Prognostic Value of Preoperative Pulmonary Arterial Capacitance for Patients Undergoing Aortic Valve Replacement for Severe Aortic Valve Stenosis

Abstract

Background: Pulmonary arterial capacitance (PAC) is a determinant of right ventricular afterload and a strong independent predictor of unfavorable outcomes in advanced heart failure (HF) with pulmonary hypertension (PH). We aimed to test the hypothesis that preoperative PAC may affect postoperative clinical outcomes in patients undergoing aortic valve replacement (AVR) for severe aortic valve stenosis (AS), even in the absence of PH.

Methods and Results: We studied 116 patients who underwent AVR for severe AS between January 2005 and December 2017. Right heart catheterization was performed for all patients prior to surgery. PAC and pulmonary vascular resistance (PVR) fit well to a hyperbolic relationship (PAC=0.23/PVR, R²=0.73). PAC also showed an inverse relationship with pulmonary capillary wedge pressure (PCWP) (r=−0.15) and mean pulmonary arterial pressure (r=−0.29) and provided a stronger prediction of death or HF admission than PCWP or PVR (area under the ROC curve of 0.74 vs. 0.40 and 0.41, respectively, P=0.002). During a median follow-up of 36 months, PAC (hazard ratio, 0.48; 95% confidence interval, 0.30–0.78; P=0.003) was an independent predictor of death or hospitalization for HF.

Conclusions: In these patients undergoing AVR for severe AS, even in the absence of PH, preoperative reduced PAC was independently associated with adverse surgical outcomes. It seems that preoperative PAC has potential as an independent predictor of long-term prognosis after AVR for severe AS.

Right heart dysfunction and failure secondary to left-sided heart failure (HF), as well as from pulmonary arterial hypertension (PAH), have been shown to contribute significantly to poor prognosis.^1–6

An increasing number of elderly patients with severe aortic valve stenosis (AS) have been undergoing aortic valve replacement (AVR) in developed countries, and these patients may suffer preoperatively from pulmonary hypertension (PH) caused by persistent backward transmission of elevated left-sided filling pressure into the pulmonary circulation, possibly resulting in an unfavorable long-term survival outcome entailing right ventricular (RV) failure. Several reports have indicated that PH has a significant effect on the long-term outcomes of patients undergoing AVR for AS.^7,8 However, only pulmonary vascular resistance (PVR) has typically been described as a measure of RV afterload related to PH.

Considering RV function, RV afterload plays a pivotal role in various clinical conditions because the RV is much more afterload-sensitive than the left ventricle (LV). The afterload of the RV is usually described as PVR in clinical practice, but this concept does not correctly reflect the opposition to the pulsatile component of pulmonary flow.⁹ According to the 3-element Windkessel model, the hydraulic load of the pulmonary arterial system can be described by incorporating the resistance of the small arteries and arterioles, the elastic properties (compliance or capacitance) of the whole arterial system, and the characteristic impedance of the proximal pulmonary artery related to the blood mass and compliance of the pulmonary artery.^10,11

Recently, the clinical significance of pulmonary arterial capacitance (PAC) over PVR in terms of RV afterload has been shown in patients with PAH or advanced HF.^12–15 However, little is known regarding the clinical significance of preoperative PAC in candidates for cardiac surgery who usually have less advanced HF without PH than the subjects of previous studies of PAC in the literature. We hypothesized that preoperative PAC in patients with AVR for severe AS, even in the absence of PH, may affect postoperative clinical outcomes. The aim of the present study was to examine the relationship between the preoperative PAC of patients undergoing AVR for severe AS and postoperative outcomes.

Methods

Patient Population

We retrospectively reviewed the clinical information of 213 consecutive patients aged 18 years or older who underwent preoperative right heart catheterization (RHC) and primary AVR with or without coronary artery bypass grafting for severe AS (aortic valve area <1 cm²) between January 2005 and December 2017 at Nara Medical University Hospital. Of these patients, 97 were excluded from the present study because of incomplete set of hemodynamic data in 42 cases, concomitant mitral or tricuspid valve procedure in 32 cases, and endstage renal disease on hemodialysis in 23 cases. A total of 116 patients were studied. The primary indication for RHC was part of the assessment for AVR candidacy. The Ethics Committee of Nara Medical University approved this study.

Hemodynamic Assessment

RHC was performed in the catheterization laboratory while the patient was resting supine. Pressure measurements were obtained at end-expiration in the steady state using a 7F balloon-tipped catheter. The right atrial pressure (RAP), the systolic and diastolic pulmonary arterial pressures (PAPs) with the mean pulmonary arterial pressure (mPAP), and the pulmonary capillary wedge pressure (PCWP), were obtained. Cardiac output (CO) was measured by the thermodilution method. PVR was calculated as: (mPAP−PCWP)/CO. PAC was estimated as the ratio between the stroke volume (SV) and the pulmonary pulse pressure (PP): SV/PP.

In addition to the hemodynamic variables, data pertaining to demographic characteristics, medical history, medical treatment, laboratory findings, and preoperative and postoperative echocardiography were collected. The LV ejection fraction (LVEF) was calculated with the modified Simpson’s method. The early diastolic ratio of the transmitral inflow velocity to the mitral annular velocity (E/e’) was measured to assess the LV filling pressure. An indexed effective orifice area <0.85 cm²/m² is generally regarded as the threshold for prosthesis-patient mismatch (PPM) in the aortic positon, with values between 0.65–0.85 cm²/m² being classified as moderate PPM and those <0.65 cm²/m² as severe PPM.¹⁶

Study Endpoint

The primary outcome measure was a combined endpoint of all-cause death or admission for HF. These data were confirmed through patient medical records by clinicians who were blinded to the PAC levels. When information was unavailable in the medical records, the same clinicians telephoned the patients or their families to collect the data.

Statistical Analysis

Continuous variables are expressed as the mean and standard deviation or as median and interquartile range; categorical variables are presented as numbers and percentages. Comparisons were made by Student’s t-test or the Wilcoxon rank-sum test for continuous variables, and with the chi-squared test for categorical variables. A non-linear least-square estimation procedure was used to explore the relationship between PAC and PVR. A simple equation, PAC=b0/PVR, demonstrated a good fit with the data. Natural log transformation was used to satisfy some model assumptions. Linear regression analysis with a Spearman rank-order correlation coefficient was used to assess the correlations between PAC and the pressure measures, including RAP, mPAP, and PCWP. Receiver-operating characteristic (ROC) curves were constructed to examine the association between various RV afterload measures and death or HF admission. Survival curves were estimated with the Kaplan-Meier method and compared using the log-rank test. Cox proportional hazard regression models were used to determine which variables were significant predictors of all-cause death or HF admission during a median follow-up of 36 months. Variables perceived as clinically important and those evaluated with P<0.1 in the univariate analysis were included in the Cox multivariate model. The following parameters were considered as covariates in the final model: age, B-type natriuretic peptide (BNP), PAC, PVR, and systolic PAP. Differences were considered statistically significant when the two-sided P-values were <0.05. Statistical analyses were performed using SPSS for Windows, version 21.0 (SPSS Inc., Chicago, IL, USA).

Results

Baseline Characteristics

A total of 116 patients underwent preoperative RHC and AVR for severe AS between January 2005 and December 2017. The median PAC was 3.9 (3.0–4.5) mL/mmHg. Table 1 shows the preoperative characteristics of our study cohort stratified according to PAC levels that were above and below the median value. Patients with reduced PAC levels had higher EuroSCORE II values (European System for Cardiac Operative Risk Evaluation II), more impaired hemodynamics in terms of mPAP, systolic PAP, PP, PCWP, SV, cardiac index, and PVR and more compromised cardiac performance with regard to LVEF and E/e’ on echocardiography. They also had higher BNP values, lower estimated glomerular filtration rates and lower hemoglobin.

Table 1. Patient Characteristics Stratified According to PAC Levels Above and Below the Median PAC Value

Characteristics	Total population (n=116)	PAC ≥3.9 mL/mmHg (n=58)	PAC <3.9 mL/mmHg (n=58)	P value
Preoperative baseline clinical data
Age (years)	74±7	73±8	75±7	0.22
Female sex (%)	67 (58)	30 (52)	37 (64)	0.26
BSA (m2)	1.5±0.2	1.6±0.2	1.5±0.2	0.002
NYHA ≥3 (%)	32 (28)	12 (21)	20 (35)	0.15
EuroSCORE II (%)	2.22 (1.43–3.18)	1.52 (1.19–2.82)	2.68 (1.85–4.28)	0.006
Comorbidities
Hypertension	97 (84)	49 (84)	48 (83)	1.0
Diabetes	42 (36)	23 (40)	19 (33)	0.56
Dyslipidemia	55 (47)	28 (48)	27 (47)	1.0
Coronary artery disease	29 (25)	16 (28)	13 (22)	0.67
Atrial fibrillation	20 (17)	7 (12)	13 (22)	0.22
Medications
β-blocker	29 (25)	13 (22)	16 (28)	0.67
Diuretic	34 (29)	12 (21)	22 (38)	0.07
ACEI/ARB	70 (60)	32 (55)	38 (66)	0.34
Statin	53 (46)	27 (47)	26 (45)	1.0
Preoperative echocardiographic data
LVEF (%)	65±11	68±10	63±13	0.02
E/e’	18.5±7.4	16.8±5.6	20.3±8.6	0.02
Preoperative laboratory data
Hb (g/dL)	12.2±1.7	12.6±1.7	11.8±1.6	0.006
BNP (pg/mL)	141 (57–285)	85 (39–161)	228 (91–371)	0.0003
eGFR (mL/min/1.73 m2)	59±17	63±16	55±17	0.03
Preoperative hemodynamic data
RAP (mmHg)	4.4±2.6	4.5±2.5	4.3±2.6	0.75
Mean PAP (mmHg)	19.3±6.5	16.7±4.3	21.9±7.3	0.007
Systolic PAP (mmHg)	32.4±8.9	28.1±5.7	36.8±9.3	<0.0001
Diastolic PAP (mmHg)	12.4±5.0	11.1±4.1	13.8±5.5	0.23
PP (mmHg)	20.0±5.6	17.0±3.8	23.0±5.6	<0.0001
PCWP (mmHg)	11.6±6.1	10.0±4.5	13.2±7.0	0.004
SV (mL)	73.7±16.7	81.9±13.6	65.5±15.4	<0.0001
Cardiac index (L/min/m2)	3.3±0.6	3.5±0.6	3.2±0.6	0.04
PVR (WU)	1.6±0.7	1.3±0.5	1.9±0.7	<0.0001
Prosthetic valve used
Mechanical	20 (17)	11 (19)	9 (16)	0.9
St. Jude Medical Regent	6 (5)	2 (3)	4 (7)
MCRI On-x	9 (8)	6 (10)	3 (5)
Open Pivot AP360	4 (3)	2 (3)	2 (3)
Open Pivot AP	1 (1)	1 (2)	0 (0)
Bioprosthesis	96 (83)	47 (81)	49 (84)	0.4
CEP	11(9)	5 (9)	6 (10)
CEP Magna	11(9)	5 (9)	6 (10)
CEP Magna EASE	63 (54)	30 (52)	33 (57)
Medtronic Mosaic Ultra	4 (3)	2 (3)	2 (3)
Epic valve	4 (3)	2 (3)	2 (3)
Trifecta GT	3 (3)	3 (5)	0 (0)
Implanted valve size (mm)	21±1.5	21±1	20±2	0.005
Postoperative echocardiographic data
LVEF (%)	66±10	66±10	66±9	0.86
TRPG (mmHg)	24±6	23±5	25±7	0.18

ACEI, angiotensin-converting enzyme inhibitor; ARB, angiotensin-II receptor blocker; BNP, B-type natriuretic peptide; BSA, body surface area; CEP, Carpentier-Edwards Perimount; E/e’, early diastolic ratio of transmitral inflow velocity to mitral annular velocity; eGFR, estimated glomerular filtration rate; EuroScore II, European System for Cardiac Operative Risk Evaluation II; Hb, hemoglobin; LVEF, left ventricular ejection fraction; NYHA, New York Heart Association functional class; PAC, pulmonary arterial capacitance; PAP, pulmonary arterial pressure; PCWP, pulmonary capillary wedge pressure; PP, pulmonary pulse pressure; PVR, pulmonary vascular resistance; RAP, right atrial pressure; SV, stroke volume; TRPG, tricuspid regurgitation peak gradient; WU, Woods unit.

Correlations Between PAC and PVR, PCWP, and Other Variables

Figure 1A is a plot of PAC as a function of PVR and demonstrates a hyperbolic relationship with the predominant dispersion along the steep part of the PAC-PVR curve, where only a small change in PVR would have a relatively large effect on PAC. The patients with adverse outcomes are distributed along the curve between the steep and flat portions, where PAC is relatively lowered. The mean pulmonary arterial time constant (the product of resistance and capacitance, PVR×PAC) is 0.23 s. When dichotomized at a PCWP < or ≥15 mmHg, there is a shift in the hyperbolic curve downward and to the left for the patients with PCWP ≥15 mmHg, and the mean pulmonary arterial time constant decreases from 0.26 to 0.16 s. Therefore, PAC is lower for similar PVR values in patients with PCWP ≥15 mmHg than in those with PCWP <15 mmHg (Figure 1B). PAC correlates inversely with PCWP (r=−0.15, P=0.035) and mPAP (r=−0.29, P<0.001), but does not correlate with RAP after natural log transformation (Figure 2A–C).

Figure 1.

Scatterplots and curve fit of pulmonary vascular resistance (PVR) vs. pulmonary arterial capacitance (PAC) show a hyperbolic relationship. (A) Total population: the mean pulmonary arterial time constant (PVR×PAC) that best fits the scatterplot is 0.23 s. Red circles indicate individuals with adverse outcomes. (B) Patients are divided according to pulmonary capillary wedge pressure (PCWP) < or ≥15 mmHg. The mean pulmonary arterial time constants are 0.26 and 0.16 s, respectively.

Figure 2.

Correlation of pulmonary arterial capacitance (PAC) with (A) pulmonary capillary wedge pressure (PCWP), (B) mean pulmonary arterial pressure (mPAP), and (C) right atrial pressure (RAP) after natural log transformation (ln).

Predictive Capacity of PAC for Adverse Events

There were 4 patients with severe PPM and 4 patients with moderate PPM. No significant relationships existed between PPM and death or hospitalization for HF. The association of PAC with death or hospitalization for HF (area under the ROC curve=0.74) was superior to that of PCWP or PVR (areas under the ROC curve=0.40 and 0.41, respectively, P=0.002) with death or HF hospitalization (Figure 3). During a median follow-up time of 36 (20–61) months, there were 10 deaths and 14 HF admissions. The causes of death were HF in 5 patients, cancer in 4 patients, and gastrointestinal bleeding in 1 patient. Survival and HF admission-free survival were shown according to the quartiles of PAC (Figure 4A,B). Decreasing quartiles of PAC were associated with a graded decrease in both survival and HF admission-free survival. Multivariate Cox proportional hazard models were constructed to determine independent predictors of death or HF hospitalization. In the univariate Cox proportional hazard model, age, BNP, PAC, PVR, and systolic PAP were considered as covariates in the final model. In the multivariate analysis, PAC remained an independent predictor of adverse clinical events (Table 2).

Figure 3.

Receiver-operating characteristic curve analysis for pulmonary arterial capacitance (PAC), pulmonary capillary wedge pressure (PCWP), and pulmonary vascular resistance (PVR) for the prediction of death or heart failure admission. AUC, area under the curve.

Figure 4.

Clinical outcomes according to quartiles of pulmonary arterial capacitance. (A) Survival. (B) Heart failure admission-free survival.

Table 2. Univariate and Multivariate Cox Proportional Hazard Models for Death or Heart Failure Admission

Characteristics	Univariate		Multivariate
	HR (95% CI)	P value	HR (95% CI)	P value
Age	1.08 (1.00–1.16)	0.06	1.04 (0.96–1.13)	0.34
BNP	1.0 (Ref.)	–	1.0 (Ref.)	–
PAC	0.52 (0.33–0.82)	0.01	0.48 (0.30–0.78)	0.003
PVR	1.52 (0.94–2.48)	0.09	–	–
Systolic PAP	1.04 (0.99–1.09)	0.1	–	–

CI, confidence interval; HR, hazard ratio. Other abbreviations as in Table 1.

Discussion

The important finding of the current study was the association of reduced PAC with adverse long-term outcomes, even in these study subjects undergoing AVR for severe AS, most of whom had PCWP <15 mmHg without PH or elevated PVR. Previous studies in the literature have examined PAC to evaluate the effect of treatment and prognosis in patients exclusively with PAH, chronic thromboembolic PH, or PH from advanced HF.^{12–15,17,18} However, little is known about the clinical significance of PAC in less advanced HF patients in the absence of PH, which is the majority of candidates for cardiac surgery. From this point of view, the present study demonstrated for the first time the prognostic value of preoperative PAC in candidates for AVR for severe AS.

There is definitive evidence of a hyperbolic relationship between PAC and PVR under the influence of PCWP in patients with PH.^14,15,19,20 In the present study patients, PAC also displayed a hyperbolic relationship with PVR, with the predominant distribution of the patients appearing along the steep portion of the PAC-PVR curve, where a slight change in PVR would have a strong effect on PAC. In addition, PAC had a linear inverse relationship with PCWP. There was a shift in the hyperbolic curve downward and to the left for patients with PCWP ≥15 mmHg compared with those with PCWP <15 mmHg, suggesting that PAC was lower for similar PVR in patients with elevated PCWP. Therefore, a decrease in PCWP through a successful therapeutic intervention early in the disease process may be accompanied by a substantial increase in PAC not only because of a steep PAC-PVR relationship with a decrease in PVR but also because of the upward shift in the curve. AVR is definitely the treatment of choice for severe AS and should bring about substantial augmentation in PAC with a reduction in PCWP, which may explain why preserved preoperative PAC is associated with better outcomes. In contrast to PAH and chronic thromboembolic PH, where the original pathology resides in the pulmonary arterial system, a chronically elevated left-sided filling pressure or PCWP is primarily caused by left heart disease. Even in early-stage left heart disease or in passive PH, the pulsatile component of RV afterload may already be elevated secondary to increased PCWP. Subjects with this condition are distributed almost predominantly on the steep part of the PAC-PVR curve, where a small increase in PVR is accompanied by a substantial reduction in PAC. When the elevated left-sided filling pressure is not improved by the treatment strategies, the pathology may continue to spread over the precapillary part of the pulmonary vascular bed and result in pulmonary arterial remodeling, with consequent reactive PH with increased PVR, suggesting that the resistive component of RV afterload on top of the pulsatile component is increased.¹⁵ Patients with reactive PH are almost all distributed on the flat portion of the PAC-PVR curve, where despite great improvements in PVR, PAC will be only slightly improved. This may explain the worse early and late outcomes after AVR in patients with severe AS and PH.^7,8 As mentioned earlier, a considerable proportion of the patients in this study were distributed almost predominantly to the steep part of the PAC-PVR curve. Thus, their preoperative PAC was relatively preserved, resulting in little elevation in the pulsatile or resistive load on the RV.

The finding that right heart dysfunction and failure secondary to left-sided HF contribute prominently to poor prognosis has been increasingly recognized.^1–6 There are several potential mechanisms that may contribute to a deteriorating RV that may ultimately become impaired in association with LV failure. First, the RV can suffer from the same cardiomyopathic process as the LV. Second, decreased coronary perfusion, LV dilatation in a limited pericardial compartment (ventricular interdependence), and septal dysfunction can all alter RV systolic and diastolic properties. Finally, LV failure can directly increase RV afterload through a passive and reactive component, thus placing the afterload-sensitive RV at increased risk of failure, even in the absence of intrinsic damage.^21,22 Ghio et al reported that RV dysfunction was strongly associated with the presence of an elevated RV afterload in HF with a preserved EF (HFpEF) as opposed to HF with a reduced EF.²³ Thus, RV afterload is likely to play an important role in RV dysfunction secondary to severe AS because systolic function in the present AS patients with LV hypertrophy (LVH) was preserved in a similar manner to that of HFpEF patients. Although PVR, a measure of the resistive load on the RV, is usually used alone to describe the total RV afterload, PAC, a measure of the pulsatile load on the RV, must also be considered essential to the total RV afterload because of the pulsatile flow of the pulmonary circulation. It has been shown that, together, the common pulmonary artery and proximal left and right arteries contribute only 15–20% to total arterial compliance, suggesting that arterial compliance is distributed over the entire pulmonary arterial bed, although in the systemic arterial tree, compliance is mainly located in the aorta.¹¹ Thus, in the pulmonary circulation, the small arteries and arterioles dominate both pulmonary resistance and compliance. In the multivariable Cox proportional hazard model constructed for death or HF hospitalization in the current study, PAC was identified as an independent predictor of adverse events. One may reasonably propose that of the several determinants of RV afterload, PAC, which is affected by the whole pulmonary arterial system, rather than PVR, which is influenced by the small arteries and arterioles alone, is an independent predictor of adverse outcomes.

Several hemodynamic parameters, such as RV systolic pressure, systolic PAP, and PVR, have been used to investigate long-term outcomes following AVR for severe AS, but PAC has rarely been considered.^7,8 Although the regression of LVH occurs early after AVR,^24,25 myocardial normalization is not always possible. Treibel et al showed that focal replacement fibrosis was irreversible, in contrast to diffuse fibrosis.²⁶ If this transition point to maladaptive remodeling can be anticipated, then intervention can be performed before the emergence of an irreversible focal replacement scar. Whether preoperative PAC can be a surrogate for the transition point to maladaptive remodeling and thus useful for timing AVR for severe AS in terms of long-term outcomes remains to be determined.

Study Limitations

First, this was a single-center retrospective study with the well-known inherent limitations. Second, the study involved a relatively small number of patients after AVR and a short follow-up period, resulting in a relatively small number of deaths or HF admissions, which limited the number of covariates that could be analyzed in the multivariate models. This increases the risk of type II errors and may limit the ability to determine whether the tested outcome predictors are independent of other variables. However, follow-up was complete for all patients, and the exclusion of patients for whom a complete set of hemodynamic data was unavailable, who had concomitant mitral or tricuspid valve surgery, or had endstage renal disease with hemodialysis should eliminate various confounding factors. The fact that PAC was predictive of adverse events even in a relatively small sample is important. Third, several surgeons were involved during this 13-year period, which can increase the variability of the data; however, this may limit the effect of surgeon-dependent factors on outcomes. Finally, no data were available on specific conditions that might have affected PAC, such as chronic pulmonary disease or sleep apnea syndrome.

Conclusions

In the study patients undergoing AVR for severe AS, even in the absence of PH, preoperative reduced PAC was independently associated with adverse surgical outcomes. It seems that preoperative PAC has potential as an independent predictor of long-term prognosis after AVR for severe AS.

Disclosure

No funding was received for this paper.

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