. JACC, 2006. 3. Cleland et al. EuroHeart, 2003. 4. Krumholz HM, et al. Circ Cardiovas Qual Outcomes 2009. 5. Wexler DJ, et al. Am Heart J 2001.
  • 10. US-2000480 A EN (08/14) | This document is approved for US use only. Worsening Heart Failure Leading to HF Hospitalizations Contributes to Disease Progression With each subsequent HF-related admission, the patient leaves the hospital with a further decrease in cardiac function. Graph adapted from: Gheorghiade MD, et al. Am J. Cardiol. 2005 10
  • 11. US-2000480 A EN (08/14) | This document is approved for US use only. Economic Burden of HF Will Continue to Rise Through 2030*  The AHA estimates that the total medical costs for HF are projected to increase to $70B by 2030  a 2-fold increase from 2013.1  50% of the costs are attributed to hospitalization.2 11 Graph: Heidenreich PA, et al. Circulation Heart Failure 2013. *Study projections assumes HF prevalence remains constant and continuation of current hospitalization practices 1. Heidenreich PA, et al. Circulation Heart Failure 2013. 2. Yancy CW, et al. Circulation 2013.
  • 12. US-2000480 A EN (08/14) | This document is approved for US use only. Economic Risks of HF Readmissions in the US Medicare’s Hospital Readmissions Reduction program penalizes hospitals that have above average all-cause readmissions within 30 days following HF discharge. 1. Dharmarajan K, et al. JAMA. 2013;309(4):355-363. 2. Linden A, Adler-Milstein J. Health Care Finance Rev. 2008;29(3):1-11. 3. CMS Hospitals Readmissions Reductions Program of the Patient Protection and Affordable Care Act (PPACA), 2010. 24.8%national average 30-day readmissions rate1,2 Fiscal Year 2013 2014 2015+ % payment withholding up to 1% up to 2% up to 3% Percent withholding of all inpatient Medicare payments will increase to up to 3% by 2015 and beyond.3 12
  • 13. Physiologic Monitoring  Worsening Heart Failure/Physiologic Markers of Decompensation  Weight, Blood Pressure, Symptoms  Impedance  Clinical Evaluations
  • 14. US-2000480 A EN (08/14) | This document is approved for US use only. 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 Increases in Pressure Start the Cycle of Worsening Heart Failure 14 Adapted from Jaski BE, “Basics of Heart Failure A Problem Solving Approach”    
  • 15. US-2000480 A EN (08/14) | This document is approved for US use only. Time Course of Decompensation Physiologic Markers of Acute Decompensation 15 * Graph adapted from Adamson PB, et al. Curr Heart Fail Reports, 2009.
  • 16. US-2000480 A EN (08/14) | This document is approved for US use only. Physiologic Markers of Acute Decompensation 16 * Graph adapted from Adamson PB, et al. Curr Heart Fail Reports, 2009.
  • 17. US-2000480 A EN (08/14) | This document is approved for US use only. Current HF Management Is Inadequate For Identifying and Managing Congestion Leading to Decompensation  90% of HF hospitalizations present with symptoms of pulmonary congestion.1,2  Post hoc analysis of 463 acute decompensated HF patients from DOSE-HF and CARRESS-HF trials showed:  40% of patients are discharged with moderate to severe congestion.3  Of patients decongested at discharge, 41% had severe or partial re-congestion by 60 days.3 1. Adams KF, et al. Am Heart J. 2005 2. Krum H and Abraham WT. Lancet 2009 3. Lala A, et al. JCF 2013 Identifying congestion early will lead to early treatment, prevent hospitalizations and slow the progression of HF. 17 60% 40% Congestion state at discharge Absent or mild congestion Moderate to severe congestion 59%24% 17% Congestion state of patients discharged without congestion at 60 day follow-up3 Maintained decongestion Partial recongestion Relapse to severe congestion
  • 18. US-2000480 A EN (08/14) | This document is approved for US use only. TELE-HF Trial: Telemonitoring of Weight and Symptoms Do Not Reduce Readmission or Death  Randomized study of 1653 patients  Primary endpoint: Readmission for any reason or death from any cause within 180 days after enrollment  Control group = Standard-of-care (no telemonitoring)  Treatment group = telemonitoring of symptoms and weight  Results: No difference in number of deaths, readmissions or days in hospital Chaudhry SI, et al. N Engl J Med, 2010. 0 10 20 30 40 50 60 Re-hospitalization Death %ofPatients Telemonitoring of Symptoms and Weight group Standard-of-care Group p = 0.39 p = 0.86 18
  • 19. US-2000480 A EN (08/14) | This document is approved for US use only. TIM-HF Trial: Telemonitoring of Weight and Blood Pressure Do Not Reduce Readmission or Mortality  Randomized study of 710 patients  Primary Endpoint: Total Mortality  Control Group: Standard-of-care (no telemonitoring)  Treatment Group: Telemonitoring of weight and BP information  Results: No difference in all-cause death or HF hospitalizations Koehler F et al, Circulation 2011. End Point Telemonitoring n = 354 (%) Usual care n = 356 (%) HR (95% CI) p All-cause mortality 15.3 15.4 0.97 (0.67-1.41) 0.87 Cardiovascular- related mortality 11.3 12.9 0.86 (0.56-1.31) 0.49 All-cause readmission 54.2 50.3 1.12 (0.91-1.37) 0.29 19
  • 20. US-2000480 A EN (08/14) | This document is approved for US use only. 1. Abraham WT, et al. Congest Heart Fail, 2011. 2. Conraads VM, et al. EHJ, 2011. 3. Yu CM, et al. Circulation, 2005. 4. St. Jude Medical. Bradycardia and Tachycardia Devices Merlin® Patient Care System Help Manual, 2012. Sensitivity of Impedance  Intra-thoracic impedance has been shown to be more sensitive than weight changes.1  Impedance still has a high false-positive rate1-3 when used to predict acute events. Note:  Results from FAST1 and MID-HeFT3 are not included in the table above as these studies used a broader definition of True Positive and therefore cannot be compared to the results from SENSE-HF.  Definition for True Positive was comparable but not the same in the calculations for Sensitivity, FP/pt/yr, and PPV% between SENSE-HF and DEFEAT-PE, therefore these numbers should not be directly compared. 20 Study FP/pt/yr PPV % Sensitivity % SENSE-HF2 1 4.7 20.7-42.1 DEFEAT-PE4 0.96 16.07 26.6%
  • 21. US-2000480 A EN (08/14) | This document is approved for US use only. 1. Whellan DJ, et al. JACC, 2010. 2. Cowie MR, et al. EHJ 2013. Impedance Monitoring Combined with Multiple Device-Derived Diagnostics May Be Used in Risk Stratification Study Description Implication PARTNERS-HF1 Impedance monitoring combined with device diagnostics High (> 100) fluid index threshold identified patients at a 3.9-fold risk of HF hospitalization with pulmonary congestion (p < 0.0001) HF Risk Score2 Development and validation of combining multiple device-derived diagnostic parameters into a single-dynamic HF risk score HF risk score may be used to triage patients at a higher risk for HF events in the next 30 days 21
  • 22. US-2000480 A EN (08/14) | This document is approved for US use only. Clinical Examination has Limited Reliability in Assessing Filling Pressures Data from clinical evaluations has poor sensitivity and predictive value in determining hemodynamic profile. 22 * Table adapted from Capomolla S, et al. Eur J Heart Failure, 2005. Capomolla, 2005. N = 366 Variable Estimate of Sensitivity (%) Specificity (%) PPV (%) NPV (%) JVP Edema RAP 48 10 78 94 60 55 69 60 Pulse Press Cardiac Index 27 69 52 44 S3 Dyspnea Rales PCWP 36 50 13 81 73 90 69 67 60 54 57 48
  • 23. Hemodynamic Monitoring for Heart Failure Management  Managing Pressures in the Heart Failure Patient  CardioMEMS™ HF System  CHAMPION Clinical Trial
  • 24. US-2000480 A EN (08/14) | This document is approved for US use only. Managing Pressures in the Heart Failure Patient Pressures Patient When patients are stable  Their pressures remain very stable over time. When patient’s decompensate  Pressures increase, leading to exacerbation. The pressures return to baseline when the exacerbation is treated and volume returns to normal  Pressures reflect the underlying volume state in HF patients.  Strongly supports the hypothesis that measuring those pressures frequently or continuously using implantable devices and managing those pressures may be a superior management strategy. Managing to targeted pressure ranges  Can reduce overall pressures and ultimately lead to a reduction in HF events. 24 Adamson PB, et al. Curr Heart Fail Reports, 2009
  • 25. US-2000480 A EN (08/14) | This document is approved for US use only. COMPASS Trial Sub-Analysis Higher Chronic PA Pressures Increase the Risk of HF Events Stevenson L et al. Circ Heart Fail 2010;3:580-587 25
  • 26. US-2000480 A EN (08/14) | This document is approved for US use only. Pulmonary Artery Pressure Sensor Patient Electronics System CardioMEMS™ HF Website CardioMEMS™ HF System 26
  • 27. US-2000480 A EN (08/14) | This document is approved for US use only. CardioMEMS™ HF System The pulmonary artery pressure sensor is implanted via a right heart catheterization procedure via femoral vein approach. 27 Target location for pulmonary artery pressure sensor
  • 28. US-2000480 A EN (08/14) | This document is approved for US use only. CHAMPION Clinical Trial: The Effect of Pulmonary Artery Pressure-Guided Therapy on HF Hospitalizations vs. Standard of Care Patients with moderate NYHA class III HF for at least 3 months, irrespective of LVEF and a HF hospitalization within the past 12 months were included in the study. Abraham WT, et al. Lancet, 2011. 550 Pts w/CMEMS Implants All Pts Take Daily readings Treatment 270 Pts Management Based on PA Pressure +Traditional Info Control 280 Pts Management Based on Traditional Info 26 (9.6%) Exited < 6 Months 15 (5.6%) Death 11 (4.0%) Other Primary Endpoint: Rate of HF Hospitalization 26 (9.6%) Exited < 6 Months 20 (7.1%) Death 6 (2.2%) Other Secondary Endpoints:  Change in PA Pressure at 6 months  No. of patients admitted to hospital for HF  Days alive outside of hospital  QOL 28
  • 29. US-2000480 A EN (08/14) | This document is approved for US use only. CHAMPION Clinical Trial: Managing to Target PA Pressures Abraham WT, et al. Lancet, 2011. 550 Pts w/CMEMS Implants All Pts Take Daily readings Treatment 270 Pts Management Based on PA Pressure +Traditional Info Control 280 Pts Management Based on Traditional Info 26 (9.6%) Exited < 6 Months 15 (5.6%) Death 11 (4.0%) Other Primary Endpoint: rate of HF Hospitalization 26 (9.6%) Exited < 6 Months 20 (7.1%) Death 6 (2.2%) Other Secondary Endpoints included:  Change in PA Pressure at 6 months  No. of patients admitted to hospital for HF  Days alive outside of hospital  QOL PA pressures were managed to target goal pressures by physicians with appropriate titration of HF medications. Target Goal PA Pressures:  PA Pressure Systolic 15 – 35 mmHg  PA Pressure diastolic 8 – 20 mmHg  PA Pressure mean 10 – 25 mmHg 29
  • 30. US-2000480 A EN (08/14) | This document is approved for US use only. Abraham WT, et al. Lancet, 2011. CHAMPION Clinical Trial: PA Pressure-guided Therapy Reduces HF Hospitalizations 30 Patients managed with PA pressure data had significantly fewer HF hospitalizations as compared to the control group.
  • 31. US-2000480 A EN (08/14) | This document is approved for US use only. CHAMPION Trial: Both Primary Safety Endpoints and All Secondary Endpoints Were Met at 6 months Treatment (n = 270) Control (n = 280) P-value Primary Safety Endpoints Device related or system-related complications 3 (1%) 3 (1%) Total 8 (1%)* < 0.0001 Pressure-sensor failures 0 0 < 0.0001 Secondary Endpoints Change from baseline in PA mean pressure (mean AUC [mm Hg 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 * Total of 8 DSRCs including 2 events in Consented not implanted patients (n = 25) Abraham WT, et al. Lancet, 2011. 31
  • 32. US-2000480 A EN (08/14) | This document is approved for US use only. CHAMPION Clinical Trial: The Number Needed to Treat (NNT) to Prevent One HF-related Hospitalization is Lower vs. Other Therapies Intervention Trial Mean Duration of Randomized Follow-Up Annualized Reduction in HF Hospitalization Rates NNT per year to Prevent 1 HF Hospitalization Beta-blocker COPERNICUS 10 months 33% 7 Aldosterone antagonist RALES 24 months 36% 7 CRT CARE-HF 29 months 52% 7 Beta-blocker MERIT-HF 12 months 29% 15 ACE inhibitor SOLVD 41 months 30% 15 Aldosterone antagonist EMPHASIS-HF 21 months 38% 16 Digoxin DIG 37 months 24% 17 Angiotensin receptor blocker Val-HeFT 23 months 23% 18 Angiotensin receptor blocker CHARM 40 months 27% 19 PA pressure monitoring CHAMPION 17 months 33% 4 32
  • 33. US-2000480 A EN (08/14) | This document is approved for US use only. CHAMPION Clinical Trial: PA Pressure-Guided Therapy Improves Outcomes in CRT Patients1 and in Patients with Preserved Systolic Function2 33 1. Weiner et al. Heart Rhythm, 2011 Additional data on file.. 2. Adamson et al. JCF Nov 2010. 0% 10% 20% 30% 40% 50% 60% with CRT without CRT HFpEF RelativeRiskReduction HF Hospitalization Reduction (6 mos follow-up) P = 0.0080 vs. controlP = 0.0071 vs. control preserved EF (≥ 40%) P < 0.0001 vs. control
  • 34. US-2000480 A EN (08/14) | This document is approved for US use only. Pulmonary Artery Pressure Medication Changes based on Pulmonary Artery Pressure (p < 0.0001) Pulmonary Artery Pressure Reduction (p = 0.008) Reduction in Heart Failure Hospitalizations (p < 0.0001) Quality of Life Improvement (p = 0.024) Managing pressures to target goal ranges:  PA Pressure systolic 15–35 mmHg  PA Pressure diastolic 8–20 mmHg  PA Pressure mean 10–25 mmHg Summary: CHAMPION Clinical Trial 34 Abraham WT, et al. Lancet, 2011.
  • 35. US-2000480 A EN (08/14) | This document is approved for US use only. Summary: Managing Pressures to Maintain Health and Manage Acute Events Enables proactive and personalized HF management 1-3 May be used in risk stratification, but not actionable4-7 Unreliable, late, and indirect markers8,9 * Graph adapted from Adamson PB, et al. Curr Heart Fail Reports, 2009. 1. Steimle AE, et al. Circulation, 1997. 2. Abraham WT, et al. Lancet, 2011 3. Ritzema J, et al. Circulation, 2010. 4. Abraham WT, HFSA, 2009. 5. Conraads VM, et al. EHJ, 2011. 6. Whellan DJ, et al. JACC, 2010. 7. van Veldhuisen DJ, et al. Circulation, 2011. 8. Chaudry SI, et al. NEJM 2010 9. Anker SD, et al. AHA 2010 35
  • 36. US-2000480 A EN (08/14) | This document is approved for US use only. Heart Failure 36  Telemonitoring with hemodynamic monitoring has shown no benefits in the absence of interventional guidelines  Telemonitoring without hemodynamics have shown limited benefits in management of heart failure patients
  • 37. US-2000480 A EN (08/14) | This document is approved for US use only. Telemonitoring with Hemodynamic Guidance 37
  • 38. US-2000480 A EN (08/14) | This document is approved for US use only. Virtual Clinic 38
  • 39. US-2000480 A EN (08/14) | This document is approved for US use only. Hospital-Cardiac Rehab 39
  • 40. US-2000480 A EN (08/14) | This document is approved for US use only. Telemedicine: Partnership 40
  • 41. US-2000480 A EN (08/14) | This document is approved for US use only. Home Monitoring Pharmacy Partnership 41
  • 42. US-2000480 A EN (08/14) | This document is approved for US use only. EMS Partners- Home Health- Partners-Urgent Care 42
  • 43. US-2000480 A EN (08/14) | This document is approved for US use only. Telemedicine Kit 43
  • 44. US-2000480 A EN (08/14) | This document is approved for US use only. Believe in Physical Exam 44
  • 45. US-2000480 A EN (08/14) | This document is approved for US use only. The Vision 45 =
  • 46. US-2000480 A EN (08/14) | This document is approved for US use only. Concepts 46
  • 47. US-2000480 A EN (08/14) | This document is approved for US use only. Industrial & Mechanical Design Leverage Standard Manufacturing Processes 47
  • 48. US-2000480 A EN (08/14) | This document is approved for US use only.48
  • 49. US-2000480 A EN (08/14) | This document is approved for US use only.49
  • 50. US-2000480 A EN (08/14) | This document is approved for US use only.

Editor's Notes

  1. Talking points included in this deck are for internal/speaker use only, and are not to be distributed.
  2. Talking points included in this deck are for internal/speaker use only, and are not to be distributed.
  3. Talking points included in this deck are for internal/speaker use only, and are not to be distributed.
  4. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. Chronic heart failure affects over 5 million people in the US, which is an overall prevalence of 2.1%. According to statistics reported by the AHA, approximately 825,000 new cases are diagnosed each year in patients 45 years of age and older. The significance of heart failure in Europe is similar to that of the US, where heart failure affects nearly 15 million people of the 900 million people from the 51-member countries of the ESC, amounting to an overall prevalence of 2-3%. Despite advances in the treatment of heart failure over the past few decades, the prognosis remains poor for patients diagnosed with heart failure. Data from the US and from Europe suggest that approximately 30% of patients will die within the first year of HF diagnosis. An analysis of Medicare data by Curtis and colleagues showed that 60% of patients will die within the first 5 years of diagnosis. References: 1. Go AS, et al. Heart Disease and Stroke Statistics – 2014 Update: A report from the American Heart Association. Circulation. 2014; 128: 1-268. 2. Dickstein K, et al. ESC Guidelines for the Diagnosis and Treatment of Acute and Chronic Heart Failure 2008. European Heart Journal. 2008; 29, 2388-2442. 3. Curtis LH, et al. Incidence and prevalence of heart failure in elderly persons, 1994-2003. Arch Intern Med. 2008 Feb 25;168(4):418-24. 4. Roger VL, et al. Trends in heart failure incidence and survival in a community-based population. JAMA 2004;292:344-50 5. Cowie MR, et al. Hospitalization of patients with heart failure: a population-based study. Eur Heart J. 2002 Jun;23(11):877-85. 6. Heidenreich PA, et al; on behalf of the American Heart Association Advocacy Coordinating Committee; Council on Arteriosclerosis, Thrombosis and Vascular Biology; Council on Cardiovascular Radiology and Intervention; Council on Clinical Cardiology; Council on Epidemiology and Prevention; Stroke Council. Forecasting the impact of heart failure in the United States: a policy statement from the American Heart Association. Circ Heart Fail. 2013;6:606–619.
  5. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. Heart failure is the underlying cause of 1.1 million hospitalizations per year in the US, where 44% of those hospitalized are Class III patients. Greater than 90% of HF patients who present at the hospital have symptoms of pulmonary congestion, which causes acute decompensation. The average length of hospital stay for acute decompensated heart failure in the US is approximately 5 days. The ADHERE registry reported an average hospital stay of 4.3 days, while the graph on the right shows just longer than 5 days. In Europe, according to the EuroHeart Failure Survey, the average hospital stay is about 11 days. The graph on the right illustrates the average length of HF-related hospitalizations across different countries. Despite these long hospital stays up to 40% of patients leave the hospital with symptoms due to inadequate diuresis. References: 1. Hall MJ, Levant S, DeFrances CJ. Hospitalization for congestive heart failure: United States, 2000–2010. NCHS data brief, no 108. Hyattsville, MD: National Center for Health Statistics. 2012.. 2. Yancy CW, ADHERE Scientific Advisory Committee and Investigators, et al. Clinical presentation, management, and in-hospital outcomes of patients admitted with acute decompensated heart failure with preserved systolic function: a report from the Acute Decompensated Heart Failure National Registry (ADHERE) Database. J Am Coll Cardiol. 2006 Jan 3;47(1):76-84. Epub 2005 Dec 15. 3. Cleland JG, Study Group on Diagnosis of the Working Group on Heart Failure of the European Society of Cardiology, et al. The EuroHeart Failure survey programme-- a survey on the quality of care among patients with heart failure in Europe. Part 1: patient characteristics and diagnosis. Eur Heart J. 2003 Mar;24(5):442-63. 4. Krumholz HM, et al. Patterns of hospital performance in acute myocardial infarction and heart failure 30-day mortality and readmission. Circ Cardiovasc Qual Outcomes. 2009;2:407-13. 5. Wexler DJ, et al. Predictors of costs of caring for elderly patients discharged with heart failure. Am Heart J 2001;142:350-7 .
  6. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. High rates of HF-related hospitalizations may further contribute to the progression of heart failure and LV dysfunction. With each admission for acute heart failure syndromes, there may be a short-term improvement. However, the patient often leaves with a further decrease in cardiac function. Graph adapted from: Gheorghiade MD, et al. Pathophysiologic targets in the early phase of acute heart failure syndromes. Am J Cardiol. 2005; 96[suppl]: 11G-17G.
  7. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. Heart failure is a major contributor to the overall cost of the national health care expenses. The cost of HF care is high and will remain a significant concern for the US health care system. The AHA projects that the total direct medical costs for HF will increase to $70B by 2030. This is a 2-fold increase from 2013, which was approximately $20.9B. Additionally, the majority of these HF-related costs (80%) are attributed to hospitalization costs. References: Heidenreich PA, et al. Forecasting the impact of heart failure in the United States. A policy statement from the American Heart Association. Circ Heart Fail. 2013; 6: 606-619. Yancy CW, et al. 2013 ACCF/AHA Guideline for the Management of Heart Failure: A report of the ACC/AHA Task Force on Practice Guidelines. Circulation. 2013;128:e240-e327.
  8. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. One of Medicare’s reform initiatives that has been introduced is the Hospital Readmissions Reduction program. This program penalizes hospitals with above national average all-cause 30-day readmission rate following HF discharge. Medicare is withholding up to 1% of all inpatient Medicare payments, this withholding will increase to up to 3 percent in fiscal year 2015 and beyond. 2 A technology that can decrease the risk of hospitalization is much needed. References: Dharmarajan K, Hsieh AF, Lin Z, et al. Diagnoses and timing of 30-day readmissions after hospitalization for heart failure, acute myocardial infarction, or pneumonia. JAMA. 2013;309(4):355-363. Linden A, Adler-Milstein J. Medicare disease management in policy context. Health Care Finance Rev. 2008;29(3):1-11. 3. CMS Hospitals Readmissions Reductions Program of the Patient Protection and Affordable Care Act (PPACA), 2010.
  9. Talking points included in this deck are for internal/speaker use only, and are not to be distributed.
  10. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. The acute HF syndrome that leads to worsening HF is a complex process and begins with increases in pressure the start the cycle.
  11. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. Physiologic markers of the development of acute decompensation include changes in filling pressures, impedance, weight, BP and symptoms. With respect to time course - changes in pressures occur early and cause decompensation while changes in weight, BP and symptoms occur later as a result of decompensation. Graph adapted from: Adamson PB. Pathophysiology of the transition from chronic compensated and acute decompensated heart failure: new insights from continuous monitoring devices. Curr Heart Fail Rep. 2009;6(4):287-92.
  12. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. If we look at the physiologic markers that are used today to manage HF patients, they occur late in the time during the course of decompensation and provide little time to react before a hospitalization – these include weight, symptoms and BP. In order to successfully manage HF patients and impact the time course of decompensation, you need to identify the issue before the patient becomes symptomatic and congested. Since increases in filling pressures cause decompensation, monitoring pressure changes will assist in identifying presymptomatic congestion in order to allow time to react and alter the time course of decompensation. Graph adapted from: Adamson PB. Pathophysiology of the transition from chronic compensated and acute decompensated heart failure: new insights from continuous monitoring devices. Curr Heart Fail Rep. 2009;6(4):287-92.
  13. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. How successful are we at managing congestion? 90% of patients who are hospitalized for HF present with symptoms of pulmonary congestion. A post-hoc analysis of DOSE-HF and CARRESS-HF trials analyzed the congestion relief 60 days following discharge of 463 acute decompensated HF patients who were hospitalized for HF. Each patient was assigned a congestion score at baseline, discharge and 60-day follow-up. Upon discharge, 40% of the patients still had moderate to severe congestion. Of the patients who were decongested at discharge, 41% had clinical recongestion at the 60 day follow-up. These data suggest that current HF management strategy is inadequate for identifying and managing congestion. Better tools and strategies are needed to identify congestion early, which can lead to early treatment, prevent hospitalizations, and slow the progression of HF. References: 1. Adams KF Jr, et al. Characteristics and outcomes of patients hospitalized for heart failure in the United States: rationale, design, and preliminary observations from the first 100,000 cases in the Acute Decompensated Heart Failure National Registry (ADHERE). Am Heart J. 2005 Feb;149(2):209-16. 2. Krum H and Abraham WT. Heart failure. Lancet. 2009;373(9667):941-55. 3. Lala A, et al. The Tides of Congestion during and after Hospitalization for Acute Decompensated Heart Failure. J Cardiac Fail. 2013;19(8):S81.
  14. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. So what data do we have on weight and symptoms to demonstrate their performance in managing HF patients? Short script: TELE-HF was a large multicenter trial with 1653 patients. Patients were randomized to telemonitoring of HF symptoms and weight changes or usual care. The telemonitoring group sent frequent updates of symptoms and weight changes to their clinicians. The TELE-HF study showed that patients who frequently updated their physicians with their changes in weight and symptoms did not have a reduction in hospitalization or mortality. Long script: TELE-HF was a large multicenter trial with 1653 patients. Patients were randomized to telemonitoring of HF symptoms and weight changes or usual care. The telemonitoring group sent frequent updates of symptoms and weight changes to their clinicians. All patients in TELE- HF had been hospitalized for HF in the previous 30 days, and all patients received a weight scale and educational material endorsed by the Heart Failure Society of America. The telemonitoring group made daily toll-free calls to the monitoring center, during which they input daily weight and answered questions about their general health and any heart failure symptoms. Every 30 days, they were asked additional questions that allowed for screening for depression. Data was uploaded from the phone system to a secure Internet site, where it was reviewed every weekday by trained coordinators at each site, and each question had predetermined responses that triggered “variances. ” Sites were required to contact any patient whose responses triggered these variances, and documented how the variances were managed. If patients did not call in for two consecutive days, they received an automated call, followed by a call from the site staff if necessary. The primary endpoint was a composite of all-cause mortality or all-cause hospital admissions within the first 180 days following enrollment in the study. Despite the positive results of the previously conducted pilot study, TELE-HF found no reduction in risk of all-cause mortality or all-cause hospitalization (primary endpoint), no reduction in the risk of HF hospitalizations, number of days in hospital or time to readmission or death. Reference: Chaudhry SI, et al. Telemonitoring in patients with heart failure. N Engl J Med. 2010;363(24):2301-9. Epub 2010 Nov 16. Presenter notes on TELE-HF study: METHODS: We randomly assigned 1653 patients who had recently been hospitalized for heart failure to undergo either telemonitoring (826 patients) or usual care (827 patients). Telemonitoring was accomplished by means of a telephone-based interactive voice-response system that collected daily information about symptoms and weight that was reviewed by the patients' clinicians. The primary end-point was readmission for any reason or death from any cause within 180 days after enrollment. Secondary end-points included hospitalization for heart failure, number of days in the hospital, and number of hospitalizations. RESULTS: The median age of the patients was 61 years; 42.0% were female, and 39.0% were black. The telemonitoring group and the usual-care group did not differ significantly with respect to the primary end point, which occurred in 52.3% and 51.5% of patients, respectively (difference, 0.8 percentage points; 95% confidence interval [CI], -4.0 to 5.6; P = 0.75 by the chi-square test). Readmission for any reason occurred in 49.3% of patients in the telemonitoring group and 47.4% of patients in the usual-care group (difference, 1.9 percentage points; 95% CI, -3.0 to 6.7; P = 0.45 by the chi-square test). Death occurred in 11.1% of the telemonitoring group and 11.4% of the usual care group (difference, -0.2 percentage points; 95% CI, -3.3 to 2.8; P = 0.88 by the chi-square test). There were no significant differences between the two groups with respect to the secondary end points or the time to the primary end-point or its components. No adverse events were reported. CONCLUSIONS: Among patients recently hospitalized for heart failure, telemonitoring did not improve outcomes. The results indicate the importance of a thorough, independent evaluation of disease-management strategies before their adoption. (Funded by the National Heart, Lung, and Blood Institute; ClinicalTrials.gov number, NCT00303212.).
  15. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. In another study looking at weight and blood pressure we see a similar result. The TIM-HF study was similar to that of TELE-HF except patients reported weight changes and BP. Data from TIM-HF showed no difference in all-cause death or HF hospitalizations between patients telemonitoring weight and BP information and those receiving usual care. Reference Koehler F, et al. Impact of remote telemedical management on mortality and hospitalizations in ambulatory patients with chronic heart failure: The Telemedical Interventional Monitoring in Heart Failure study. Circulation. 2011; 123: 1873-1880. TIM-HF:Anker SD, et al. Telemedical interventional monitoring in heart failure (TIM-HF), a randomized, controlled, intervention trial investigating the impact of telemedicine on mortality in ambulatory patients with chronic heart failure. American Heart Association 2010 Scientific Sessions; November 16, 2010; Chicago, IL. Cleland JG, et al. trials update from the American Heart Association Meeting 2010: EMPHASIS-HF, RAFT, TIM-HF, Tele-HF, ASCEND-HF, ROCKET-AF, and PROTECT. Eur J Heart Fail. 2011 Apr;13(4):460-5. Notes to presenter on TIM-HF study: AIMS: Remote patient management (telemonitoring) may help to detect early signs of cardiac decompensation, allowing optimization of and adherence to treatments in chronic heart failure (CHF). Two meta-analyses have suggested that telemedicine in CHF can reduce mortality by 30-35%. The aim of the TIM-HF study was to investigate the impact of telemedical management on mortality in ambulatory CHF patients. Methods: CHF patients [New York Heart Association (NYHA) II/III, left ventricular ejection fraction (LVEF) ≤ 35%] with a history of cardiac decompensation with hospitalization in the past or therapy with intravenous diuretics in the prior 24 months (no decompensation required if LVEF≤25%) were randomized 1:1 to an intervention group of daily remote device monitoring (electrocardiogram, blood pressure, body weight) coupled with medical telephone support or to usual care led by the patients' local physician. In the intervention group, 24/7 physician-led medical support was provided by two central telemedical centres. A clinical event committee blinded to treatment allocation assessed cause of death and reason for hospitalization. The primary endpoint was total mortality. The first secondary endpoint was a composite of cardiovascular mortality or hospitalization due to heart failure. Other secondary endpoints included cardiovascular mortality, all-cause and cause-specific hospitalizations (all time to first event) as well as days lost due to heart failure hospitalization or cardiovascular death (in % of follow-up time), and changes in quality of life and NYHA class. Overall, 710 CHF patients were recruited. The mean follow-up was 21.5 ± 7.2 months, with a minimum of 12 months.
  16. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. Congestion monitoring with device-based intra-thoracic impedance has been demonstrated to be more sensitive than weight changes in predicting HF events (FAST trial). The FAST, MID-HeFT, and SENSE-HF trials have evaluated the sensitivity of impedance in determining HF events. These studies have confirmed that impedance has a high false positive rate and moderate sensitivity suggesting that it should only be used as a risk stratification tool in combination with other diagnostics. Note: The lower sensitivity observed in SENSE-HF trial is partially due to a more stringent definition of true positive (TP) in this study. It is important to note that a positive predictive value of 5 translates to 1 in 20 readings is accurate and/or informative, therefore 19 out of 20 will be a false positive. Furthermore, impedance data are not actionable. References: 1. Abraham WT, Compton S, Haas G et al. Intrathoracic Impedance vs. Daily Weight Monitoring for Predicting Worsening Heart Failure Events: Results of the Fluid Accumulation Status Trial (FAST). Congest Heart Fail 2011 March;17(2):51-5. 2. Conraads VM, et al. Sensitivity and positive predictive value of implantable intrathoracic impedance monitoring as a predictor of heart failure hospitalizations: the SENSE-HF trial. Eur Heart J. 2011 Feb 28. [Epub ahead of print] 3. Yu CM, et al. Intrathoracic impedance monitoring in patients with heart failure: correlation with fluid status and feasibility of early warning preceding hospitalization. Circulation. 2005 Aug 9;112(6):841-8. Epub 2005 Aug 1. Notes to presenter on FAST trial: FAST trial FAST was designed as a prospective, nonrandomized trial with the aim of prospectively characterizing the utility of the intrathoracic impedance-derived fluid status, particularly its ability to predict the following HF-related health-care utilization events: Hospitalization (> 24 hours) Urgent care visit Emergency department visit HF-related unscheduled office visit A total of 47 patients (mean age, 68.8 years; 79% male) were enrolled in FAST at centers in Canada and the United States. Patients had mild-to-moderate HF (average NYHA functional class, 1.9) of ischemic etiology in almost three quarters (72.3%), and the mean 6-minute walk test was 319.2 m (range, 91-640). The OptiVol feature was downloaded into a CRT-D device (InSync Marquis; Medtronic) in all patients. Patients kept a daily log of weights, symptoms, medication changes, and clinic visits. The daily impedance data collected daily by the device were not available to the physician or patient. Patients were managed with conventional standard of care, and clinically relevant events representing significant fluid overload were collected on case report forms. These clinically relevant events were defined as signs and/or symptoms of pulmonary congestion associated with either an HF hospitalization or outpatient treatment with intravenous diuretics, or significant outpatient diuretic change (doubling of dose in a 1-day period or a therapeutic equivalent to doubling of diuretic dose). Events were adjudicated by an independent committee. Results Over a mean follow-up time of 5.4 months (252.5 total months of follow-up), there were 7 clinically relevant events in 4 patients. Five of these events were detected by OptiVol for a sensitivity of 71.4%. The false alarm rate was .9 false alarms per year of follow-up. Based on these data, the investigators predicted that in a larger sample size, a prospective detection rate of 70% with only 1 false alarm per year could be expected. Conclusion The primary aim of the trial design was to validate that the decreases in daily impedance correlated with HF decompensation events resulting from pulmonary congestion. Using the impedance-derived fluid status trends recorded by OptiVol in conjunction with other currently available clinical methods (eg, daily patient weights, physical examination, and chest x-rays) provides valuable assistance to physicians in assessing patients' thoracic fluid statuses. FAST: Abraham WT, Compton S, Haas G et al. Intrathoracic impedance vs. daily weight monitoring for predicting worsening heart failure Events: Results of the Fluid Accumulation Status Trial (FAST). Congest Heart Fail 2011;17(2):51-5.
  17. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. While the previous studies discussed reported on false positive rates, positive predictive value and sensitivity, the 2010 PARTNERS-HF study reported on the relationship between impedance levels and the risk of experiencing a HF event. The observational study showed that a high fluid index threshold identified patients to be at a 3.9-fold increased risk of a HF-event. It is important to note that a high fluid index increases specificity but it decreases sensitivity and therefore positive predictive value. While these data are important the clinical relevance is unclear. PARTNERS-HF showed that impedance monitoring combined with other device diagnostics may be a useful risk stratification tool, but this is only relevant to 1 in 4 patients due to device indications. Martin Cowie, et al developed and validated a HF risk score combining daily measurements of multiple device diagnostic parameters (including intrathoracic impedance) in a Bayesian Belief Network framework to improve the ability to identify when patients are at risk for HF-related hospitalizations. Results showed that patients who achieved a high-risk state on any day in the last 30 days were 10x more likely to be hospitalized for HF in the next 30 days compared to patients with a low-risk score. However, the study did not evaluate whether timely clinical actions initiated by the stratification of HF patients using the HF risk score on a regular basis can actually reduce HF-hospitalizations. So the HF risk score may currently only be used to triage patients at a higher risk for HF events in the next 30 days. Reference: 1. Whellan DJ, PARTNERS Study Investigators, et al. Combined heart failure device diagnostics identify patients at higher risk of subsequent heart failure hospitalizations: results from PARTNERS HF (Program to Access and Review Trending Information and Evaluate Correlation to Symptoms in Patients With Heart Failure) study. J Am Coll Cardiol. 2010 Apr 27;55(17):1803-10. 2. Cowie MR, et al. Development and validation of an integrated diagnostic algorithm derived from parameters monitored in implantable devices for identifying patients at risk for heart failure hospitalization in an ambulatory setting. Eur Heart J. 2013 Aug;34(31):2472-80
  18. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. Even clinical examinations are not highly predictive of assessing worsening heart failure Currently clinicians try to estimate filling pressure through examination and patient symptoms. However, these indirect measures of pressure have poor sensitivity and predictive value. Right atrial pressure (RAP) is measured by raised jugular vein pressure (JVP) and edema. Cardiac index is measured by proportional pulse pressure. Pulmonary capillary wedge pressure (PCWP) is measured by third heart sounds (S3), dyspnea and Rales. This table shows the sensitivity, specificity, positive predictive value and negative predictive value of these measures in determining the patients’ hemodynamic profile or status. RAP = Right Atrial Pressure PCWP = Pulmonary Capillary Wedge Pressure JVP = raised Jugular Venous Pressure Pulse press = clinical proportional pulse pressure (25%) S3 = Third heart sound Reference: Capomolla S, et al. Echo-Doppler and clinical evaluations to define hemodynamic profile in patients with chronic heart failure: accuracy and influence on therapeutic management. Eur J Heart Fail. 2005 Jun;7(4):624-30. Notes to presenter on Capomolla paper: BACKGROUND: Correct classification of chronic heart failure (CHF) patients by dual evidence of congestion and adequate perfusion is the primary clinical focus for management. OBJECTIVES: To evaluate the accuracy of echo-Doppler compared with clinical evaluation in determining the hemodynamic profile of patients with CHF; and to compare therapeutic changes based on hemodynamic or echo-Doppler findings. METHODS: Three hundred and sixty-six consecutive CHF patients (ejection fraction 25+/-7%) in sinus rhythm, undergoing evaluation for cardiac transplantation, underwent physical examination prior to right heart catheterization and echo-Doppler studies. Subsequently, patients were randomized to therapeutic optimization using either right heart catheterization or echo-Doppler data. The endpoints were: identification of low cardiac output (cardiac index < 2.2 l/min/m(2)); high pulmonary wedge pressure (PWP > 18 mmHg); high right atrial pressure (RAP > 5 mmHg) and analysis of therapeutic changes made in response to the right heart catheterization and echo-Doppler studies. RESULTS: Echo-Doppler showed better accuracy in estimating abnormal hemodynamic indices than clinical variables (cardiac index < 2.2 l/min/m(2): echo positive predictive accuracy (PPA) 98% vs. clinical PPA 52% p< 0.00001; PWP >18 mmHg: echo PPA 85% vs. clinical PPA 76% p = 0.0011; RAP > 5 mmHg: echo PPA 82% vs. clinical PPA 57% p< 0.00001). When applied to individual patients, the echo-Doppler assessment was more accurate than clinical evaluation in defining the different hemodynamic profiles: wet/cold (89% vs. 13%, p< 0.0001); wet/warm (73% vs. 30%, p< 0.0001); dry/cold (68% vs. 12%, p< 0.0001); dry/warm (88% vs. 51%, p< 0.0001). Therapeutic decision-making based on echo-Doppler findings was similar to that based on hemodynamics. CONCLUSION: Echo-Doppler hemodynamic monitoring proved accurate in estimating hemodynamic profiles and influenced therapeutic management Reference: Capomolla S, et al. Echo-Doppler and clinical evaluations to define hemodynamic profile in patients with chronic heart failure: accuracy and influence on therapeutic management. J Heart Fail. 2005 Jun;7(4):624-30.
  19. Talking points included in this deck are for internal/speaker use only, and are not to be distributed.
  20. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. In Adamson’s 2009 paper, he explains that when patients are stable, their pressures remain very stable over time. However, when patients decompensate, pressures increase, leading to the exacerbation. The pressures return to baseline when the exacerbation is treated and volume returns to normal. This provides convincing evidence that pressures reflectthe underlying volume state in patients with heart failure and strongly supports the hypothesis that measuring those pressures frequently or continuouslyusing implantable devices and managing those pressures may be a superior management strategy to quantifying daily weights. Managing to targeted pressure ranges can reduce overall pressures and ultimately lead to a reduction in heart failure events. References: Adamson PB. Pathophysiology of the transition from chronic compensated and acute decompensated heart failure: new insights from continuous monitoring devices. Curr Heart Fail Rep. 2009 Dec;6(4):287-92. Zile MR, et al. Transition from chronic compensated to acute decompensated heart failure: pathophysiological insights obtained from continuous monitoring of intracardiac pressures. Circulation. 2008 Sep 30;118(14):1433-41. Epub 2008 Sep 15.
  21. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. Another COMPASS trial sub-analysis provides evidence of the changing risk of an HFE over the spectrum of estimated PA diastolic pressures (ePAD) levels seen, as opposed to a specific threshold. The graph shows the probability of an HF event for 261 patients during a 6-month period in relation to chronic daily ePAD. As the slope of the smoothing spline function illustrates, there is a consistent and monotonic increase in the risk of HFE with higher chronic ePAD. The linear component is highly significant (p < 0.001). When adjusted for covariates, the curve has the same shape and significance. There is a trend for significance of the “S”-shaped nonlinear component (p = 0.11), which was slightly greater in the adjusted analysis (p = 0.07) but limited by the paucity of data at the tapering ends of the curve. The probability of an HFE was progressively higher with higher chronic daily ePAD Reference: Stevenson LW, et al. Chronic ambulatory intracardiac pressures and future heart failure events. Circ Heart Failure. 2010; 3: 580-587. Background—Intracardiac pressures in heart failure (HF) have been measured in patients while supine in the hospital but change at home with posture and activity. The optimal level of chronic ambulatory pressure is unknown. This analysis compared chronic intracardiac pressures to later HF events and sought a threshold above which higher pressures conferred worse outcomes. Methods and Results—Median pressures were measured every 24 hours from continuous 8-minute segments for 6 months after implantation of hemodynamic monitors in 261 patients with New York Heart Association class III-IV HF in the Chronicle Offers Management to Patients with Advanced Signs and Symptoms of Heart Failure Study. Baseline and chronic daily medians of estimated pulmonary artery diastolic, right ventricular systolic, and right ventricular end-diastolic pressures were compared with HF event rate. The group median for chronic 24-hour estimated pulmonary artery diastolic pressure was 28 mmHg (excluding 7 days before and after events). Despite weight-guided management, events occurred in 100 of 261 (38%) patients. Event risk increased progressively with higher chronic 24-hour estimated pulmonary artery diastolic pressure, from 20% at 18 mmHg to 34% at 25 mmHg and 56% at 30 mmHg, with similar relations for right ventricular pressures. Among patients with baseline day median estimated pulmonary artery diastolic pressures of 25 mmHg, event risk was 1.10/6 mo when they remained chronically 25 mmHg, but risk fell to 0.47 when 24-hour pressures declined to 25 mmHg for more than half of the days. Conclusions—Despite current management, many patients with advanced HF live on a plateau of high filling pressures from which later events occur. This risk is progressively higher with higher chronic ambulatory pressures. It is not known whether more targeted intervention could maintain lower chronic ambulatory pressures and better outcomes. (Circ Heart Fail. 2010;3:580-587.)
  22. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. The CardioMEMS HF System is made up of the PA pressure sensor itself, an external electronics measurement system and HF website. -The sensor is implanted into the distal branch of the descending pulmonary artery. -Patient is instructed to take daily pressure readings from home using the external electronics measurement system. Information transmitted from the electronics system to the HF system website is immediately available to the clinicians for review. Transmitted information consists of systolic, diastolic, and mean pressure trend information and pulmonary artery pressure waveforms. Patient takes daily measurements at home by lying on a padded antenna and pressing the remote button. Data is transmitted to a secure database and accessed by clinicians via the CardioMEMS HF website to review and adjust HF medical therapy.
  23. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. The PA pressure sensor is implanted with a right heart catheter via femoral vein approach. The target location for the sensor is the left pulmonary artery. Mean sensor implant time after completion of right heart catheterization is approximately 7 minutes (from CHAMPION clinical trial data).
  24. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. The CHAMPION clinical trial, enrolled 550 patients who all received the CardioMEMS implants. All patients took daily readings. However, the treatment group received care that was guided by their PA pressure readings. The control group received standard care. The primary endpoint of the study was rate of HF hospitalization. Secondary endpoints included change in PA pressure, number of patients admitted to the hospital for HF, days alive outside of the hospital and quality of life. Reference: Abraham WT, et al. Wireless pulmonary artery haemodynamic monitoring in chronic heart failure: a randomised controlled trial. The Lancet. 2011;377(9766):658-66.
  25. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. The PA pressure was managed by physicians to target goal pressures with appropriate titration of HF medications.
  26. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. Compared to the control group, patients managed with PA pressure information had significantly less HF-related hospitalizations (28% reduction at 6 months, 37% at 15 months).
  27. Talking points included in this deck are for internal/speaker use only, and are not to be distributed.
  28. Talking points included in this deck are for internal/speaker use only, and are not to be distributed.
  29. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. Two CHAMPION clinical trial sub analyses evaluated the effect of PA pressure-guided therapy with the CardioMEMS HF System in patients with and without a CRT device and in patients with preserved ejection fraction (≥ 40%). In the sub analysis results showed that at 6 months follow-up, patients with a CRT device had significantly fewer HF hospitalization (RRR = 29%, p = 0.0071 vs. control). HF hospitalizations were also reduced in patients without a CRT device (RRR = 28%, p = 0.0080). At HFSA in 2010, Phil Adamson et al. reported the effect of PA pressure-guided therapy on NYHA Class III patients with preserved ejection fraction (HFpEF). After 6 months of follow-up, the PA-pressure guided therapy using the CardioMEMS HF System significantly reduced HF hospitalizations in HFpEF patients in the treatment group by 50% vs. patients in the control group (p < 0.0001). The CHAMPION clinical trial is the only study, to our knowledge, that has shown improved outcomes in patients with preserved systolic function. References: Weiner S, et al. Effect of CRT on Heart Failure Related Hospitalizations in patients with reduced EF utilizing remote Pulmonary Artery Pressures in the CHAMPION clinical trial. Heart Rhythm, 2011; 8(5S):S437. Additional data on file. Adamson PB, et al. CardioMEMS Heart Sensor Allows Monitoring of Pressures to Improve Outcomes in NYHA Class III Heart Failure Patients (CHAMPION) Trial: Impact of Hemodynamic Guided Care on Patients With Preserved Ejection Fraction. Journal of Cardiac Failure. 2010 Nov; 16(11):913.
  30. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. In summary, each hypotheses of the study was statistically significant. Patients who received PA pressure-guided therapy had significantly more medication changes, these patients also had a significant reduction in PA pressure, significantly reduced HF-related hospitalizations and significantly improved quality of life. The positive clinical outcomes of PA pressure-guided therapy were sustained and improved over time. Managing pressures can minimize congestion, maintain health and reduce HF-related hospitalizations.
  31. Talking points included in this deck are for internal/speaker use only, and are not to be distributed. Physiologic markers of the development of acute decompensation include changes in filling pressures, impedance, weight, BP and symptoms. Changes in pressures occur early and cause decompensation while changes in weight, BP and symptoms occur later as a result of decompensation. Because pressure changes occur early and lead to decompensation, managing pressures to targeted goal ranges may provide a strategy for heart failure management to identify the early onset of worsening hear failure, intervene early and avoid a heart failure hospitalization. References: Steimle AE, et al. Sustained Hemodynamic Efficacy of Therapy Tailored to Reduce Filling Pressures in Survivors With Advanced Heart Failure. Circulation. 1997;96:1165-1172 . http://circ.ahajournals.org/cgi/content/full/96/4/1165#SEC1 Abraham WT, et al. Wireless pulmonary artery haemodynamic monitoring in chronic heart failure: a randomised controlled trial. Lancet. 2011 Feb 19;377(9766):658-666. Ritzema J, et al. Physician-Directed Patient Self-Management of Left Atrial Pressure in Advanced Heart Failure. Circulation 2010;121:1086-1095 Abraham WT, et al. Intrathoracic Impedance vs Daily Weight Monitoring for Predicting Worsening Heart Failure Events: Results of the Fluid Accumulation Status Trial (FAST). Congest Heart Fail 2011 March;17(2):51-5. Conraads VM, et al. Sensitivity and positive predictive value of implantable intrathoracic impedance monitoring as a predictor of heart failure hospitalizations: the SENSE-HF trial. Eur Heart J (2011) 32 (18): 2266-2273. Whellan DJ, et al. PARTNERS Study Investigators, et al. Combined heart failure device diagnostics identify patients at higher risk of subsequent heart failure hospitalizations: results from PARTNERS HF (Program to Access and Review Trending Information and Evaluate Correlation to Symptoms in Patients With Heart Failure) study. J Am Coll Cardiol. 2010 Apr 27;55(17):1803-10. van Veldhuisen DJ, et al. for DOT-HF Investigators. Intrathoracic Impedance Monitoring, Audible Patient Alerts, and Outcome in Patients With Heart Failure. Circulation. 2011 Oct 18;124(16):1719-1726. Chaudhry SI, et al. Telemonitoring in patients with heart failure. N Engl J Med. 2010 Dec 9;363(24):2301-9. Anker SD. Telemedical interventional monitoring in heart failure (TIM-HF), a randomized, controlled, intervention trial investigating the impact of telemedicine on mortality in ambulatory patients with chronic heart failure. American Heart Association 2010 Scientific Sessions; November 16, 2010; Chicago, IL. Graph adapted from: Adamson PB. Pathophysiology of the transition from chronic compensated and acute decompensated heart failure: new insights from continuous monitoring devices. Curr Heart Fail Rep. 2009 Dec;6(4):287-92.