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(Circulation. 1996;94:2492-2496.)
© 1996 American Heart Association, Inc.

Articles

Coupling of Hemodynamic Measurements With Oxygen Consumption During Exercise Does Not Improve Risk Stratification in Patients With Heart Failure

Donna Mancini, MD; Stuart Katz, MD; Lisa Donchez, RN; Keith Aaronson, MD

the Division of Circulatory Physiology, Columbia Presbyterian Medical Center, New York, NY.

	Abstract

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Background Measurement of peak O₂ has become an accepted method to select patients for cardiac transplantation. Some investigators have suggested that the addition of exercise hemodynamic measurements can further enhance risk stratification because these measurements may identify patients with a noncardiac limitation to exercise.

Methods and Results Accordingly, we performed maximal bicycle exercise with respiratory gas analysis and hemodynamic measurements in 65 patients (47 men, 18 women) 53±10 years old (mean±SD) who underwent a transplant evaluation at Columbia Presbyterian Medical Center. Skeletal muscle oxygenation of the vastus lateralis during exercise was assessed with near-infrared spectroscopy. Exercise hemodynamic, ventilatory, and muscle oxygenation measurements were obtained in all patients. For each subject, a linear correlation was derived between O₂ and pulmonary artery saturation (PA SaO₂). The slope of this relationship and a theoretical O_2max at a PA SaO₂ of 0% (O₂ intercept) was derived. Baseline measurements were left ventricular ejection fraction, 22±9%; pulmonary capillary wedge pressure (PCWP), 16±10 mm Hg; cardiac index (CI), 2.1±0.5 L·min^-1·m^-2; and PA SaO₂, 53±8%. The cardiac output response to exercise was categorized as normal or abnormal by comparison to the linear equation of peak O₂ versus peak cardiac output as described by Higginbotham. Exercise measurements were peak O₂, 12.1±3.0 mL·kg^-1·min^-1; O₂ intercept, 19.1±5.5 mL·kg^-1·min^-1; PCWP, 31±11 mm Hg; CI, 3.8±1.3 L·min^-1·m^-2; and PA SaO₂, 27±9%. Only 6% of patients exhibited a normal cardiac output response to exercise. Multivariate analysis was performed with peak O₂, O₂ intercept, skeletal muscle oxygenation at end exercise, and peak exercise hemodynamic variables. Only left ventricular stroke work and left ventricular stroke work index were shown to be predictive of survival.

Conclusions Addition of exercise hemodynamic measurements to noninvasive metabolic stress testing minimally improves risk prognostication in patients with severe heart failure.

Key Words: exercise • heart failure • hemodynamics

	Introduction

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The development of objective criteria for the selection of cardiac transplant candidates has gained increasing importance as the referral for cardiac transplantation continues to increase despite a limited donor supply. Cardiac transplantation remains the best option for survival for patients with NYHA functional class IV congestive heart failure who are nonambulatory and/or dependent on inotropic or mechanical support.¹ In the ambulatory patient with heart failure, the decision on when to proceed to listing for cardiac transplantation remains less well defined. We have previously attempted to objectify this process via the measurement of several well-defined prognostic variables, including peak exercise oxygen consumption (O₂).^{1 2} The major limiting factor to exercise performance in patients with heart failure is presumed to be a reduced cardiac output response.^{3 4 5 6 7 8 9} However, peak O₂ is dependent on central hemodynamic factors and peripheral factors. Alterations in peripheral vasodilatory capacity, intrinsic skeletal muscle changes, pulmonary factors, hemoglobin oxygen carrying capacity, age, sex, and conditioning status will all modify O₂.^{10 11 12} In an attempt to differentiate peripheral from central limitations to exercise performance, we used algebraic manipulation of the Fick equation to derive a true maximum O₂ for each patient, ie, an oxygen consumption that assumes total peripheral extraction of oxygen. This variable could provide an indication of the potential cardiac reserve of each patient and thus may provide better risk stratification by identifying those individuals with the most severe cardiac limitation. Accordingly, in the present study, exercise hemodynamic measurements during bicycle exercise were measured in 65 patients referred for cardiac transplant evaluation at Columbia Presbyterian Medical Center. We also used near-infrared spectroscopy to obtain skeletal muscle oxygenation data during exercise. Ventilatory measurements were also recorded. Prospective follow-up of this patient cohort was performed. Multivariate analysis was applied to determine whether any exercise hemodynamic parameter would improve risk stratification.

	Methods

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Subjects
Sixty-five patients participated in the exercise study during a period from July 1, 1994, to December 1, 1995. Forty-seven patients were male and 18 female. The mean (±SD) age was 53±10 years. Twenty-nine percent of patients had NYHA functional class II, 65% had class III, and 6% had class IV heart failure symptomatology. The cause of heart failure was coronary artery disease in 29% of patients, dilated cardiomyopathy in 63%, and end-stage valvular disease in 8%. Left ventricular ejection fraction averaged 22±9%. Peak O₂ averaged 12.1±3.0 mL·kg^-1·min^-1. All patients were receiving treatment with digoxin, diuretics, and vasodilators. Before participation in this study, all patients had performed a prior metabolic stress test as part of their transplant evaluation. All exercise tests were performed on patients receiving a stable medical regimen. Patients who were limited by angina or claudication were not eligible for study.

The protocol was approved by the Committee on Studies Involving Human Beings at Columbia University. Written informed consent was obtained from all subjects.

Exercise Hemodynamic Study
Studies were performed at least 4 hours after meals with the patients on their usual medical regimens. Under local anesthesia, a Swan-Ganz catheter was inserted through the internal jugular vein and positioned in the pulmonary artery. Sixty minutes after instrumentation, the patient arrived in the exercise laboratory. A near-infrared light probe was placed over the vastus lateralis muscle. A pneumatic cuff connected to a rapid cuff inflator was placed on the thigh above the near-infrared probe. The subject then sat on a Monark ergometer and was connected to a Medical Graphics 2001 Metabolic Cart via a disposable pneumotachograph. A pulse oximeter was placed to monitor arterial saturation (Ohmeda). Resting pulmonary artery, pulmonary wedge, and right atrial pressures and respiratory gases were measured, and blood samples were obtained from the pulmonary artery for oxygen saturation and lactate concentration. The transducer was positioned at the level of the fourth intercostal space in the midaxillary line. Arterial blood pressure was assessed by cuff sphygmomanometry. After a 3-minute equilibrium period, the patient began a bicycle exercise test at 0 W. Workload was increased by 25 W every 3 minutes until exhaustion. Respiratory gas, heart rate, and near-infrared measurements were made continuously. Blood sampling, arterial blood pressure, pulse oximetry, and Borg-scale recordings for dyspnea and fatigue were performed during the last 30 seconds of each exercise stage and at peak exercise. Cardiac output determination was performed twice at or near peak exercise. After termination of exercise, the catheter was removed and the patient discharged.

The peak O₂ was defined as the O₂ averaged over the last minute of exercise. The arteriovenous oxygen difference was calculated as (arterial-venous O₂ saturation)x(1.34 mL O₂/g hemoglobin)x(hemoglobin concentration). Arterial O₂ saturation was measured by oximetry (Ohmeda). Hemoglobin concentration was measured by Coulter counter. Pulmonary artery hemoglobin oxygen saturation was determined with an Instrumentation Laboratories 282 Co-Oximeter. Cardiac output was calculated from the Fick equation. Blood for lactate determination was stored at 0°C and assayed with a spectrophotometric technique. Normal values for this technique in our laboratory are <1.6 mmol/mL.

Because O₂ equals the product of cardiac output (CO) and the arterial minus venous O₂ difference (A-V O₂), algebraic manipulation of this equation will yield a linear relationship from which one can derive a true maximum O₂ and a slope that is dependent on the cardiac output response to work.

The slope of this relationship (k) and O_2max0 was derived for each subject. O_2max0 is therefore the O₂ at a pulmonary artery saturation of 0% and thus total extraction of oxygen.

Systemic vascular resistance, pulmonary vascular resistance, cardiac index, left ventricular stroke work, left ventricular stroke work index, stroke volume, stroke index, and mean arterial pressure were derived from standard formulas.

Normal cardiac response to bicycle exercise was determined by use of the regression equation describing the Fick cardiac output versus O₂ in mL/min in 102 normal subjects from the work of Higginbotham et al (Reference 8 and personal communication). This equation was

Patients were defined as having a normal output response if the measured cardiac output was greater than or equal to the above calculated value.

Near-Infrared Spectroscopy
Near-infrared spectroscopic measurements were made with a dual-wave spectrometer (Runman, NIM, Inc), which filtered light at 760 and 850 nm. Light was transmitted to the tissue via one fiber-optic light guide. Reflected light was delivered via a second fiber-optic light guide to a photomultiplier. Changes in muscle oxygenation were expressed relative to the overall change in the signal noted during the reactive hyperemic phase of the protocol, ie, the physiological range. The signal noted at the end of arterial occlusion was presumed to represent near-maximal muscle deoxygenation and therefore was assigned a value of 0% oxygenation. The signal noted after release of the cuff was considered to represent near-maximal oxygenation and therefore was assigned a value of 100% oxygenation. Percent muscle deoxygenation was therefore derived from the measured deflection of the baseline from the maximal oxygenation divided by the physiological range. This was then converted into percent oxygenation.

Patient Follow-up
The majority of patients were followed in the Heart Failure and/or Transplant Clinics of Columbia University. Periodic telephone follow-up of patients cared for primarily by their referring physicians was made every 6 months.

Statistical Analysis
Statistical analysis was performed with t tests, ANOVA, or ² analysis for continuous and noncontinuous variables as appropriate. Cumulative survival curves were constructed by use of Kaplan-Meier survivorship methods. Outcome events were urgent transplantation (UNOS status 1) and death without transplantation. Censoring was performed at the time of elective transplantation (UNOS status 2). Differences between the curves were tested for significance by the log-rank test. Multivariate analyses were performed by Cox proportional-hazards regression modeling. Variables analyzed included all exercise-related parameters.

	Results

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Exercise Testing
The resting and peak exercise data for the entire 65-patient cohort are shown in Table 1. The resting hemodynamic values are consistent with the general profile of transplant recipients. Peak O₂ for the whole group averaged 12.1±3.0 mL·kg^-1·min^-1 (range, 7 to 20.2). The slope of the relation of PA SaO₂ versus O₂ in mL·kg^-1·min^-1 was -0.287±0.106. The O₂ intercept averaged 19.1±5.5 mL·kg^-1·min^-1. Only 4 patients (6% of our cohort) had a normal peak cardiac output response to exercise as calculated from the formula of Higginbotham et al.⁸

View this table: [in this window] [in a new window]   Table 1. Exercise and Rest Metabolic and Hemodynamic Measurements

Peak cardiac output and peak oxygen consumption (mL/min) were linearly correlated (r=.81; P<.0001) and described by the following equation: cardiac output=0.006xO₂+1.38. This equation is similar to that of Higginbotham et al.

Near-Infrared Spectroscopy
Because of technical problems, near-infrared spectra were not obtained in 13 patients. Skeletal muscle oxygenation at end exercise averaged 35±18% (range, 0% to 71%). The variability in the skeletal muscle oxygenation data may represent technical problems versus variability in the activation of the leg muscles (ie, the more superficial muscles that are being sampled by the NIR probe may not be fully activated during low work levels).

Outcomes
Follow-up averaged 232±133 days. During this time period, 6 patients died, 10 patients underwent urgent transplantation, and 7 patients had an elective transplantation. Two additional patients underwent urgent transplantation, but the mechanism for the worsening heart failure was subacute bacterial endocarditis in 1 patient and hyperthyroidism in the other patient; therefore, these transplantations were analyzed as censored observations. Six-month and 1-year survivals for this cohort were 79% and 71%, respectively.

The resting and exercise hemodynamic and metabolic variables were compared between the patients who survived (n=49) and those who died or underwent urgent transplantation (n=16) (Tables 2 and 3). No significant differences were observed in any resting parameter. Peak mean arterial blood pressure was significantly lower in the nonsurvivors. Mean pulmonary artery pressure and pulmonary artery wedge pressure were significantly greater at end exercise in the nonsurvivors. Left ventricular stroke work index tended to be lower, but this did not achieve statistical significance (P=.06). O₂ intercept and slope of the relation of O₂ to PA SaO₂ tended to be higher in the survivors than nonsurvivors, but this did not achieve statistical significance (Figure).

View this table: [in this window] [in a new window]   Table 2. Comparison of Resting Variables of Survivors and Nonsurvivors

View this table: [in this window] [in a new window]   Table 3. Comparison of Exercise Variables of Survivors and Nonsurvivors

View larger version (17K): [in this window] [in a new window]   Figure 1. Mean regression equations of O2 versus pulmonary artery saturation for survivors and nonsurvivors.

Multivariate analysis was performed to determine which of the following exercise variables were most predictive of survival: peak heart rate; mean arterial blood pressure; right atrial, mean pulmonary artery, and pulmonary capillary wedge pressures; pulmonary vascular resistance; systemic vascular resistance; left ventricular stroke work; pulmonary artery saturation; cardiac output; cardiac index; skeletal muscle oxygenation; lactate; peak O₂; the slope of the relation between the PA SaO₂ and O₂; derived maximum cardiac output; derived maximum cardiac index; the O₂ intercept; and left ventricular stroke work index. The results of this multivariate analysis are shown in Table 4. Only left ventricular stroke work and left ventricular stroke work index were found to be predictive of survival.

View this table: [in this window] [in a new window]   Table 4. Results of the Multivariate Analyses

	Discussion

Top Abstract Introduction Methods Results Discussion References

 
Measurement of oxygen consumption in patients with heart failure was first described by Weber et al⁹ as a noninvasive method for characterizing cardiac reserve and functional status in these patients. In his initial study, 40 patients underwent treadmill exercise with hemodynamic and metabolic measurements. Thirty-six of the patients had oxygen consumption measurements <15 mL·kg^-1·min^-1. The remaining 4 patients, with an average ejection fraction of 51%, had a O₂ >15 mL·kg^-1·min^-1. Cardiac index response to exercise expressed as a function of percent maximum O₂ demonstrated differences between patient groups stratified by peak O₂, ie, those patients with a O₂ <10, O₂ between 10 and 15, and O₂ >15 mL·kg^-1·min^-1. A similar analysis on our larger series with bicycle exercise confirms these initial observations. A series of lines are generated with a progressively lower cardiac index as a function of percent O_2max as the O_2max declines. In their original study, Weber et al did not correlate peak cardiac index with peak O₂; subsequently, they and others have demonstrated a significant linear correlation between these two variables.^{3 4} In our study, we did observe a highly significant correlation between peak cardiac output and peak O₂. Thus, in this and other studies there is a significant correlation between the peak O₂ and cardiac output.

However, recent investigators have emphasized that peak exercise performance in patients with heart failure is determined not only by cardiac output response but also by the vasodilator capacity of the vascular smooth muscle, metabolic capacity of skeletal muscle, and pulmonary function.^{10 11 12} Age, sex, activity level, and hemoglobin concentration will also affect exercise performance. Recently, Wilson et al^{13 14} reported that 56% of patients with heart failure had a normal cardiac output response to exercise and that in these patients other peripheral factors are limiting exercise performance. At first analysis, these results appear to be dramatically different from those of the present study. In actuality, the results are only semantically different. The equations to define a normal cardiac output response used in these two studies were different. In the studies by Wilson et al, the equation was derived from several prior reports in the literature that used different exercise protocols and contained few subjects with low cardiac output responses. Additional assumptions were also made, such as normalization of the equation by an average body surface area to derive their formula and generation of confidence intervals. Although Wilson concluded that more than half of his population had a normal cardiac output response to exercise, the peak cardiac output of this patient cohort was only 8.5 L/min. In normal subjects from whom Wilson primarily derived his formula, fewer than 5% had a peak cardiac output in this range. Thus, in terms of absolute cardiac output, the exercise response in patients with heart failure is markedly abnormal, although, as for the normal subjects, it can be described by a similar linear equation. The results of our study indicate a decreased peak cardiac output in the vast majority of patients but also that the slope of the relationship between peak O₂ and peak cardiac output is similar to that of normal subjects.

Since oxygen consumption is the product of the cardiac output and the arteriovenous oxygen difference, the relationship between oxygen consumption and cardiac output should be linear, with the arteriovenous difference describing the slope. Higginbotham et al⁸ described this relationship during bicycle exercise in 102 normal subjects. A similar relation is observed in our patients with heart failure. Indeed, the slopes of the two equations are the same, with the normal and heart failure groups described by different segments of the same line. Deviations from this line are probably due to differences in the arteriovenous oxygen difference, which depends primarily on muscle metabolic function. Moreover, the reduction in cardiac output observed with the use of the Higginbotham formula in our study is probably related to the inaccuracy of the formula. The line describing the relationship between O₂ and cardiac output should begin at the origin and not at a y intercept of 4.45. If this line were forced through the origin, a much larger percentage of our heart failure patients would undoubtedly be described by this equation.

A better paradigm by which to analyze the exercise hemodynamic data may be to construct a linear relationship between oxygen consumption and cardiac output response for each individual patient. With this relationship, one could derive a true maximum oxygen consumption and maximum cardiac output/index. In our study, we correlated oxygen consumption to pulmonary artery saturation in each patient. Using this approach, we were able to demonstrate a trend toward improved prognostication using the O₂ intercept. However, this variable was not statistically significant. Our additional derived variables of O₂ intercept and the slope tended to be lower in nonsurvivors. With study of additional patients and longer patient follow-up, these variables may become significant. It is also important to note that in the multivariate analyses of this small group of patients with a narrower range of oxygen consumption, peak O₂ did not achieve statistical significance. Many other reports have demonstrated the utility of this parameter in predicting survival.^{15 16 17} We recently demonstrated the continuous prognostic nature of this variable by the application of stratum-specific ratios.¹⁸

Previously, Griffin et al¹⁹ had examined the prognostic significance of exercise hemodynamic variables in 49 patients. Multiple logistic regression analysis in that study identified peak exercise stroke work index as the only exercise-derived hemodynamic predictor of mortality. Other investigators quantified cardiovascular reserve by measuring the dP/dt response to catecholamine stimulation. Using this highly invasive technique, they also reported that peak stroke work index and peak left ventricular hydraulic power were predictors of 1-year survival.^{20 21 22} In the comparison of survivors and nonsurvivors in the study by Griffin et al,¹⁹ nonsurvivors had a lower peak exercise stroke work index and higher peak mean pulmonary capillary wedge pressure. The results of our study are similar. During exercise, we also observed that nonsurvivors had significantly greater mean pulmonary pressures and tended to have lower left ventricular stroke work indexes. However, many of the heart failure patients have significant mitral regurgitation; thus, the formula used to calculate left ventricular stroke work is frequently inaccurate in this population. Without simultaneous quantification of the extent of mitral regurgitation, it is difficult to advocate the widespread application of this particular hemodynamic variable.

In our study, we also applied near-infrared spectroscopy to assess skeletal muscle oxygenation during exercise. Near-infrared spectroscopy is a noninvasive technique that relies on the optical properties of oxygenated and deoxygenated hemoglobin.^{23 24 25} Previously, we used this technique to monitor vastus lateralis muscle oxygenation during exercise in both normal and heart failure subjects.²⁴ We have also validated the use of this instrument in humans through a series of experimental protocols.²⁵ Although our mean level of muscle oxygenation was similar to our previous report with this device, in many of the subjects we were surprised at the high level of muscle oxygenation at end exercise. Prior studies have consistently reported markedly reduced femoral venous oxygen saturations at end exercise in these patients. It is unclear whether the variability in our near-infrared measurement was related to technical problems such as inadequate penetration or differences in patients' conditioning status. In 20% of the patients, we were unable to obtain an adequate signal. We are currently modifying our light guide probe to achieve a larger sampling volume.

Study Limitations
This study is limited by the small sample size, the short duration of follow-up, and the nonconsecutive enrollment of subjects. Moreover, serial assessments were not performed. However, the patients enrolled had a prior treadmill exercise test. The medical regimens of all the enrolled subjects were optimized and stable. None of the patients were limited by exertional angina.

Clinical Implications
Exercise capacity in patients with heart failure is associated with a reduced cardiac output response to exercise. Addition of exercise hemodynamic variables minimally improves risk stratification of patients with heart failure. Widespread application of this approach over noninvasive exercise testing with measurement of oxygen consumption does not appear warranted. This approach is not cost-effective and increases risk to the patient.

The results of the study indicate that the addition of exercise hemodynamic data to noninvasive O₂ measurement minimally improves risk stratification and candidate selection for cardiac transplantation.

	Acknowledgments

 
This study was supported by a Grant-in-Aid from the American Heart Association, New York City Affiliation, and by Division of Research Resources, General Clinical Research Centers Program, grant NIH 5-M01-RR-00645.

	Footnotes

 
Reprint requests to Donna M. Mancini, MD, Division of Circulatory Physiology, Department of Medicine, Columbia Presbyterian Medical Center, 622 W 168th St, New York, NY 10032.

Received March 18, 1996; revision received June 11, 1996; accepted June 17, 1996.

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