ONLINE APPENDIX
Cardiovascular Model
The cardiovascular system was modeled as shown by the electrical analog in Fig. S1. The details
of this model are provided elsewhere (1-3) and will be discussed here in brief. Ventricular and
atrial pumping characteristics were represented by modifications of the time-varying elastance
[(E(t)] theory of chamber contraction which relates instantaneous ventricular pressure [P(t)] to
instantaneous ventricular volume [V(t)] as detailed previously (2). The systemic and pulmonary
circuits are each modeled by lumped venous and arterial capacitances (Cv and Ca, respectively), a
proximal characteristic resistance (Rc, also commonly called characteristic impedance) which
relates to the stiffness of the proximal aorta or pulmonary artery, a lumped arterial resistance
(Ra), and a resistance to return of blood from the venous capacitance to the heart (Rv, which is
similar, though not identical, to Guyton's resistance to venous return (4)). The heart valves
permit flow in only one direction through the circuit.
The total blood volume (Vtot) contained within each of the capacitive compartments is
divided functionally into two pools: the unstressed blood volume (Volunstr) and the stressed blood
volume (Volstr). Volunstr, sometimes referred to as the dead volume, is defined as the maximum
volume of blood that can be placed within a capacitive vessel without raising its pressure above 0
mmHg. The blood volume within the capacitive compartment in excess of Volunstr is Volstr, so
that Vtot=Vunstr+Vstr. The unstressed volume of the entire vascular system is equal to the sum of
Volunstr of all the capacitive compartments; similarly, the total body stressed volume equals the
sum of Volstr for all compartments (5). The pressure within the compartment is assumed to rise
linearly with Volstr in relation to the compliance (C): P=Volstr/C.
Pump flow characteristics were set to those of the Synergy System as detailed previously
and (2). This pump can generate flows up to ~4.25 L/min with its impeller spinning at 28,000
rpm (pressure head between 100 and 150 mm Hg). As shown in Fig. S1, it could be specified
during the simulation whether the VAD withdrew blood from the left atrium or from the left
ventricle. In either case, the blood was pumped to the proximal portion of the arterial system.
The normal value of each parameter of the model was set to be appropriate for a 70-75 kg man
(body surface area 1.9 m2). These values, adapted from values in the literature have been
detailed previously (2) and are shown in Table S1. Values used to simulate patients with
different types of HFpEF are summarized in the main text, Table 2. The simultaneous
differential equations describing the circuit of Fig. A1 were programmed and solved in real time
in a mobile application developed for the iPad (6).
Clinical Considerations. As detailed in the main text, it would be important moving forward to
define clinical factors that would render a HFpEF patient appropriate for implantation of a
mechanical circulatory support device. For HFrEF, the INTERMACS profile score (7) has
proven invaluable in capturing a patient’s prevailing health status and facilitating risk/benefit
assessment. No such scoring system currently exists for HFpEF. INTERMACS profiles 4-7
could be considered applicable in HFpEF (Table 4). However, INTERMACS profiles 1-3,
which for HFrEF are defined by the use of inotropic agents, temporary mechanical support
devices and overall speed of clinical decline are not directly applicable to the HFpEF population.
Substitution of the frequency of heart failure hospitalizations for inotropic support and inclusion
of end-organ dysfunction and hemodynamic assessment may result in a viable construct to
stratify HFpEF severity of illness (Table S3). This classification scheme would need to be
prospectively validated prior to use in the selection of patients for a clinical trial investigating
VAD therapy in this cohort. As for HFrEF, it may be that the HFpEF patients most suitable for
mechanical circulatory support are those in profiles 1-3 of the proposed modified classification.
Arguably, limited functional abilities are one of the most common complaints of all heart failure
patients and HFpEF patients appear to have similar degrees of exercise intolerance as the HFrEF
cohort. Cardiopulmonary exercise testing and 6 minute hall walk testing have been extensively
used to objectively determine cardiac limitations and provide objective criteria for selection of
patients for MCS.
Another important selection consideration in the HFpEF population is quality of life
(QoL). Existing data suggests that reductions in QoL are similar in HFrEF and HFpEF. Diseasespecific tools such as the Minnesota Living with Heart Failure or the Kansas City
Cardiomyopathy Questionnaires are validated and reproducible methods for assessing QoL.
Joseph and colleagues (8) recently performed a prospective study of the Kansas City
Cardiomyopathy Questionnaire (KCCQ) as a prognostic tool for patients with either HFrEF or
HFpEF. They showed that KCCQ scores accurately stratified morbidity and mortality risks and
performed equally well in both categories of heart failure. For example, HFpEF patients with the
lowest KCCQ scores (0-25) had a strikingly high 1 year composite rate of mortality and
hospitalizations of 86.8% and a mortality rate of 22.3%, which was similar to those of HFrEF.
Accordingly, KCCQ might be helpful to guide appropriate patient selection. It is important to
note that while NYHA classification also correlated with events in this registry, the KCCQ score
correlated more strongly with prognosis in HFpEF patients.
This may be because the
questionnaire encompasses symptom stability over a duration of time from the patient’s
perspective, while the NYHA class is assigned by the clinician during a given encounter. Thus,
the KCCQ may be able to identify HFpEF patients who are more chronically limited from heart
failure, rather than those who are relatively asymptomatic at rest with episodic bouts of
pulmonary edema as mentioned above.
Another approach to risk stratification may be provided by survival models such as
derived from the Meta-analysis Global Group in Chronic Heart Failure (MAGGIC) trial (9). This
study analyzed data of 39,372 heart failure patients, 17,930 of them with HFpEF, and established
a risk score predicting the expected survival of HFpEF patients. According to this study, the
main negative prognostic factors of HFpEF patients include advanced age, diabetes mellitus and
New York Heart Association classes III and IV.
The availability of a tool to measure health status and QoL in HFpEF will be important to
identify patients with the proper risk/benefit ratio to undergo surgery, to live with a chronic
indwelling device with percutaneous drivelines and to require chronic anticoagulation.
Reference List for Online Appendix
1. Santamore WP, Burkhoff D. Hemodynamic consequences of ventricular interaction as
assessed by model analysis. Am J Physiol 1991; 260 (HCP 29):H146-H157.
2. Morley D, Litwak K, Ferber P, et al. Hemodynamic effects of partial ventricular support
in chronic heart failure: Results of simulation validated with in vivo data. J Thorac
Cardiovasc Surg 2007; 133:21-8.
3. Burkhoff D, Tyberg JV. Why does pulmonary venous pressure rise following the onset of
left ventricular dysfunction: a theoretical analysis. Am J Physiol 1993; 265 (HCP
34):H1819-H1828.
4. Guyton AC, Lindsey AW, Abernathy B, Richardson T. Venous return at various right
atrial pressures and the normal venous retrun curve. Am J Physiol (Heart Circ Physiol )
1957; 189:609-15.
5. Guyton AC, Armstrong GG, Chipley PL. Pressure-volume curves of the arterial and
venous systems in live dogs. Am J Physiol (Heart Circ Physiol ) 1956; 184:253-8.
6. Burkhoff D. Harvi (version 1.0.3) [mobile application software]. 2013; Retrieved from.
https://itunes apple com/us/app/harvi/id568196279?mt=8 2013.
7. Stevenson LW, Pagani FD, Young JB, et al. INTERMACS profiles of advanced heart
failure: the current picture. J Heart Lung Transplant 2009; 28:535-41.
8. Joseph SM, Novak E, Arnold SV, et al. Comparable performance of the Kansas City
Cardiomyopathy Questionnaire in patients with heart failure with preserved and reduced
ejection fraction. Circ Heart Fail 2013; 6:1139-46.
9. Pocock SJ, Ariti CA, McMurray JJ, et al. Predicting survival in heart failure: a risk score
based on 39 372 patients from 30 studies. Eur Heart J 2013; 34:1404-13.
Online Figure 1. Electric circuit analog of the cardiovascular system used to
simulate patients with different diseases and the impact of LVAD support. See
text for further details.
MCS
Online Table 1. Values of simulation parameters appropriate for a normal adult (~70 kg) human.
Refer to Online Fig. 1 for additional context.
Parameter Group/Name
Symbol
Units
Values
General Cardiovascular Parameters
Heart Rate
HR
min-1
70
AV Delay
AVD
msec
160
Total Blood Volume
BVtot
ml
5000
BVstress
ml
950
BVunstress
ml
4050
Stressed Blood Volume
Unstressed Blood Volume
Heart
RA
RV
LA
LV
End-systolic elastance
Ees
mmHg/ml
0.45
0.61
0.45
3
Volume axis intercept
Vo
ml
10
5
10
5
Scaling factor for EDPVR
A
mmHg
0.44
0.35
0.44
1.3
Exponent for EDPVR
B
ml-1
0.049
0.04
0.049
0.027
Time to end-systole
Tmax
msec
125
200
125
200
Time constant of relaxation
Tau
msec
25
30
25
30
AV Valve Resistance
Rav
mmHg.s/ml
Circulation
0.0025
0.0025
Pulmonary
Systemic
Characteristic Impedance
Rc
mmHg.s/ml
0.03
0.04
Arterial Resistance
Ra
mmHg.s/ml
0.03
1.1
Venous Resistance
Rv
mmHg.s/ml
0.025
0.025
Arterial Compliance
Ca
ml/mmHg
13
1.5
Venous Compliance
Cv
ml/mmHg
8
70
Online Table 2. Model parameters varied from “normal” to
simulate different types of HFpEF.
Simulation Parameter
Stressed Blood Volume (ml)
Heart Rate (bpm)
LV Ees (mmHg/ml)
LV alpha (1/ml)
RV Ees (mmHg/ml)
RV alpha (1/ml)
LA Ees (mmHg/ml)
LA alpha (1/ml)
RA Ees (mmHg/ml)
RA alpha (1/ml)
Type 1
HCM
1800
75
3.44
0.058
2.13
0.068
0.36
0.043
0.32
0.039
Type of HFpEF
Type 2
Type 3
Amyloid nonLVH
1768
2030
90
70
2.5
2.43
0.052
0.044
4.99
2.47
0.075
0.055
0.31
0.39
0.038
0.047
0.28
0.48
0.034
0.058
Type 4
HTN
2345
72
2.01
0.03
2.34
0.039
0.26
0.032
0.32
0.038
Online Table 3. Proposed modifications to INTERMACS profiles for HFpEF.
Profile
1
2
3
4
5
6
HFpEF
Cardiogenic Shock. Hospitalization with invasive hemodynamic
measurements demonstrating low cardiac output and elevated cardiac
filling pressures associated with a normal ejection fraction. Requires
evidence of end-organ dysfunction.
Recurrent Advanced HFpEF. Requires current hospitalization with at
least 2 prior hospitalizations in the past 6 months for HFpEF. Patient
should have manifest volume overload with abnormal end-organ
function.
Signs and Symptoms at rest including nocturnal dyspnea, persistent
edema, elevated neck veins, and inability to diurese without azotemia
(e.g., BUN<50% greater than upper limit of normal). Frequent clinic
visits without hospitalizations in the past 12 months.
Exertion intolerant
Exertion limited
Class III Symptoms