Reduced peripheral arterial blood flow with preserved cardiac output during submaximal bicycle exercise in elderly heart failure.

BACKGROUND: Older heart failure (HF) patients exhibit exercise intolerance during activities of daily living. We hypothesized that reduced lower extremity blood flow (LBF) due to reduced forward cardiac output would contribute to submaximal exercise intolerance in older HF patients. METHODS AND
RESULTS: Twelve HF patients both with preserved and reduced left ventricular ejection fraction (LVEF) (aged 68 +/- 10 years) without large (aorta) or medium sized (iliac or femoral artery) vessel atherosclerosis, and 13 age and gender matched healthy volunteers underwent a sophisticated battery of assessments including a) peak exercise oxygen consumption (peak VO2), b) physical function, c) cardiovascular magnetic resonance (CMR) submaximal exercise measures of aortic and femoral arterial blood flow, and d) determination of thigh muscle area. Peak VO2 was reduced in HF subjects (14 +/- 3 ml/kg/min) compared to healthy elderly subjects (20 +/- 6 ml/kg/min) (p = 0.01). Four-meter walk speed was 1.35 +/- 0.24 m/sec in healthy elderly verses 0.98 +/- 0.15 m/sec in HF subjects (p < 0.001). After submaximal exercise, the change in superficial femoral LBF was reduced in HF participants (79 +/- 92 ml/min) compared to healthy elderly (222 +/- 108 ml/min; p = 0.002). This occurred even though submaximal stress-induced measures of the flow in the descending aorta (5.0 +/- 1.2 vs. 5.1 +/- 1.3 L/min; p = 0.87), and the stress-resting baseline difference in aortic flow (1.6 +/- 0.8 vs. 1.7 +/- 0.8 L/min; p = 0.75) were similar between the 2 groups. Importantly, the difference in submaximal exercise induced superficial femoral LBF between the 2 groups persisted after accounting for age, gender, body surface area, LVEF, and thigh muscle area (p <or= 0.03).
CONCLUSION: During CMR submaximal bike exercise in the elderly with heart failure, mechanisms other than low cardiac output are responsible for reduced lower extremity blood flow.

Background

Heart failure (HF) patients often exhibit reduced exercise-induced lower extremity blood flow (LBF) that correlates with their severe exercise intolerance[1,2]. The failure of muscle blood flow to increase during maximal exercise in patients with HF has been shown to be mediated in part by reduced maximal exercise-induced cardiac output[2,3]. In the elderly, HF limits many activities of daily living, which are performed during submaximal as opposed to maximal exercise[4]. Understanding the relationship between cardiac output and LBF during submaximal exercise in the elderly would be useful for designing treatment strategies that could preserve the ability of older individuals to perform activities of daily living.

Accordingly, we hypothesized that reduced cardiac output would contribute to reduced superficial femoral arterial LBF during submaximal exercise. To address this hypothesis, we performed cardiovascular magnetic resonance (CMR) in elderly participants in which aorta and superficial femoral arterial blood flow was measured before and after submaximal exercise. In these same participants, we also performed assessments of middle thigh skeletal muscle area, physical function, and peak exercise capacity using expired gas analysis.

Methods

Study Population

The study was approved by the Institutional Review Board of the Wake Forest University School of Medicine, and all participants provided informed consent. The study population consisted of 25 individuals aged 57-82 years: 13 were healthy subjects, and 12 participants had HF. The diagnosis of HF was based on clinical criteria that included: (1) a HF clinical score from National Health and Nutrition Examination Survey-I of ≥ 3,[5] and (2) those utilized previously, including a history of acute pulmonary edema or the occurrence of at least 2 of the following that improved with diuretic therapy without another identifiable cause: dyspnea on exertion, paroxysmal nocturnal dyspnea, orthopnea, bilateral lower extremity edema, or exertional fatigue[5-7]. A range of left ventricular ejection fraction (LVEF) was recruited into the study. The healthy community-dwelling volunteers were aged ≥ 55 years, took no heart failure medications, had no chronic medical disease, had a normal physical examination, had a systolic and diastolic blood pressure below 140 and 90 mmHg, respectively, normal pulmonary function tests, and normal serum chemistries with normal rest and exercise stress echocardiogram.

Participants were ineligible for enrollment into the HF or healthy group if they had; (1) cognitive impairment; (2) alcoholic consumption > 2 drinks/day within the preceding 2 months; (3) current tobacco use; (4) an inability to exercise; (5) any historical, physical exam, or imaging evidence of peripheral or carotid vascular disease; (6) evidence of myocardial ischemia or infarction within 12 months of study participation; (7) a contraindication for CMR scanning (e.g. claustrophobia, pacemakers, defibrillators or other implanted electronic device); (8) a stroke within 6 months; (9) active treatment cancer; (10) anemia (<11 gm hemoglobin), (11) renal insufficiency defined as a serum creatinine >2.5 gm/dl, (12) atherosclerosis within the thoracic aorta, (13) non-contrast CMR angiographic evidence of >30% luminal narrowings in the iliac or femoral arteries, or (14) moderate or severe valvular heart disease.

Study Design

Participants reported in the morning in the post-prandial state after abstention from all caffeine containing products for at least 12 hours. Heart failure participants also withheld medications after midnight. Each participant underwent knee extensor strength tests, a 4-meter walk speed assessment, and a chair rise test. After these tests, they participated in a maximal exercise test (upright position on an electronically braked bicycle, Medical Graphics, Minneapolis, MN) as previously described in which maximal oxygen consumption and anaerobic threshold was determined by expired gas analysis[5]. During this maximal test, the initial workload began at 12.5 watts for 2 minutes, was advanced to 25 watts for 2 minutes and then by 25-watts increments in 3-minute stages thereafter.

Data from the maximal exercise test were used to identify the level of work that was 30% to 50% of the maximum exercise workload (a modification of the protocol developed by Sullivan, et al. [8,9]); this level of activity established the submaximal, or low level workload for use in the CMR stress test in which aorta and superficial femoral artery LBF would be measured. Twenty-four to 48 hours after maximal testing, participants underwent a non-contrast gradient-echo angiogram of the aorta, iliac and superficial femoral arteries, and a submaximal, supine bicycle exercise test on the CMR table. Before and within 60 seconds of exercise cessation, phase contrast measures of ascending and descending thoracic aorta were accomplished. A recovery period of 5 minutes passed, and then repeat exercise and superficial femoral arterial flow were completed according to previously published techniques within 60 minutes of exercise cessation[10]. This technique was utilized so that the time of image acquisition related to exercise cessation would be similar in the aorta and superficial femoral artery. The exercise during CMR was performed on a nonferromagnetic electronically braked bike (Lode, The Netherlands) beginning at 10 watts for 90 seconds (warm-up), increased to 15 watts for 3 minutes, and finally, increased to the submaximal workload as described.

CMR of flow in thoracic aorta and superficial femoral artery

CMR was performed with the use of a 1.5-T, GE Twin Speed Scanner (General Electric Medical Systems, Waukesha, WI). Electrocardiographic monitoring leads and a nonferromagnetic brachial blood pressure cuff (In vivo Monitoring Systems, Orlando, FL) were applied for monitoring heart rate and systemic blood pressure throughout the exam. Phase-array surface coils were applied across the chest and around the leg to maximize signal to noise on the images.

According to previously published techniques,[10] interleaved, phase-contrast gradient-echo sequences were positioned perpendicular to the course of the artery of interest for the purpose of determining cardiac cycle dependent changes in flow. As shown in Figures 1 and 2, the locations for measurement of flow within the arteries of interest were in the axial plane, 4 cm distal to aortic valve level for the ascending thoracic aorta, and 20 cm distal to femoral head for the superficial femoral artery. Measurements in the descending thoracic aorta were obtained from the axial slice, which was used to obtain the ascending aorta flow measurements (Figure 1). Phase-contrast CMR parameters included an 8-mm-thick slice, a 256 × 256 matrix, a 20 cm (for the superficial femoral artery) to 32 cm (for the aorta) field of view (FOV), a 40-degree flip angle, an 13.5-ms repetition time (TR), a 4-ms echo time (TE), and VENC of 150 m/sec. The scan duration was 12 to 15 seconds.

Figure 1

Methodology used to measure flow in the ascending aorta in one of the study patients. At the top, a diagram indicating positioning of slices across the ascending aorta 4 cm distal to aortic valve. At these locations, magnitude images and velocity maps were generated with standard phase-contrast techniques. On velocity map, the gray scale intensity for each pixel encodes for velocity in the range of ± m/sec. For each frame of the cardiac cycle, velocity within the vessel is calculated as the average velocity for all the pixels within the lumen. As shown in the lower portion of the figure, flow is determined by summing the flow measurement (Area × mean velocity) the all of the frames acquired across the cardiac cycle.

Figure 2

Methodologies used to acquire superficial femoral artery blood flow and mid-thigh muscle and fat composition. The location for measurement of flow within the arteries of interest was in the axial plane 20 cm distal to femoral head. The magnified images at the top right demonstrate the cross-section of superficial femoral artery used to measure flow. The images at the bottom demonstrate the mid-thigh cross-sections acquired just distal to the superficial femoral arterial flow images. As shown, color-coded signal thresholding was used to identify fat and skeletal muscle in the middle thigh.

MR of mid thigh cross-sectional area

Upon completion of the flow sequences, multislice axial images were acquired along the length of the femur. Imaging parameters for these acquisitions included double inversion recovery fast spin-echo images with a 7-mm-thick slice, an echo train length of 32, a TR of 2 × the R-wave to R-wave interval, a 650 msec inversion time, a 42 msec TE, a 20 cm FOV, and a 256 × 256 matrix (pixel sizes = 0.78 mm × 0.78 mm). Using the Tomo-Slice software as previously described, the areas of skeletal muscle, adipose, and other (bone, interstitial, vascular) tissue were determined (Figure 2)[11].

All CMR data were analyzed by individuals blinded to patient condition (HF versus healthy), individual components of the CMR exam (thigh muscle area versus flow), or the measures of physical function or exercise capacity. Also, individuals reporting data on physical function exercise capacity were blinded to the results of CMR analyses.

Statistical analysis

Baseline population characteristics of healthy and HF groups were compared using Student's t-test (for continuous variables) or the Chi-square test (for categorical variables). Distributions of the outcome measurements (physical performance, exercise capacity, mid thigh composition and arterial blood flows) were examined, and appropriate transformations were made if necessary. Since superficial femoral LBF is affected by height, BSA, and mid-thigh cross-sectional muscle area, three adjusted versions of superficial femoral LBF were obtained by dividing each factor. Student's t-tests were used to compare the 2 groups (HF and healthy) on these outcomes. In order to adjust for other confounding factors such as age, gender, and LVEF, we also fitted two separate analysis of covariance models to compare superficial femoral arterial blood flow measurements (rest, stress and the difference between rest and stress) between the 2 groups after adjusting for age, gender, or body surface area, height, LVEF, and thigh muscle area, respectively. All tests were two-sided with significance levels of 0.05. All analyses were performed with SAS 9.1 (Cary, NC). All authors had full access to the data and take full responsibility for the integrity of the data, and have read and agree to the manuscript as written.

All authors had full access to the data and take full responsibility for the integrity of the data, and have read and agree to the manuscript as written.

Results

All participants completed the study protocol and their demographic data are displayed in Table 1. Participants with HF displayed a higher incidence of hypertension (67%) and remote myocardial infarction (33%), compared to the healthy older individuals. Elderly HF participants trended toward reduced knee extensor strength (maximum torque 94.5 ± 58.6 vs. 124.5 ± 45.1 Nm; p = 0.18) and delayed chair raise (11.7 ± 2.2 vs. 13.5 ± 1.9 m/sec, p = 0.06), respectively, compared to healthy older individuals. Four-meter walk speed (0.98 ± 0.15 vs. 1.35 ± 0.24 m/sec, p < 0.001) was reduced in elderly HF participants relative to the healthy older individuals, respectively. Heart failure participants demonstrated reduced peak exercise capacity (peak VO2, p = 0.01) compared to healthy subjects (Table 2).

Table 1

Demographic data (mean ± standard deviation)

	Healthy(n = 13)	Heart Failure(n = 12)	p-value
Male, n(%)	6(46%)	6(50%)	0.85
Age (years)	67 ± 5	70 ± 8	0.29
Weight (kg)	76 ± 11	81 ± 14	0.41
Height (cm)	171 ± 10	169 ± 10	0.5
BSA (m2)	1.9 ± 0.2	1.9 ± 0.2	0.64
LVEF(%)	66 ± 7	48 ± 25	0.04*
Diabetes, n(%)	0(0%)	1(8%)	0.48
Hypertension, n (%)	0(0%)	8(67%)	0.001*
Hypercholesterolemia	0(0%)	8(67%)	0.001*
Prior myocardial infarction	0(0%)	4(33%)	0.04*
COPD/Asthma	0(0%)	2(17%)	0.22
Medication, n(%)
Betablocker	0(0%)	8(67%)	<0.001*
ACE inhibitor	0(0%)	6(50%)	0.01*
ARB	0(0%)	2(17%)	0.22
Calcium channel blocker	1(8%)	3(25%)	0.32
Digoxin	0(0%)	2(17%)	0.22
Hydralazine	0(0%)	1(8%)	0.48
Nitrate	0(0%)	2(17%)	0.22
Aspirin/NSAID	9(69%)	6(50%)	0.43
Diuretic	0(0%)	6(50%)	0.01*
Statin	0(0%)	5(42%)	0.01*
Calcium supplement	5(38%)	2(17%)	0.38
Prior hormone replacement therapy	1(8%)	0(0%)	1
Hemoglobin (g/dl)	14.9 ± 1.7	13.1 ± 1.4	0.02*
BNP	20 ± 12	118 ± 132	0.06
Serum sodium level	143 ± 2	142 ± 2	0.61
* = p < 0.05

Abbreviation: ACE = Angiotensin converting enzyme; ARB = Angiotensin II receptor blocker; BMI = Body mass index; BNP = B-Type natriuretic peptide; BSA = Body surface area; BUN = Blood urea nitrogen; COPD = chronic obstructive airway disease; FBS = Fasting blood sugar; LVEF = left ventricular ejection fraction; NSAID = Non-steroid anti-inflammatory drug

Table 2

Maximal (Peak) upright bicycle exercise and gas exchange analysis

	Healthy	Heart Failure	p-value
	mean ± SD	mean ± SD
Peak work load (watts)	97.8 ± 19.1	82.7 ± 22.3	0.002
Peak VO2 (ml/kg/min)	19.8 ± 5.7	13.9 ± 3.2	0.01
Max RER	1.03 ± 0.33	1.04 ± 0.07	0.95
Peak Heart rate	138 ± 28	111 ± 20	0.01
Peak Systolic blood pressure	195 ± 24	156 ± 30	0.01
Peak Diastolic blood pressure	81 ± 9	78 ± 8	0.51
Peak RPP	28295 ± 7412	17842 ± 5616	0.003

Abbreviations: PMHR = percent maximum heart rate (adjusted for age); RER = Respiratory exchange ratio; RPP = rate pressure project; VO2 = oxygen uptake

After submaximal exercise, the change in superficial femoral artery LBF was lower in HF participants (79 ± 92 ml/min) compared to healthy participants (222 ± 108 ml/min; p = 0.002). This occurred even though resting, stress induced, and the stress-rest difference in the descending aortic flow were similar between the 2 groups (Figure 3). Peak VO2 was correlated with peak superficial femoral arterial flow after submaximal exercise (r = 0.67; p = 0.003). The watts achieved during CMR exercise were correlated with peak superficial femoral artery blood flow (r = 0.51; p = 0.01), but not with the stress-rest difference in superficial femoral artery flow (r = -0.34; p = 0.11).

Figure 3

Bar graphs demonstrating rest and submaximal exercise induced measures of arterial blood flow (mean ± standard deviation) in the ascending aorta, descending aorta, and the superficial femoral artery. White bars indicate data from the healthy elderly participants, and gray bars indicate data from the heart failure (HF) elderly participants. As shown, although blood flow in the aorta (ascending and descending portions) augmented with submaximal exercise in both HF and healthy elderly participants, blood flow did not display a commensurate increase in the superficial femoral artery in participants with HF.

To determine if the presence of prior myocardial infarction, diabetes, hypertension, or hypercholesterolemia could have accounted for the differences in flow observed in the superficial femoral artery of our HF and healthy participants, we adjusted our results for the presence of these factors. After these adjustments, submaximal exercise induced difference (stress-rest) in superficial femoral artery LBF persisted between our healthy and HF groups (difference significant at p ≤ 0.05 after including all clinical factors). Also, the similarity between measures of ascending and descending aorta blood flow persisted between HF and healthy elderly participants (p > 0.2 after considering all clinical factors). Since body habitus and particularly thigh muscle size or mass can be different in participants with HF relative to normals, we performed analyses that accounted for body habitus and thigh muscle area. Images of the middle thigh demonstrated trends toward reductions in thigh muscle area and elevations in subcutaneous fat and intermuscular fat in the elderly HF participants versus the healthy participants (0.1