Poor Increase in Pulse Pressure During Cardiopulmonary Exercise Testing Predicts Cardiovascular Death of Patients With Heart Failure With Reduced Ejection Fraction

Abstract

Background: The increase in stroke volume during inotropic stimulation in patients with heart failure with reduced ejection fraction (HFrEF) is called the “pump function reserve.” Few studies have reported on the relationship between pump function reserve and HF prognosis. In HFrEF patients who have pump function reserve, stroke volume increases during exercise. Simply put, the pulse pressure change (∆PP) during cardiopulmonary exercise testing (CPX) is closely related to the prognosis of patients with HFrEF. We hypothesized that ∆PP could predict disease severity and cardiovascular death in patients with HFrEF.

Methods and Results: A total of 224 patients with HFrEF who underwent symptom-limited maximal CPX between 2012 and 2016 were enrolled. During a median follow-up of 1.5 years, cardiovascular death occurred in 54 participants (24%). Patients who died demonstrated a lower ∆PP between rest and peak exercise (∆PP [peak−rest]) than those who survived (P<0.001). Cox regression analyses revealed that ∆PP, slope of the relationship between minute ventilation and carbon dioxide production, and B-type natriuretic peptide level were independent predictors of cardiovascular death in patients with HFrEF (P=0.001, 0.021, and <0.001, respectively).

Conclusions: ∆PP (peak−rest) can accurately predict cardiovascular death in patients with HFrEF and may be a useful new prognostic indicator in these patients.

Cardiopulmonary exercise testing (CPX) is routinely used in the prognostic evaluation of patients with heart failure with reduced ejection fraction (HFrEF). Agostoni et al conducted the first large-scale multicenter study in which the prognostic score and the metabolic exercise test data, combined with the cardiac and kidney indexes (MECKI) score, were used in assessing patients with HFrEF. The MECKI score combines CPX data with clinical, laboratory, and echocardiographic measurements, such as the percentage of the predicted value of peak oxygen consumption (% peak V̇O₂), the slope of the relationship between minute ventilation and carbon dioxide production (V̇E vs. V̇CO₂ slope), ejection fraction (EF), hemoglobin (Hb) level, estimated glomerular filtration rate (eGFR), and serum sodium (Na) level.¹ Subsequently, Carubelli et al successfully demonstrated the validity of the MECKI prognostic score.^2,3

Recent reports have shown an increase in the stroke volume (SV) of some patients with HFrEF during inotropic stimulation by dobutamine in a phenomenon called the “pump function reserve”.⁴ Nearly all previous studies have investigated the relationship between the of pump function reserve and exercise capacity.^5–9 Only one study, by Scrutinio et al, has reported a significant association between the percentage change in end-systolic volume index during CPX and dobutamine infusion, and the occurrence of adverse events.¹⁰ However, performing echocardiography during CPX is extremely difficult in Japan because of the shortage of experienced technicians and sonographers who can obtain images during stress testing, the limited amount of available evidence, and inadequate standardized testing protocols.¹¹ Considering these issues, performing echocardiography during CPX is therefore often impractical.

Pulse pressure (PP) is the difference between systolic and diastolic blood pressures (BP). Systolic BP is defined as the maximum pressure developed in the aorta by the left ventricle, whereas diastolic BP is defined as the minimum pressure in the aorta while the heart relaxes before ejecting the blood into the aorta from the left ventricle. The PP difference has 2 major components, namely: (a) the effects of ventricular ejection and the properties of the arterial circulation such as arterial compliance (direct component) and (b) the effects of wave reflection (indirect component).^12,13 In all patients with HFrEF, arterial compliance is decreased due to the compensatory activation of the neurohormonal mechanism;¹⁴ therefore, PP is closely related to SV.

In patients with HFrEF who have pump function reserve, SV increases during exercise, such as CPX. Simply put, PP would increase during CPX, and this is closely related to the prognosis of patients with HFrEF.

Based on our understanding of this mechanism and the results of previous studies, we hypothesized that patients with severe HF have poor pump function reserve and consequently demonstrate a reduced increase in PP (∆PP) during CPX. This study aimed to evaluate the relationship between ∆PP and cardiovascular death in patients with HFrEF. Several previously reported prognostic risk factors, including Na level, Hb level, eGFR, % peak V̇O₂, the V̇E vs. V̇CO₂ slope, EF, and B-type natriuretic peptide (BNP) level were analyzed.^1,15,16

Methods

Patient Selection

In this cohort study, data were collected from the Gunma Prefectural Cardiovascular Center database, which was established in 2012 for newly admitted patients. Data of patients who underwent symptom-limited maximal CPX between 2012 and 2016 were analyzed. The inclusion criteria were previous or present HF symptoms (New York Heart Association [NYHA] functional classes II–III, American College of Cardiology/American Heart Association [ACC/AHA] classification stage C), previous documentation of left ventricular systolic dysfunction (left ventricular EF [LVEF] <40%), stable clinical condition with unchanged medications for at least 3 months, ability to perform CPX, and no major cardiovascular treatments or interventions scheduled. The exclusion criteria included a history of pulmonary embolism, moderate-to-severe aortic or mitral regurgitation and stenosis, pericardial disease, severe obstructive lung disease, exercise-induced angina and significant ECG alterations, or the presence of any clinical comorbidity that could interfere with exercising. Based on these criteria, 224 patients with HFrEF were enrolled.

The relevant results of the following investigations were recorded: (1) blood sampling performed after a 12-h overnight fast to assess blood levels of Hb, lymphocytes, Na, uric acid (UA), fasting plasma glucose (FPG), hemoglobin A1c (HbA1c), total cholesterol (TC), triglyceride, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and BNP; eGFR was calculated using the Japanese Society of Nephrology formulae¹⁷ (194×serum creatinine^−1.094×age^−0.287 for men and 194×serum creatinine^−1.094×age^−0.287×0.739 for women); (2) BP measured after 10 min of rest in a seated position and expressed as the average of 3 consecutive measurements of each arm using the conventional cuff method; (3) transthoracic echocardiography results; and (4) cardio-ankle vascular index (CAVI).

The endpoint was cardiovascular death, defined as any fatal event related to coronary artery disease, cerebrovascular disease, and other heart or vascular diseases, specifically fatal myocardial infarction, acute coronary syndrome, stroke, transient ischemic attack, HF, and arrhythmia.¹⁸ The time interval from CPX to cardiovascular death was defined as the duration of follow-up. Endpoints were censored in October 2018. Notably, the rate of follow-up was 100%.

Cardiopulmonary Exercise Testing

Anaerobic threshold (AT) and peak oxygen consumption (V̇O₂) were evaluated using symptom-limited CPX that was performed on an upright cycle ergometer (StregthErgo8; Mitsubishi Electric Engineering, Tokyo, Japan) with an ECG machine (ML-9000; Fukuda Denshi, Ltd., Tokyo, Japan). CPX was performed 2–4 h after a light meal. Following recommendations,^19,20 the tests included a 3-min rest and a 3-min warm-up period at 0 W, followed by a continuous increase in the work rate (WR) by 1 W every 6 s until exhaustion. The criteria for halting the exercise testing in this study are outlined in the American College of Sports Medicine guidelines.²¹ The increments in WR level were selected based on the patients’ ability to perform the exercises within 8–15 min.^19,20 V̇O₂, V̇CO₂, and V̇E were measured on a breath-by-breath basis using a gas analyzer (MINATO 300S; Minato Science Co., Ltd., Osaka, Japan). Peak V̇O₂ was determined as V̇O₂ at the highest WR. The AT was measured using the V-slope method.²² Respiratory compensation point (RCP) was recorded when an increase in the V̇E/V̇CO₂ ratio was simultaneously observed with a decrease in end-tidal CO₂ pressures (PETCO₂).²³ The predicted peak V̇O₂ (% peak V̇O₂) and AT (% AT) were determined based on data from a healthy Japanese population.²⁴

BP

BP was measured at the 1st and 5th Korotkoff phases with the use of an arm-cuff sphygmomanometer during CPX. Brachial PP was calculated as the difference between systolic and diastolic BP.²⁵ PP at rest, PP increase between AT and rest (∆PP [AT–rest]), and PP increase between peak exercise and rest (∆PP [peak–rest]) were calculated.

Statistical Analysis

Basic demographic data (e.g., age and body mass index [BMI]), cardiovascular risk factors (e.g., number of lymphocytes and Hb, Na, UA, and TC levels), biomarkers (e.g., BNP levels), and CPX parameters (e.g., ∆PP, V̇O₂, AT, peak V̇O₂, the V̇E vs. V̇CO₂ slope, load, PETCO₂, and peak O₂ pulse) were compared between patients who survived and those who died during the follow-up period. The distribution of each continuous variable was tested for normality using the Shapiro-Wilk test, and the results are expressed as mean±standard deviation. Variables with a skewed distribution are expressed as median [interquartile range]. Statistical significance of obtained results was assessed by unpaired t-test or Mann-Whitney U test for continuous variables and the chi-squared test for categorical variables. In the investigation of the associations with cardiovascular death, univariate and multivariate Cox regression analyses were performed to examine the aforementioned potential factors, including Na level, Hb level, eGFR, % peak V̇O₂, the V̇E vs. V̇CO₂ slope, EF, and BNP level.^1,3,15,16 Notably, systolic BP at peak exercise, peak HR, nadir V̇E/V̇CO₂, maximum PETCO₂, or peak load were not used in the multivariate analysis, although a significant difference was observed between the 2 groups. This is because the explanatory variables were selected based on our experience in specialized fields and previous literature.^1,15 As mentioned in the Results, a relatively high number of patients died of arrhythmia in this study. Therefore, only the univariate Cox regression analysis was performed using a history of ventricular fibrillation.

Receiver-operating characteristic (ROC) curves were used to identify the sensitivity and specificity of ∆PP (peak–rest) for predicting cardiovascular death, and the area under the curve (AUC) was calculated. Survival analyses were similarly performed using Kaplan-Meier models. All statistical analyses were performed using the Statistical Package for Social Sciences 21.0J for Mac (IBM Corp., Armonk, NY, USA). Statistical significance was set at a 2-sided P-value <0.05.

Ethics Statement

This study was approved by the Ethics Committee of Gunma Prefectural Cardiovascular Center (approval no. 31018) and was conducted in accordance with the Declaration of Helsinki. Informed consent was given by each patient.

Results

Baseline Clinical Characteristics of Patients

Table 1 summarizes the baseline characteristics of patients who survived and those who died during a median follow-up period of 1.5 years. Cardiovascular death was documented in 54 patients (24%), with 38 patients (16%) dying of HF and 16 patients (7%) dying from arrhythmia. The mean age and BMI were not significantly different between groups. The patients who died had lower Hb and higher BNP levels, a higher prevalence of atrial fibrillation, a higher rate of receiving an implantable cardioverter defibrillator (ICD) and cardiac resynchronization therapy (CRT), and were more likely to be ventricular fibrillation survivors (126±21 g/L vs. 139±29 g/L, P<0.01; 720.2 [255.1, 1,054.7] ng/L vs. 246.5 [109.8, 458.5] ng/L, P<0.01; 50% vs. 32%, P=0.02; 46% vs. 14%, P<0.01, 20% vs. 1%, P<0.01, respectively) than those who survived. In contrast, no significant differences were observed in the lymphocyte count, eGFR, or the serum levels of Na, UA, FPG, HbA1c, TC, triglycerides, LDL-C, or HDL-C. Moreover, no significant differences were detected between the 2 groups regarding CAVI, NYHA class, the prevalence of hypertension, diabetes mellitus, or dyslipidemia, or the etiology of HF. Regarding the echocardiography findings, there was no significant difference in LVEF between the 2 groups. Moreover, no differences were observed between the groups in the proportion of patients on cardioprotective agents such as β-blockers.

Table 1. Characteristics of the Study Population in Each Group

	Death (n=54)	Survival (n=170)	P value
Patient characteristics
Sex (male/female)	44/10	132/38	0.50
Age (years)	62.9±14.6	61.4±14.1	0.48
Height (cm)	162.5±10.2	163.5±8.4	0.46
Weight (kg)	57.5±14.0	62.3±15.8	0.06
BMI (kg/m2)	21.6±4.1	23.1±4.7	0.09
LVEF (%)	28.1±12.0	28.9±7.7	0.63
Hb level (g/L)	126±21	139±29	<0.01*
Lymphocyte count (%)	26.7±9.6	26.8±8.0	0.23
Sodium level (mmol/L)	139.0 [134.0, 140.0]	141.0 [139.0, 143.0]	0.10
Uric acid level (μmol/L)	416.4±136.8	416.4±214.2	0.90
eGFR (mL/min/1.73 m2)	55.9±34.1	58.7±22.2	0.49
BNP level (ng/L)	720.2 [255.1, 1,054.7]	246.5 [109.8, 458.5]	<0.01*
FPG (mg/dL)	94.0 [85.0, 123.0]	105.0 [88.0, 117.0]	0.21
HbA1c (%)	6.4 [6.1, 6.8]	6.2 [5.8, 6.8]	0.90
Total cholesterol level (mmol/L)	4.4 [3.6, 4.9]	4.5 [4.1, 5.3]	0.10
Triglyceride (mg/dL)	111.5 [83.0, 188.0]	111.0 [81.0, 154.0]	0.55
LDL-C (mg/dL)	88.0 [79.0, 104.3]	98.0 [80.0, 119.5]	0.07
HDL-C (mg/dL)	47.5 [35.3, 52.3]	46.0 [37.0, 53.0]	0.11
CAVI	9.86±0.80	9.29±0.60	0.41
Atrial fibrillation	27 (50)	55 (32)	0.02*
ICD/CRT	25 (46)	25 (14)	<0.01*
Pacemaker	3 (6)	14 (8)	0.77
VF survivor	11 (20)	2 (1)	<0.01*
NYHA class II/III	6/48	29/141	0.39
Etiology of HF
Ischemic/non-ischemic	28/26	108/62	0.15
Medical history
Hypertension	12 (22)	58 (34)	0.12
Diabetes mellitus	12 (22)	50 (29)	0.38
Dyslipidemia	13 (24)	56 (32)	0.24
Medical therapy
β-blocker	51 (94)	147 (86)	0.09
ACEI/ARB	36 (67)	118 (69)	0.76
Spironolactone	29 (54)	80 (47)	0.39
Amiodarone	15 (27)	31 (18)	0.17
Sotalol	1 (2)	2 (1)	0.56
Digitalis	3 (6)	4 (2)	0.36
Loop diuretic	39 (72)	140 (82)	0.08
Calcium-channel blocker	3 (5)	14 (8)	0.76
Statin	28 (51)	110 (64)	0.10
Antiplatelet	28 (51)	112 (65)	0.07
NOAC	5 (9)	23 (42)	0.48
Warfarin	22 (40)	32 (18)	0.01*
Insulin	1 (7)	8 (4)	0.69

Values are mean±standard deviation, median value [interquartile range], or n (%). *Statistical significance. ACEI, angiotensin-converting enzyme inhibitor; ARB, angiotensin receptor blocker; BMI, body mass index; BNP, B-type natriuretic peptide; CAVI, cardio-ankle vascular index; CRT, cardiac resynchronization therapy; eGFR, estimated glomerular filtration rate; FPG, fasting plasma glucose; ICD, Implantable cardioverter defibrillator; Hb, hemoglobin; HbA1c, hemoglobin A1c; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; LVEF, left ventricular ejection fraction; NOAC, non-vitamin K antagonist oral anticoagulant; NYHA, New York Heart Association; VF, ventricular fibrillation.

Comparison of CPX Parameters

The CPX parameters of each group are summarized in Table 2. There were no significant differences in systolic or diastolic BP at rest. However, significant differences were observed in systolic BP at peak exercise (121.6±33.3 mmHg vs. 140.3±28.6 mmHg, P<0.001). In addition, the heart rate at peak exercise was significantly higher in patients who survived than in those who died (115.3±21.9 beats/min vs. 100.4±24.1 beats/min, P<0.001). Regarding PP, no significant differences in PP were observed at rest; however, there were significant differences in PP at peak exercise (37.9±18.6 mmHg vs. 40.7±15.1 mmHg; P=0.26 and 51.4±25.3 mmHg vs. 66.1±23.1 mmHg, P<0.001, respectively). Concerning the increase in PP, significant differences were observed in the PP increases from rest to peak exercise (∆PP [peak–rest]) (13.5±16.7 mmHg vs. 22.0±12.0 mmHg, P<0.001).

Table 2. Differences in Cardiopulmonary Exercise Test Parameters Between Groups

	Death (n=54)	Survival (n=170)	P value
Systolic BP at rest (mmHg)	102.3±21.5	108.3±20.9	0.60
Diastolic BP at rest (mmHg)	63.6±11.6	67.6±13.0	0.41
Systolic BP at AT (mmHg)	117.4±26.7	124.1±29.7	0.18
Diastolic BP at AT (mmHg)	67.1±16.6	70.5±16.8	0.24
Systolic BP at peak (mmHg)	121.6±33.3	140.3±28.6	<0.001*
Diastolic BP at peak (mmHg)	70.2±15.8	74.3±13.8	0.06
PP at rest (mmHg)	37.9±18.6	40.7±15.1	0.26
PP at AT (mmHg)	41.2±33.7	52.3±20.6	0.004*
PP at peak (mmHg)	51.4±25.3	66.1±23.1	<0.001*
ΔPP (AT–rest) (mmHg)	11.2±16.7	14.0±11.2	0.08
ΔPP (peak–rest) (mmHg)	13.5±16.7	22.0±12.0	<0.001*
Heart rate at rest (beats/min)	75.3±13.8	74.4±12.5	0.63
Heart rate at peak (beats/min)	100.4±24.1	115.3±21.9	<0.001*
Rest V̇O2 (mL/min/kg)	3.5±0.8	3.7±0.7	0.11
AT (mL/min/kg)	8.1±2.0	10.7±8.1	0.04*
Peak V̇O2 (mL/min/kg)	10.2±3.8	14.0±4.0	<0.001*
% AT (%)	51.2±12.3	63.2±14.5	0.01*
% peak (%)	42.2±12.6	57.1±15.3	<0.001*
V̇E vs. V̇CO2 slope	42.6 [34.6, 56.0]	35.8 [31.5, 42.7]	<0.001*
Nadir V̇E/V̇CO2	42.9 [40.0, 56.7]	39.6 [34.6, 44.7]	<0.001*
Peak load (watts)	42.0 [29.0, 60.0]	63.0 [49.0, 82.7]	<0.001*
Maximum PETCO2 (mmHg)	31.6±2.0	36.5±4.8	0.002*
Peak O2 pulse (mL/beat)	5.6 [4.2, 7.4]	7.3 [5.7, 9.3]	0.51

Values are mean±standard deviation or median value [interquartile range]. *Statistical significance. AT, anaerobic threshold; BP, blood pressure; PP, pulse pressure; peak VO₂, oxygen uptake at peak work rate; PETCO₂, end-tidal carbon dioxide pressure; rest V̇O₂, oxygen uptake at rest; V̇CO₂, carbon dioxide production; V̇E, minute ventilation.

No significant differences were observed in V̇O₂ at rest; however, significant differences in AT and peak V̇O₂ were observed. Parameters indicating cardiac function during exercise, such as the V̇E vs. V̇CO₂ slope (42.6 [34.6, 56.0] vs. 35.8 [31.5, 42.7], P<0.001), nadir V̇E/V̇CO₂ (42.9 [40.0, 56.7] vs. 39.6 [34.6, 44.7], P<0.001), maximum PETCO₂ (31.6±2.0 mmHg vs. 36.5±4.8 mmHg, P=0.002) were significantly different between the groups.

Predictors of Cardiovascular Death

In the univariate analysis, the following factors were significant predictors of cardiovascular death: % peak V̇O₂ (hazard ratio [HR]: 0.945; 95% confidence interval [CI]: 0.927–0.964; P<0.001), Hb level (HR: 0.773; 95% CI: 0.660–0.904; P<0.001), the V̇E vs. V̇CO₂ slope (HR: 1.014; 95% CI: 1.007–1.021; P<0.001), sodium level (HR: 0.973; 95% CI: 0.955–0.991; P=0.046), BNP level (HR: 1.003; 95% CI: 1.002–1.004; P<0.001), ∆PP (peak–rest) (HR: 0.944; 95% CI: 0.923–0.966; P<0.001), and PP at peak (HR: 0.973; 95% CI: 0.960–0.986; P<0.001) (Tables 3,4).

Table 3. Univariate and Multivariate Cox Regression Analyses of Cardiovascular Death

Variable	Univariate			Multivariate
	HR	95% CI	P value	HR	95% CI	P value
% peak V̇O2 (%)	0.945	0.927–0.964	<0.001*
Hb level (g/L)	0.773	0.660–0.904	<0.001*
VE vs. V̇CO2 slope	1.014	1.007–1.021	<0.001*	1.028	1.004–1.053	0.021*
Sodium level (mmol/L)	0.973	0.955–0.991	0.046*
LVEF (%)	0.994	0.953–1.038	0.809
eGFR (mL/min/1.73 m2)	0.993	0.981–1.006	0.328
BNP level (ng/L)	1.003	1.002–1.004	<0.001*	1.005	1.003–1.007	<0.001*
ΔPP (peak–rest) (mmHg)	0.944	0.923–0.966	<0.001*	0.932	0.893–0.974	0.001*

*Statistical significance. CI, confidence interval; HR, hazard ratio; % peak V̇O₂, predicted value of oxygen uptake at peak work rate; PP, pulse pressure. Other abbreviations as in Tables 1,2.

Table 4. Univariate and Multivariate Cox Regression Analyses of Cardiovascular Death

Variable	Univariate			Multivariate
	HR	95% CI	P value	HR	95% CI	P value
% peak V̇O2 (%)	0.945	0.927–0.964	<0.001*
Hb level (g/L)	0.773	0.660–0.904	<0.001*
VE vs. V̇CO2 slope	1.014	1.007–1.021	<0.001*	1.039	1.017–1.061	<0.001*
Sodium level (mmol/L)	0.973	0.955–0.991	0.046*
LVEF (%)	0.994	0.953–1.038	0.809
eGFR (mL/min/1.73 m2)	0.993	0.981–1.006	0.328
BNP level (ng/L)	1.003	1.002–1.004	<0.001*	1.006	1.004–1.008	<0.001*
PP at peak (mmHg)	0.973	0.960–0.986	<0.001*

*Statistical significance. Abbreviations as in Tables 1,3.

Regarding the history of ventricular fibrillation, only the univariate analysis was performed, and the result was as follows: HR: 3.823; 95% CI: 1.94–7.535; P<0.001.

Multivariate analysis revealed that the V̇E vs. V̇CO₂ slope (HR: 1.028; 95% CI: 1.004–1.053; P=0.021), BNP level (HR: 1.005; 95% CI: 1.003–1.007; P<0.001), and ∆PP (peak–rest) (HR: 0.932; 95% CI: 0.893–0.974; P=0.001) were independent predictors of cardiovascular death (Table 3).

Univariate and multivariate Cox regression analyses were equally performed with the explanatory variables changed from ∆PP (peak–rest) to PP at peak. However, PP at peak was not an independent predictor of cardiovascular death (Table 4).

∆PP (Peak–Rest) Cutoff Level

Based on ROC curve analysis, the optimal cutoff for ∆PP (peak–rest) in the prediction of cardiovascular death was 11.5 mmHg, with a specificity and sensitivity of 76.5% and 57.4%, respectively (AUC=0.718; 95% CI: 0.633–0.803) (Figure 1).

Figure 1.

ROC curve of ∆PP (peak–rest) as a predictor of cardiovascular death. PP, pulse pressure; ∆PP (peak–rest), difference between PP at peak and at rest; ROC, receiver-operating characteristic.

Long-Term Follow-up and New-Onset Cardiovascular Death

Similarly, the event-free survival curve was evaluated using the ∆PP (peak–rest) cutoff value (11.5 mmHg). Results indicated that individuals with ∆PP (peak–rest) ≤11.5 mmHg demonstrated a significantly higher risk of cardiovascular death than did individuals with a ∆PP (peak–rest) >11.5 mmHg (P<0.001) (Figure 2).

Figure 2.

Kaplan-Meier survival curves of cardiovascular death according to ∆PP (peak–rest) > or ≤11.5 mmHg. PP, pulse pressure; ∆PP (peak–rest), difference between PP at peak and at rest.

Discussion

This study observed that patients with a smaller increase in PP during CPX had a higher incidence of cardiovascular death and greater severity of HF than patients with a higher ∆PP (peak–rest).

PP is the difference between systolic and diastolic BP, reflecting the complex interaction between cardiac ejection and the properties of the large arteries.^26–28 Many studies have shown that PP is an easily quantifiable parameter that correlates with arterial stiffness and pulsatile hemodynamic load;^26–28 moreover, PP is considered to be an independent predictor of chronic HF (CHF).²⁹ PP is the single most informative BP parameter because it best captures the physiological sequelae of arterial stiffness as reflected in the disproportionately elevated systolic BP and decreased diastolic BP. Previous studies have focused on the aortic compliance, which is one of the elements determining the PP; unfortunately, the other element of PP was not considered, which is cardiac ejection. This study focused on cardiac ejection. In addition, all other studies focused on resting PP, and very few studies have examined the increase in PP during exercise. Therefore, this study provides a novel perspective on PP increase during exercise and its relevance to HFrEF prognosis.

The pump function reserve can be exclusively evaluated during exercise or inotropic stimulation.⁴ In CHF, the sympathetic nervous system activity increases chronically, leading to a variety of maladaptive changes in the regulation of cardiovascular function.³⁰ Beta-adrenergic receptor pathway desensitization, a fundamental abnormality in CHF that results from chronic activation of the sympathetic nervous system,³¹ is the main determinant of the attenuated cardiac response to inotropic stimulation.^32–34 It depends on the degree of myocardial failure, and the nature of systolic dysfunction.³¹ Based on this mechanism, the pump function reserve is closely related to the severity of HF.

Scrutinio et al reported that the cardiac response to low-dose dobutamine and exercise (as assessed by echocardiography) correlated with peak V̇O₂ and the occurrence of death or hospital readmission for worsening HF in patients with CHF secondary to idiopathic cardiomyopathy.¹⁰ Peak V̇O₂ has a strong relationship with peak cardiac output, suggesting that peak V̇O₂ is closely associated with circulatory dysfunction during exercise.^5–9,35,36 Peak V̇O₂ is generally considered the most powerful predictor of HF;^37–39 accordingly, the pump function reserve is closely related to HFrEF prognosis.

As mentioned earlier, the pump function reserve can be exclusively evaluated during exercise or inotropic stimulation such as dobutamine infusion.⁴ Many studies report fewer complications of the dobutamine stress test;⁴⁰ however, very few reports limited to patients with HFrEF are currently available. With regard to CPX, in the HF-ACTION trial, Keteyian et al examined subjects with left ventricular dysfunction and observed no fatal events and only 2 episodes of ventricular arrhythmia.⁴¹ Those results suggest that CPX is a significantly safer stimulation test than dobutamine stress testing in patients with HFrEF. Concerning echocardiography, its use during ergometer stress testing is not widespread in Japan, mainly because of equipment-related factors (e.g., insufficient ergometers or space for test implementation) at each medical institution and a shortage of experienced technicians and sonographers who can obtain images during stress testing. Other possible reasons are the limited evidence available in Japan and inadequate standardized testing protocols.¹¹ Therefore, performing echocardiography using CPX remains impractical in Japan. For these reasons, CPX and PP were selected instead of dobutamine infusion and echocardiography. The calculation of PP is significantly easier, less time-consuming, and much more practical.

CPX is routinely used in the prognostic evaluation of patients with HFrEF, as the prognostic value of peak V̇O₂ and the V̇E vs. V̇CO₂ slope is high and well established.^42–44 However, in this study, peak V̇O₂, the V̇E vs. V̇CO₂ slope, and ∆PP (peak–rest) were associated with cardiovascular death in the univariate analysis; in contrast, unlike peak V̇O₂, ∆PP (peak–rest) and the V̇E vs. V̇CO₂ slope were associated with cardiovascular death in the multivariate analysis. This is because of the small sample size and, as reported earlier, there were no significant differences between the groups regarding the NYHA class. Peak V̇O₂, a prognostic indicator in patients with HFrEF, was significantly different between patients who survived and those who died; however, both groups had low values, which is probably why peak V̇O₂ was not identified as a statistically significant prognostic predictor.

In previous studies, the BNP level was reported as an important factor in the assessment of severity and prediction of poor prognosis in patients with HF.^16,45 Systematic reviews have reported that the BNP and NT-pro BNP levels are independent predictors of death (all-cause and cardiovascular) in HF.^16,46 Regarding the V̇E vs. V̇CO₂ slope, reduced PaCO₂ and increased fractional dead space resulted in an abnormal elevation in the V̇E vs. V̇CO₂ slope. This factor is equally important for the prediction of poor prognosis in patients with HF, and it is already established as an important prognostic marker in CPX.⁴⁷ Therefore, our results were consistent with those of previous studies. Ventricular arrhythmias, including ventricular premature beats, ventricular tachycardia, and ventricular fibrillation, are common in patients with HF.^48–50 Sudden cardiac death is a major cause of death among HF patients and is commonly related to ventricular arrhythmia.⁵¹ The risk of ventricular arrhythmias is similarly increased by comorbidities such as electrolyte disturbances, hypoxemia, excess catecholamines and renal and hepatic dysfunction, and is closely related to the severity of HF.⁵² Additionally, in most cases, ventricular arrhythmias are complications of CHF secondary to cardiac damage.⁵³ In this study, a significantly higher proportion of patients with a history of ventricular fibrillation died. Such data not only support the validity of this study but also have potential clinical significance. The direct relationship between the occurrence of ventricular arrhythmia and ∆PP is yet to be confirmed; however, from the hypothesis that ∆PP could be closely related to the pump function reserve, ∆PP could be related to the incidence of ventricular arrhythmias. In addition, this marker could be useful in the prediction of ventricular fibrillation. Further investigation is required to confirm this relationship.

Study Limitations

To the best of our knowledge, this is the first study to investigate the relevance of PP increase in the cardiovascular death of patients with HFrEF. However, this study had several limitations. First, both the sample size and the number of outcomes were small. Therefore, the generalizability of the obtained results is limited. Second, this was a retrospective, single-center study. Therefore, the possibility of unintentional selection bias cannot be fully excluded. Third, echocardiography was not performed and the pump function reserve was not evaluated for reasons stated above. Finally, the results of this study are exclusively applicable to patients with HFrEF because patients with preserved systolic function or with other diseases that affect exercise performance were not evaluated.

In conclusion, it is important to perform CPX in patients with HFrEF to assess ∆PP (peak–rest), because this is an important prognostic parameter and determinant of HF severity. Therefore, evaluation of the pump function reserve has physiological significance and prognostic power in patients with HF. The results of this study could facilitate more accurate prediction of cardiovascular death in patients with HFrEF and selection of the appropriate treatment by physicians. Furthermore, ∆PP (peak–rest) may be used to evaluate the therapeutic effects of treatments in patients with HFrEF by comparing the ∆PP (peak–rest) before and after treatment.

Acknowledgments

We thank our lecturers, Haruyasu Fujita (Department of Public Health, Gunma University, Gunma, Japan) and Bumsuk Lee (Gunma University Graduate School of Health Sciences, Gunma, Japan), for their valuable statistical advice during the preparation of this report. We thank Editage (http://www.editage.jp) for English language editing.

Author Contributions

T.N. led the study as the principal investigator, prepared the plan for the statistical analyses, and drafted and revised the manuscript. H.A. cleaned the data and performed the statistical analyses. M.M. and S.N. collected the data. All authors have approved the final version of the manuscript.

Data Availability

The individual participant data and datasets generated and analyzed that underlie the results reported in this article after de-identification (text, tables, figures, and appendices) will be shared on a request basis. The data registered in UMIN-CTR (trial registration number: UMIN 000039250) will be additionally available. The data will become available beginning from 9 months and ending 12 months following this article’s publication. The data access criteria will be for researchers who provide a methodologically sound proposal and sign a data access agreement.

Please directly contact the corresponding author to request data sharing, E-mail: [e-mail]

Conflicts of Interest

The authors declare no conflicts of interest.

Funding

This research received no grant from any funding agency in the public, commercial, or not-for-profit sectors.

IRB Approval Information

This study was approved by the Ethics Committee of Gunma Prefectural Cardiovascular Center (approval no. 31018).

References

• 1.   Agostoni P, Corra U, Cattadori G, Veglia F, La Gioia R, Scardovi AB, et al. Metabolic exercise test data combined with cardiac and kidney indexes, the MECKI score: A multiparametric approach to heart failure prognosis. Int J Cardiol 2013; 167: 2710–2718.
• 2.   Goto Y. Exercise capacity: Just a powerful prognostic predictor, or a potential therapeutic target in patients with chronic heart failure? Circ J 2015; 79: 2547–2548.
• 3.   Carubelli V, Metra M, Corra U, Magri D, Passino C, Lombardi C, et al. Exercise performance is a prognostic indicator in elderly patients with chronic heart failure: Application of metabolic exercise cardiac kidney indexes score. Circ J 2015; 79: 2608–2615.
• 4.   Cohen-Solal A, Logeart D, Guiti C, Dahan M, Gourgon R. Cardiac and peripheral responses to exercise in patients with chronic heart failure. Eur Heart J 1999; 20: 931–945.
• 5.   Weber KT, Kinasewitz GT, Janicki JS, Fishman AP. Oxygen utilization and ventilation during exercise in patients with chronic cardiac failure. Circulation 1982; 65: 1213–1223.
• 6.   Franciosa JA, Ziesche S, Wilen M. Functional capacity of patients with chronic left ventricular failure: Relationship of bicycle exercise performance to clinical and hemodynamic characterization. Am J Med 1979; 67: 460–466.
• 7.   Higginbotham MB, Morris KG, Conn EH, Coleman RE, Cobb FR. Determinants of variable exercise performance among patients with severe left ventricular dysfunction. Am J Cardiol 1983; 51: 52–60.
• 8.   Metra M, Raddino R, Dei Cas L, Visioli O. Assessment of peak oxygen consumption, lactate and ventilatory thresholds and correlation with resting and exercise hemodynamic data in chronic congestive heart failure. Am J Cardiol 1990; 65: 1127–1133.
• 9.   Sullivan MJ, Cobb FR. Central hemodynamic response to exercise in patients with chronic heart failure. Chest 1992; 101: 340S–346S.
• 10.   Scrutinio D, Napoli V, Passantino A, Ricci A, Lagioia R, Rizzon P. Low-dose dobutamine responsiveness in idiopathic dilated cardiomyopathy: Relation to exercise capacity and clinical outcome. Eur Heart J 2000; 21: 927–934.
• 11.   Suzuki K, Hirano Y, Yamada H, Murata M, Daimon M, Takeuchi M, et al. Practical guidance for the implementation of stress echocardiography. J Echocardiogr 2018; 16: 105–129.
• 12.   Dart AM, Kingwell BA. Pulse pressure: A review of mechanisms and clinical relevance. J Am Coll Cardiol 2001; 37: 975–984.
• 13.   Lakatta EG, Levy D. Arterial and cardiac aging: Major shareholders in cardiovascular disease enterprises. Part I: Aging arteries: A “set up” for vascular disease. Circulation 2003; 107: 139–146.
• 14.   Pepper GS, Lee RW. Sympathetic activation in heart failure and its treatment with beta-blockade. Arch Intern Med 1999; 159: 225–234.
• 15.   Agostoni P, Paolillo S, Mapelli M, Gentile P, Salvioni E, Veglia F, et al. Multiparametric prognostic scores in chronic heart failure with reduced ejection fraction: A long-term comparison. Eur J Heart Fail 2018; 20: 700–710.
• 16.   Santaguida PL, Don-Wauchope AC, Oremus M, McKelvie R, Ali U, Hill SA, et al. BNP and NT-proBNP as prognostic markers in persons with acute decompensated heart failure: A systematic review. Heart Fail Rev 2014; 19: 453–470.
• 17.   Kimura K. Preface: Evidence-based clinical practice guidelines for CKD: An abridged English version. Clin Exp Nephrol 2014; 18: 339–340.
• 18.   Elfassy T, Swift SL, Glymour MM, Calonico S, Jacobs DR Jr, Mayeda ER, et al. Associations of income volatility with incident cardiovascular disease and all-cause mortality in a US cohort. Circulation 2019; 139: 850–859.
• 19.   Buchfuhrer MJ, Hansen JE, Robinson TE, Sue DY, Wasserman K, Whipp BJ. Optimizing the exercise protocol for cardiopulmonary assessment. J Appl Physiol Respir Environ Exerc Physiol 1983; 55: 1558–1564.
• 20.   Agostoni P, Bianchi M, Moraschi A, Palermo P, Cattadori G, La Gioia R, et al. Work-rate affects cardiopulmonary exercise test results in heart failure. Eur J Heart Fail 2005; 7: 498–504.
• 21.   Thompson PD, Arena R, Riebe D, Pescatello LS, American College of Sports Medicine. ACSM’s new preparticipation health screening recommendations from ACSM’s guidelines for exercise testing and prescription, ninth edition. Curr Sports Med Rep 2013; 12: 215–217.
• 22.   Beaver WL, Wasserman K, Whipp BJ. Bicarbonate buffering of lactic acid generated during exercise. J Appl Physiol (1985) 1986; 60: 472–478.
• 23.   Agostoni P, Dumitrescu D. How to perform and report a cardiopulmonary exercise test in patients with chronic heart failure. Int J Cardiol 2019; 288: 107–113.
• 24.   Itoh H, Koike A, Taniguchi K, Marumo F. Severity and pathophysiology of heart failure on the basis of anaerobic threshold (AT) and related parameters. Jpn Circ J 1989; 53: 146–154.
• 25.   Stergiopulos N, Meister JJ, Westerhof N. Simple and accurate way for estimating total and segmental arterial compliance: The pulse pressure method. Ann Biomed Eng 1994; 22: 392–397.
• 26.   Franklin SS, Gustin Wt, Wong ND, Larson MG, Weber MA, Kannel WB, et al. Hemodynamic patterns of age-related changes in blood pressure: The Framingham Heart Study. Circulation 1997; 96: 308–315.
• 27.   Smulyan H, Safar ME. Systolic blood pressure revisited. J Am Coll Cardiol 1997; 29: 1407–1413.
• 28.   O’Rourke MF. Arterial function in health and disease. Edinburgh: Churchill Livingstone, 1982.
• 29.   Chae CU, Pfeffer MA, Glynn RJ, Mitchell GF, Taylor JO, Hennekens CH. Increased pulse pressure and risk of heart failure in the elderly. JAMA 1999; 281: 634–639.
• 30.   Packer M. The neurohormonal hypothesis: A theory to explain the mechanism of disease progression in heart failure. J Am Coll Cardiol 1992; 20: 248–254.
• 31.   Bristow MR, Gilbert EM. Improvement in cardiac myocyte function by biological effects of medical therapy: A new concept in the treatment of heart failure. Eur Heart J 1995; 16(Suppl F): 20–31.
• 32.   Colucci WS, Denniss AR, Leatherman GF, Quigg RJ, Ludmer PL, Marsh JD, et al. Intracoronary infusion of dobutamine to patients with and without severe congestive heart failure: Dose-response relationships, correlation with circulating catecholamines, and effect of phosphodiesterase inhibition. J Clin Invest 1988; 81: 1103–1110.
• 33.   Colucci WS, Leatherman GF, Ludmer PL, Gauthier DF. Beta-adrenergic inotropic responsiveness of patients with heart failure: Studies with intracoronary dobutamine infusion. Circ Res 1987; 61: I82–I86.
• 34.   Fowler MB, Laser JA, Hopkins GL, Minobe W, Bristow MR. Assessment of the beta-adrenergic receptor pathway in the intact failing human heart: Progressive receptor down-regulation and subsensitivity to agonist response. Circulation 1986; 74: 1290–1302.
• 35.   Kraemer MD, Kubo SH, Rector TS, Brunsvold N, Bank AJ. Pulmonary and peripheral vascular factors are important determinants of peak exercise oxygen uptake in patients with heart failure. J Am Coll Cardiol 1993; 21: 641–648.
• 36.   Pardaens K, Van Cleemput J, Vanhaecke J, Fagard RH. Atrial fibrillation is associated with a lower exercise capacity in male chronic heart failure patients. Heart 1997; 78: 564–568.
• 37.   Mancini D, LeJemtel T, Aaronson K. Peak VO(2): A simple yet enduring standard. Circulation 2000; 101: 1080–1082.
• 38.   Cohn JN, Johnson GR, Shabetai R, Loeb H, Tristani F, Rector T, et al. Ejection fraction, peak exercise oxygen consumption, cardiothoracic ratio, ventricular arrhythmias, and plasma norepinephrine as determinants of prognosis in heart failure: The V-HeFT VA Cooperative Studies Group. Circulation 1993; 87: VI5–V16.
• 39.   Parameshwar J, Keegan J, Sparrow J, Sutton GC, Poole-Wilson PA. Predictors of prognosis in severe chronic heart failure. Am Heart J 1992; 123: 421–426.
• 40.   Geleijnse ML, Krenning BJ, Nemes A, van Dalen BM, Soliman OI, Ten Cate FJ, et al. Incidence, pathophysiology, and treatment of complications during dobutamine-atropine stress echocardiography. Circulation 2010; 121: 1756–1767.
• 41.   Keteyian SJ, Isaac D, Thadani U, Roy BA, Bensimhon DR, McKelvie R, et al. Safety of symptom-limited cardiopulmonary exercise testing in patients with chronic heart failure due to severe left ventricular systolic dysfunction. Am Heart J 2009; 158: S72–S77.
• 42.   Nakanishi M, Takaki H, Kumasaka R, Arakawa T, Noguchi T, Sugimachi M, et al. Targeting of high peak respiratory exchange ratio is safe and enhances the prognostic power of peak oxygen uptake for heart failure patients. Circ J 2014; 78: 2268–2275.
• 43.   Balady GJ, Williams MA, Ades PA, Bittner V, Comoss P, Foody JA, et al. Core components of cardiac rehabilitation/secondary prevention programs: 2007 update. A scientific statement from the American Heart Association Exercise, Cardiac Rehabilitation, and Prevention Committee, the Council on Clinical Cardiology; the Councils on Cardiovascular Nursing, Epidemiology and Prevention, and Nutrition, Physical Activity, and Metabolism; and the American Association of Cardiovascular and Pulmonary Rehabilitation. J Cardiopulm Rehabil Prev 2007; 27: 121–129.
• 44.   Arena R, Guazzi M, Cahalin LP, Myers J. Revisiting cardiopulmonary exercise testing applications in heart failure: Aligning evidence with clinical practice. Exerc Sport Sci Rev 2014; 42: 153–160.
• 45.   Nakanishi M, Nakao K, Kumasaka L, Arakawa T, Fukui S, Ohara T, et al. Improvement in exercise capacity by exercise training associated with favorable clinical outcomes in advanced heart failure with high B-type natriuretic peptide level. Circ J 2017; 81: 1307–1314.
• 46.   Oremus M, Don-Wauchope A, McKelvie R, Santaguida PL, Hill S, Balion C, et al. BNP and NT-proBNP as prognostic markers in persons with chronic stable heart failure. Heart Fail Rev 2014; 19: 471–505.
• 47.   Malhotra R, Bakken K, D’Elia E, Lewis GD. Cardiopulmonary exercise testing in heart failure. JACC Heart Fail 2016; 4: 607–616.
• 48.   Hynes BJ, Luck JC, Wolbrette DL, Boehmer J, Naccarelli GV. Arrhythmias in patients with heart failure. Curr Treat Options Cardiovasc Med 2002; 4: 467–485.
• 49.   Francis GS. Development of arrhythmias in the patient with congestive heart failure: Pathophysiology, prevalence and prognosis. Am J Cardiol 1986; 57: 3B–7B.
• 50.   Holmes J, Kubo SH, Cody RJ, Kligfield P. Arrhythmias in ischemic and nonischemic dilated cardiomyopathy: Prediction of mortality by ambulatory electrocardiography. Am J Cardiol 1985; 55: 146–151.
• 51.   Luu M, Stevenson WG, Stevenson LW, Baron K, Walden J. Diverse mechanisms of unexpected cardiac arrest in advanced heart failure. Circulation 1989; 80: 1675–1680.
• 52.   Whitman IR, Feldman HI, Deo R. CKD and sudden cardiac death: Epidemiology, mechanisms, and therapeutic approaches. J Am Soc Nephrol 2012; 23: 1929–1939.
• 53.   Gupta S, Figueredo VM. Tachycardia mediated cardiomyopathy: Pathophysiology, mechanisms, clinical features and management. Int J Cardiol 2014; 172: 40–46.