Download Heart Failure Diagnostics – Dr. Waqas Ghummann

Heart Failure Diagnostics
Waqas Ghumman MD FACC
Community Health Network Heart Failure Director
HEART FAILURE – A GROWING GLOBAL CONCERN
Prevalence and Incidence
Mortality
 Overall 2.1% prevalence: 5.1M heart failure
patients in 2010 1
 For AHA/ACC stage C/D patients
diagnosed with HF:
 825,000 people ≥ 45 years of age are newly
diagnosed each year with HF1
 15M heart failure patients in the ESC
51-member countries 2
 30% will die in the first year.3-5
 60% will die within 5 years.5
 Overall 2-3% prevalence2
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
1.
2.
3.
4.
5.
6.
AHA 2014 Statistics at a Glance, 2014
The European Society of Cardiology, ESC HF Guideline, 2008
Curtis et al, Arch Intern Med, 2008.
Roger et al. JAMA, 2004.
Cowie et al, EHJ, 2002.
Heidenreich PA et al. Circ Heart Failure 2013.
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 diagnosis 1

Hospitalization rate did not change significantly
from 2000 1
 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 months 4,5
Graph from www.health.org.uk. Bridging the gap: Heart Failure, 2010.
Data from Organization for Economic Cooperation and Development, 2009.
1.
2.
3.
4.
5.
CDC NCHS National Hospital Discharge Survey, 2000-2010
Yancy et al. JACC, 2006.
Cleland et al. EuroHeart, 2003.
Krumholz HM, et al. Circ Cardiovas Qual Outcomes 2009.
Wexler DJ, et al. Am Heart J 2001.
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
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.
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.
22.7%
national average 30-day
readmissions rate1,2
Percent withholding of all inpatient Medicare payments will increase to up to 3% by 2015
and beyond.3
Fiscal Year
2013
2014
2015+
% payment withholding
up to 1%
up to 2%
up to 3%
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.
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
HF HOSPITALIZATIONS ARE A STRONG PREDICTOR
OF MORTALITY1,2
Data from the EFFECT study, n = 9138 patients 1
Data from Setoguchi et al., n = 14,374 patients 2
Among 1 year survivors after index EFFECT-HF discharge,
the number of heart failure hospitalizations in the preceding
year stratified the risk of death in crude analysis. 1
KP cumulative mortality curve for all-cause mortality
after each subsequent hospitalization for HF. 2
Studies show each admission decreases a patient’s chance of survival.
1. Lee DS, et al. Am J of Med, 2009.
2. Setoguchi S, et al. Am Heart J, 2007.
CURRENT HF MANAGEMENT IS INADEQUATE FOR
IDENTIFYING AND MANAGING CONGESTION LEADING
TO DECOMPENSATION
Identifying congestion early will lead to early treatment,
prevent hospitalizations and slow the progression of HF.
 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
Congestion state of patients discharged
without congestion at 60-day follow-up3
Congestion state at discharge
Maintained decongestion
17%
Absent or mild congestion
Moderate to severe congestion
1. Adams KF, et al. Am Heart J. 2005
2. Krum H and Abraham WT. Lancet 2009
3. Lala A, et al. JCF 2013
40%
60%
24%
59%
Partial recongestion
Relapse to severe congestion
INCREASES IN FILLING PRESSURE START THE CYCLE OF
WORSENING HEART FAILURE SYNDROMES
 Pulmonary Artery Pressure
Left Heart Failure
Left Atrial Pressure


Right Heart Failure
Cardiac Output

Right Atrial Pressure
Dyspnea
Fatigue
Heptic Insufficiency
Orthopnea
Confusion
Renal Insufficiency
Pulmonary Edema
Renal Insufficiency
Peripheral Edema
Peripheral Edema
Adapted from Jaski BE, “Basics of Heart Failure A Problem Solving Approach”
TIME COURSE OF DECOMPENSATION
Physiologic Markers of Acute Decompensation
Graph adapted from Adamson PB, et al. Curr Heart Fail Reports, 2009.
PHYSIOLOGIC MARKERS OF ACUTE DECOMPENSATION
Graph adapted from Adamson PB, et al. Curr Heart Fail Reports, 2009.
CLINICAL EXAMINATION HAS LIMITED RELIABILITY IN
ASSESSING FILLING PRESSURES
Data from clinical evaluations has poor sensitivity and predictive value in determining
hemodynamic profile
Capomolla, 2005. N = 366
Variable
JVP
Edema
Pulse Press
S3
Dyspnea
Rales
Estimate
of
Sensitivity (%)
Specificity (%)
PPV
(%)
NPV
(%)
RAP
48
10
78
94
60
55
69
60
Cardiac Index
27
69
52
44
PCWP
36
50
13
81
73
90
69
67
60
54
57
48
Table adapted from Capomolla S, et al. Eur J Heart Failure, 2005.
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
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
End Point
Koehler F et al, Circulation 2011
IS THERE VALUE IN FREQUENT MONITORING OF WEIGHT,
SYMPTOM AND BP TO MONITOR DECOMPENSATION?
Frequent monitoring of weight, symptoms, BP has mixed results in reducing mortality and hospitalization.
Author
n
Mean age
Type of interventions
Goldberg 2002 (WHARF)1
280/280
59
Wt. and symptoms
Bondmass 20011
164/164
61
Wt., BP, HR and oxygen saturation
Gattis 1999
(PHARM study)2
181
67
symptoms
Significant reduction in mortality
Rainville 19992
34
70
symptoms
Significant reduction in hospitalization
Massie 20011
147/147
69
Wt., vital signs and symptoms
Cleland 2005
(TEN-HMS)2
426
67
Wt, BP, symptoms, ECG
Barth 20012
34
75
symptoms
No difference in hospitalization
Riegel 20022
358
74
symptoms
No difference in hospitalization
Laramee 20032
287
71
symptoms
No difference in hospitalization
De Busk 20042
462
72
symptoms
No difference in hospitalization
Tsuyuke 20042
276
72
symptoms
No difference in hospitalization
Riegel 20062
134
72
symptoms
No difference in hospitalization
1. Louis AA, et al. EJHF, 2003.
2. Clark RA, et al. BMJ, 2007.
Outcome
Significant reduction in mortality with no
difference in readmission rates
Fewer HF readmissions with reduced length
of stay compared to nurse visit group
No significant difference in outcome
No difference in hospitalization, significant
difference in mortality
DOT-HF TRIAL: MONITORING IMPEDANCE WITH AUDIBLE
ALERT INCREASED HF HOSPITALIZATIONS
Monitoring intrathoracic impedance (OptiVol™ algorithm, Medtronic) with an audible alert did not
improve mortality and increased HF hospitalizations
van Veldhuisen DJ, et al. Circulation, 2011.
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
1. Whellan DJ, et al. JACC, 2010.
2. Cowie MR, et al. EHJ 2013.
COMBINED DIAGNOSTIC ALGORITHM
• Based on 8 Diagnostic trends
which are recorded daily
• Individual algorithms for each
trend have been used to flag
significant observations from
the trends in Medtronic
ICDs/CRTs
OptiVol
VT/VF
therapy
AF burden
Rate during
AF
%CRT
HR
Activity
HRV
COMBINED ALGORITHM
Positive Combined Algorithm = any 2 criteria +
Parameter
Criterion
Fluid Index
AT/AF Duration
V. rate during AT/AF
Patient Activity
Night Heart Rate
HRV
CRT % Pacing
Shock(s)
≥60 ohm/days
≥6 hours & not persistent AT/AF
AT/AF ≥24 hrs & V. ≥ 90 bpm
Avg. <1 hr over 1 week
≥85 bpm for 7 consecutive days
<60 ms for 7 consecutive days
< 90% for 5 of 7 days
1 or more shocks
OR Fluid Index ≥100
COMBINED DIAGNOSTICS TRIGGERED
1324 monthly evaluations with combined algorithm triggered
≥ 2 Diagnostic Criteria Met
43%
% of
evaluations
when ≥2
Diagnostic
Criteria Met
(N = 960)
75%
OptiVol Fluid Index ≥100 ohm days Met
29%
67%
28%
% of triggered evaluations
62%
60%
43%
45%
30%
21%
18%
14%
15%
7%
5%
0%
AF
AF+RVR OptiVol
Low
Night
Index ≥60 Activity HR
Low
HRV
Low ICD Shock(s)
Pacing%
Evaluations with Heart Failure
Hospitalization (Pulmonary)
KAPLAN-MEIER HF HOSPITALIZATION CURVES
P < 0.0001
Hazard Ratio = 5.5 (95% CI: 3.4 – 8.8)
6%
5%
+ Diagnostic
4%
3%
2%
- Diagnostic
1%
0
0
10
20
30
Days After Diagnostic Evaluation
Risk of a HF hosp. for pts with
+ Diagnostic was 5.5 x risk of pts w/ - Diagnostic
CASE
STUDY 1
HF Hospitalization with Pulmonary Congestion
30 Day Evaluation window
AF+
Fluid +
MECHANISMS OF WORSENING HEART FAILURE
Increased pressure is the proximate cause of congestion
Precipitating cause
Sympathetic activation
Renal and dietary
Venous redistribution
(fast)
Fluid retention
(slow)
Increased L Heart Filling
LAP/PAP
Pulmonary capillary
transudation
Decompensation /
hospitalization
Pressures rise early and
have few confounders
CARDIOMEMS™ HF SYSTEM
Pulmonary Artery
Pressure Sensor
Patient
Electronics
System
CardioMEMS™
HF System
Website
CARDIOMEMS™ HF SYSTEM
The pulmonary artery pressure sensor
is implanted via a right heart catheterization
procedure via femoral vein approach .
Target location for pulmonary artery
pressure sensor
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.
550 Pts with CardioMEMS™ HF System Implants
All Pts Take Daily readings
Treatment
270 Pts
Management Based on
PA Pressure +Traditional Info
26 (9.6%) Exited
< 6 Months
15 (5.6%) Death
11 (4.0%) Other
Control
280 Pts
Management Based on
Traditional Info
Primary Endpoint: Rate of HF Hospitalization
Secondary Endpoints:
 Change in PA Pressure at 6 months
 No. of patients admitted to hospital for HF
 Days alive outside of hospital
 QOL
Abraham WT, et al. Lancet, 2011.
26 (9.6%) Exited
< 6 Months
20 (7.1%) Death
6 (2.2%) Other
CHAMPION CLINICAL TRIAL: MANAGING TO
TARGET PA PRESSURES
550 Pts with CardioMEMS™ HF System Implants
All Pts Take Daily readings
Treatment
270 Pts
Management Based on
PA Pressure +Traditional Info
26 (9.6%) Exited
< 6 Months
15 (5.6%) Death
11 (4.0%) Other
Control
280 Pts
Management Based on
Traditional Info
PA pressures were managed to target goal
Primary
rate of with
HF Hospitalization
pressures
byEndpoint:
physicians
appropriate
titration of HF medications.
Target Goal PA Pressures:
Secondary Endpoints included:
 PA Pressure
15 –at35
mmHg
 Change Systolic
in PA Pressure
6 months
 No. of patients admitted to hospital for HF
 PA Pressure
diastolic 8 – 20 mmHg
 Days alive outside of hospital
 QOL mean 10 – 25 mmHg
 PA Pressure
Abraham WT, et al. Lancet, 2011.
26 (9.6%) Exited
< 6 Months
20 (7.1%) Death
6 (2.2%) Other
PULMONARY ARTERY PRESSURE DATABASE
Trend Data
Reading
Discrete data
seconds
Systolic:
24
Mean:
19
Diastolic:
16
Heart Rate:
81
CHAMPION CLINICAL TRIAL: PA PRESSURE-GUIDED
THERAPY REDUCES HF HOSPITALIZATIONS
Patients managed with PA pressure data had significantly fewer
HF hospitalizations as compared to the control group.
Abraham WT, et al. Lancet, 2011.
CHAMPION CLINICAL TRIAL: BOTH PRIMARY SAFETY ENDPOINTS
AND ALL SECONDARY ENDPOINTS WERE MET AT 6 MONTHS
Primary Safety
Endpoints
Device-related or system-related complications
Pressure-sensor failures
Control
(n = 280)
3 (1%)
3 (1%)
Total 8 (1%)*
P-value
< 0.0001
0
0
< 0.0001
-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
Change from baseline in PA mean pressure
(mean AUC [mm Hg x days])
Secondary
Endpoints
Treatment
(n = 270)
* Total of 8 DSRCs including 2 events in Consented not implanted patients (n = 25)
Abraham WT, et al. Lancet, 2011.
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
Beta-blocker
COPERNICUS
10 months
33%
7
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
EMPHASIS-HF
21 months
38%
16
DIG
37 months
24%
17
Angiotensin
receptor blocker
Val-HeFT
23 months
23%
18
Angiotensin
receptor blocker
CHARM
40 months
27%
19
CHAMPION
17 months
33%
4
Aldosterone antagonist
Aldosterone antagonist
Digoxin
PA pressure monitoring
Annualized Reduction
in HF Hospitalization
Rates
NNT per year to
Prevent 1 HF
Hospitalization
CHAMPION CLINICAL TRIAL: PA PRESSURE-GUIDED THERAPY
IMPROVES OUTCOMES IN PATIENTS WITH PRESERVED EJECTION
FRACTION


HF Hospitalization Reduction
(18 mo follow-up)
Preserved Ejection Fraction Heart Failure (HFpEF)
or diastolic HF patients represent ~50% of all HF
patients
Pulmonary artery pressure-guided therapy
significantly reduced HF hospitalizations in HFpEF
patients in the treatment group by 46% at 6 months
(p<0.0001) and by 50% at 18 months (p<0.0001)
The effect in HFpEF patients is even more dramatic
than HFrEF or systolic patients with an estimated
NNT = 2
60%
Relative Risk Reduction

p<0.0001 vs. control
50%
40%
30%
P<0.0001 vs. control
20%
10%
0%
HFrEF
reduced EF (< 40%)
Adamson PB,, et al.. Circ Heart Fail. 2014.
HFpEF
preserved EF (≥ 40%)
SUMMARY: MANAGING PRESSURES TO MAINTAIN
HEALTH AND MANAGE ACUTE EVENTS
Unreliable, late, and
indirect markers8,9
May be used in
risk stratification,
but not actionable4-7
Enables proactive and
personalized HF
management 1-3
* 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
CARDIOMEMS AT
COMMUNITY HEALTH NETWORK

http://www.theindychannel.com/lifestyle/health/new-implant-helping-heart-failure-patients