Original Articles |
From the Division of Cardiology (C.C.L., P.K., J.H., D.M.M.), Columbia University, New York, NY; and the Division of Medicine and Therapeutics (C.C.L., T.K.L.), Ninewells Hospital and Medical School, Dundee, United Kingdom.
Correspondence to Donna M. Mancini, MD, Columbia Presbyterian Medical Center, 622 West 168th St, New York, NY 10032. E-mail dmm31{at}columbia.edu
Received April 15, 2008; accepted November 18, 2008.
| Abstract |
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Method and Results— One hundred seventy-one consecutive patients with chronic heart failure underwent symptom limited bicycle exercise with noninvasive estimation of CO using an inert gas rebreathing method. An accurate measure of peak CO was obtained in 148 patients (85% of patients; mean age, 53±14 years; 80% male; left ventricular ejection fraction, 24±12%; ischemic etiology, 34%). Peak cardiac power was derived from the product of the peak mean arterial blood pressure and CO divided by 451. End points consisted of death, urgent heart transplant, or left ventricular assist device implantation. Duration of follow-up averaged 337±252 days (median, 295 days). Univariate and multivariate analysis were performed. The variables analyzed included peak VO2, peak CO, peak cardiac power, VE/VCO2 slope, and VO2 at anaerobic threshold. Event-free survival for the entire cohort was 83% with 5 deaths, 4 left ventricular assist device implants, and 16 urgent transplants. Peak VO2 was 12.9±4.5 mL/kg per min, and peak cardiac power was 1.7±0.9 W. Peak VO2, peak CO, peak cardiac power, VE/VCO2 slope, and VO2 at anaerobic threshold were predictive of outcome on univariate analysis. On multivariate analysis, peak cardiac power and peak CO were predictive of outcome with peak cardiac power being the most powerful independent predictor of outcome (P=0.01).
Conclusions— Peak cardiac power, measured noninvasively, is an independent predictor of outcome that can enhance the prognostic power of peak VO2 in the evaluation of patients with heart failure.
Key Words: chronic heart failure cardiac transplantation peak VO2 cardiac output exercise
| Introduction |
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| Methods |
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Cardiopulmonary Exercise Testing
The method has previously been reported.11 In brief, patients were instructed on the breathing technique and performed at least 1 practice measurement before each test. The Innocor rebreathing system (Copenhagen, Denmark) uses an oxygen enriched mixture of an inert soluble gas (0.5% nitrous oxide) and an inert insoluble gas (0.1% sulfur hexafluoride) from a 4-L prefilled anesthesia bag. Photo-acoustic analyzers measure gas concentrations over a 5-breath interval. Use of sulfur hexafluoride allowed us to measure the volume of the lungs, valve, and rebreathing bag. Nitrous oxide concentration decreases during the rebreathing maneuver, with a rate proportional to pulmonary blood flow. Three to four respiratory cycles were needed to obtain nitrous oxide washout. Absence of pulmonary shunt was defined as arterial oxygen saturation >98% by pulse oximetry. Patients performed a graded maximal bicycle exercise test using a mouthpiece connected to the Innocor breathing system. After 3 minutes of rest data, exercise began at a workload of 0 W and increased every 3 minutes by 25 W until symptom limited maximum. During exercise, tidal volume was progressively increased in the closed circuit to match the physiological increase. Patients were instructed to signal
1 minute before peak exercise. Expired gas analysis was performed continuously throughout the test with the Innocor system. Metabolic measurements were made before and after rebreathing. CO measurements were made at the end of the rest period, at 25 W and at peak exercise. VO2, VCO2, and VE were measured on a breath-by-breath basis. Peak VO2 was defined as the highest value of VO2 achieved in the final 30 s of exercise VO2 at the anaerobic threshold was identified as the nadir of the ventilatory equivalent for VO2. The VE/VCO2 slope was calculated by linear regression fitting of the breath-by-breath values obtained below the anaerobic threshold. Mean arterial pressure was calculated from the standard equation, mean arterial pressure=(systolic pressure+2xdiastolic pressure)/3. Peak cardiac power was derived from the product of the peak mean arterial blood pressure and CO divided by 451.12 A peak pulmonary capillary wedge pressure of 25 mm Hg was imputed based on the median from prior invasive hemodynamic testing.13 Follow-up averaged 337±252 days (median, 295 days) and the end points consisted of death, urgent heart transplant, or left ventricular assisted device (LVAD) implantation.
Statistical Analysis
Categorical data are presented as numbers (percentages) and were compared using the
2 test. Continuous data are presented as means±SD and compared using the Student t test. Differences in cardiopulmonary exercise variables among New York Heart Association (NYHA) functional classes were tested using 1-factorial ANOVA and the t test–based contrast statistics. The effects of known cardiopulmonary exercise testing variables on the outcome were examined using Cox proportional hazards regression analysis. The analysis of the data were performed in two stages. Initially the individual effects of cardiopulmonary exercise testing variables (peak VO2, peak CO, VO2 at anaerobic threshold, VE/VCO2, and peak cardiac power) were examined separately in a series of univariate analysis. Subsequently, the joint effect of the explanatory variables on the time to event was examined in a multivariable analysis. A forward stepwise selection procedure was used to retain only the statistically significant variables. As peak cardiac power was derived from the product of the peak mean arterial blood pressure and CO divided by 451, there is thus a strong correlation (coefficient=0.95, P<0.001) between peak cardiac power and peak CO. This is known as collinearity, and further check on collinearity diagnostics has confirmed this. Therefore, peak cardiac power and peak CO were entered separately into the multivariable model. The best cutoff for peak cardiac power to predict outcome was derived from the receiver operating curve.14 Survival was analyzed using Kaplan–Meier cumulative survival curves and compared using the log-rank test. A probability value
0.05 was considered significant. All analyses were done using SPSS version 12.
| Results |
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| Discussion |
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These findings support the findings of previous studies that have used invasive techniques to derive cardiac work related performance to enhance the discriminatory power of peak VO2 measurement.8,9,12 Griffin et al15 were first to demonstrate that stroke work index at peak exercise dichotomized at 20 gm/m2 identified patients with a 3- to 5-fold higher mortality. Exercise duration and peak VO2 was not able to discriminate survivors from nonsurvivors. This was followed by the study of Roul et al16 who showed that hemodynamic data measured at rest were weak predictors but cardiac power output and stroke work index measured at peak exercise were very strong predictors. Chomsky et al8 in 185 patients with CHF found that the CO response to exercise was the most powerful predictor of survival in this study population according to both univariate and multivariate analyses. Several other investigators demonstrated that left ventricular stroke work and stroke work index were most predictive of survival.12 However, it remained unclear whether the risk of the catheter placement particularly for serial assessment was acceptable given that the data obtained only minimally and indirectly improved risk prognostication.
In 2001, Williams et al17 using noninvasive measurement of CO by CO2 rebreathing integrated with a standard exercise test showed that peak cardiac power was a stronger predictor than peak VO2. Patients with reduced VO2 (ie, peak <14 mL/min per kg) but with a peak cardiac power higher than the identified critical value of 1.96 W had an excellent prognosis with an 89% 4-year survival rate. However, it should be emphasized that Williams et al17 used the CO2 rebreathing method, which has a number of potential problems in the setting of exercise testing in patients with CHF.12 First, the CO2 rebreathing method, unlike the inert gas rebreathing method, requires 2 exercise tests. Second, at the required exercise situation (ie, above anaerobic threshold), lactic acidosis supervenes that will result in a buffering of H+ with the release of CO2 from HCO3–. Acidosis, therefore, has the effect of reducing the total CO2 concentration at a given PaCO2 and the failure to take the pH into consideration could potentially cause an underestimation of CO by up to 50% at high levels of exercise. Finally, a problem with CO2 rebreathing method is that for it to obtain reasonably fast equilibration with mixed venous CO2 it is necessary to add high concentrations of CO2 to the rebreathing mixture. Indeed, it is difficult to choose the right CO2 concentration, and inhaled CO2 occasionally causes discomfort to the patient with a strong feeling of suffocation. Consequently, Cohen-Solal et al18 have come up with the peak circulatory power, derived from the product of peak VO2 and mean arterial pressure as an alternative to peak cardiac power, and have reported that it is an important prognostic indicator in patients with CHF than peak VO2. However, as mentioned earlier, peak VO2 may be influenced by factors other than CO such as muscle deconditioning and obesity.5,6 Therefore, a more reliable noninvasive measure of CO is required. Inert gas rebreathing with continuous analysis of respired gases has recently been shown to be a reliable, safe, and validated method for noninvasive measurements of CO including patients with CHF.10,11 In this study, we have demonstrated for the first time that peak CO and its derived variables determined by this simple and reliable inert gas rebreathing method may enhance the prognostic value of peak VO2 measurement. Thus, the potential indication of this noninvasive tool is to discriminate between patients whose main cause of exercise limitation and low peak VO2 is a poor CO response to exercise and those who are limited by peripheral factors, such as skeletal muscle deconditioning. This tool may therefore be useful in patients with a potential indication to heart transplantation and LVAD implantation and more generally, in patients with advanced chronic HF.
In this study, cardiac power output was found to be the best prognostic indicator. By incorporating both the pressure and flow domains of the cardiovascular system, cardiac power is an intergrated measure of the cardiac hydraulic pumping capacity and it has been argued that it provides a comprehensive indicator of cardiac function.19 Cardiac power has been shown to be powerful predictor of mortality in patients with acute cardiac diseases including cardiogenic shock.20
It should be noted that submaximal measures such as O2 kinetics and ventilatory efficiency, which are not influenced by mechanical work, have been evaluated as prognostic markers. CO and derived variables may also potentially have prognostic value at submaximal exercise loads below the anaerobic threshold. In this study, we found VE/VCO2 slope to be a better predictor of outcome than peak VO2. VE/VCO2 slope >34 had been reported to be a more accurate prognostic index than peak VO2.21 Indeed, Arena et al22 have recently proposed that ventilatory data be used to guide therapy in patients with CHF. However, there is some concern regarding this strategy.23 In this regard, the group at Cleveland Clinic had prospectively analyzed data on 2015 patients, and found that the VE/VCO2 slope was not predictive of survival in patients with CHF.24
Limitations
It should be emphasized that there are a number of limitations with our study. First, our group of patients is somewhat mixed and included patients with mild symptoms and slight impairment of the LVEF. Arguably, these patients do not represent a problem for prognostic stratification. A study limited to a higher risk group might have been more interesting as it would have been important in this group to discriminate whether the low peak VO2 is caused by inadequate cardiac output response to exercise or to physical deconditioning. A second limitation of this study was that there were only a few deaths in this cohort of optimally treated patients with CHF. Third, this was a single center study. Fourth, 13% of patients peak cardiac output measurements could not be made for technical reasons. Other newer noninvasive methods of measuring cardiac output may be more reliable.
Clinical Implications
Do these findings call for the implementation of peak CO and cardiac power determination in the selection of heart transplant candidates? Clearly, the widespread clinical application of noninvasive determination peak CO and peak cardiac power in the evaluation of patients with CHF remains to be determined by a larger multicenter study with a longer follow-up of clinical events to fully determine its prognostic value. These parameters will also need to be compared with other predictive tools such as the Heart Failure Survival Score and Seattle Heart Failure Model.25,26
| Acknowledgments |
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None.
| References |
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2. Mancini DM, Eisen H, Kussmaul W, Mull R, Edmunds LH Jr, Wilson JR. Value of peak exercise oxygen consumption for optimal timing of cardiac transplantation in ambulatory patients with heart failure. Circulation. 1991; 83: 778–786.
3. Costanzo MR, Augustine S, Bourge R, Bristow M, O'Connell JB, Driscoll D, Rose E. Selection and treatment of candidates for heart transplantation. A statement for health professionals from the Committee on Heart Failure and Cardiac Transplantation of the Council on Clinical Cardiology, American Heart Association. Circulation. 1995; 92: 3593–3612.
4. Meiler SE, Ashton JJ, Moeschberger ML, Unverferth DV, Leier CV. An analysis of the determinants of exercise performance in congestive heart failure. Am Heart J. 1987; 113: 1207–1217.[CrossRef][Medline]
5. Wilson JR, Rayos G, Yeoh TK, Gothard P. Dissociation between peak exercise oxygen consumption and hemodynamic dysfunction in potential heart transplant candidates. J Am Coll Cardiol. 1995; 26: 429–435.[Abstract]
6. Becklake MR, Frank H, Dagenais GR, Ostiguy GL, Guzman CA. Influence of age and sex on exercise cardiac output. J Appl Physiol. 1965; 20: 938–947.
7. Stevenson LW, Steimle AE, Fonarow G, Kermani M, Kermani D, Hamilton MA, Moriguchi JD, Walden J, Tillisch JH, Drinkwater DC. Improvement in exercise capacity of candidates awaiting heart transplantation. J Am Coll Cardiol. 1995; 25: 163–170.[Abstract]
8. Chomsky DB, Lang CC, Rayos GH, Shyr Y, Yeoh TK, Pierson RN III, Davis SF, Wilson JR. Hemodynamic exercise testing. A valuable tool in the selection of cardiac transplantation candidates. Circulation. 1996; 94: 3176–3183.
9. Metra M, Faggiano P, D'Aloia A, Nodari S, Gualeni A, Raccagni D, Dei Cas L. Use of cardiopulmonary exercise testing with hemodynamic monitoring in the prognostic assessment of ambulatory patients with chronic heart failure. J Am Coll Cardiol. 1999; 33: 943–950.
10. Agostoni P, Cattadori G, Apostolo A, Contini M, Palermo P, Marenzi G, Wasserman K. Noninvasive measurement of cardiac output during exercise by inert gas rebreathing technique: a new tool for heart failure evaluation. J Am Coll Cardiol. 2005; 46: 1779–1781.
11. Lang CC, Karlin P, Haythe J, Tsao L, Mancini DM. Ease of noninvasive measurement of cardiac output coupled with peak VO2 determination at rest and during exercise in patients with heart failure. Am J Cardiol. 2007; 99: 404–405.[CrossRef][Medline]
12. Lang CC, Agostoni P, Mancini DM. Prognostic significance and measurement of exercise-derived hemodynamic variables in patients with heart failure. J Card Fail. 2007; 13: 672–679.[CrossRef][Medline]
13. Mancini D, Katz S, Donchez L, Aaronson K. Coupling of hemodynamic measurements with oxygen consumption during exercise does not improve risk stratification in patients with heart failure. Circulation. 1996; 94: 2492–2496.
14. Zweig MH, Campbell G. Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clin Chem. 1993; 39: 561–577.
15. Griffin BP, Shah PK, Ferguson J, Rubin SA. Incremental prognostic value of exercise hemodynamic variables in chronic congestive heart failure secondary to coronary artery disease or to dilated cardiomyopathy. Am J Cardiol. 1991; 67: 848–853.[CrossRef][Medline]
16. Roul G, Moulichon ME, Bareiss P, Gries P, Koegler A, Sacrez J, Germain P, Mossard JM, Sacrez A. Prognostic factors of chronic heart failure in NYHA class II or III: value of invasive exercise haemodynamic data. Eur Heart J. 1995; 16: 1387–1398.
17. Williams SG, Cooke GA, Wright DJ, Parsons WJ, Riley RL, Marshall P, Tan LB. Peak exercise cardiac power output; a direct indicator of cardiac function strongly predictive of prognosis in chronic heart failure. Eur Heart J. 2001; 22: 1496–1503.
18. Cohen-Solal A, Tabet JY, Logeart D, Bourgoin P, Tokmakova M, Dahan M. A non-invasively determined surrogate of cardiac power ("circulatory power") at peak exercise is a powerful prognostic factor in chronic heart failure. Eur Heart J. 2002; 23: 806–814.
19. Cotter G, Williams SG, Vered Z, Tan LB. Role of cardiac power in heart failure. Curr Opin Cardiol. 2003; 18: 215–222.[CrossRef][Medline]
20. Fincke R, Hochman JS, Lowe AM, Menon V, Slater JN, Webb JG, LeJemtel TH, Cotter G. Cardiac power is the strongest hemodynamic correlate of mortality in cardiogenic shock: a report from the SHOCK trial registry. J Am Coll Cardiol. 2004; 44: 340–348.
21. Gitt AK, Wasserman K, Kilkowski C, Kleemann T, Kilkowski A, Bangert M, Schneider S, Schwarz A, Senges J. Exercise anaerobic threshold and ventilatory efficiency identify heart failure patients for high risk of early death. Circulation. 2002; 106: 3079–3084.
22. Arena R, Myers J, Abella J, Peberdy MA, Bensimhon D, Chase P, Guazzi M. Development of a ventilatory classification system in patients with heart failure. Circulation. 2007; 115: 2410–2417.
23. Mancini D, LeJemtel TH. Is ventilatory classification preferable to peak oxygen consumption for risk stratification in heart failure? Circulation. 2007; 115: 2376–2378.
24. O'Neill JO, Young JB, Pothier CE, Lauer MS. Peak oxygen consumption as a predictor of death in patients with heart failure receiving beta-blockers. Circulation. 2005; 111: 2313–2318.
25. Aaronson KD, Schwartz JS, Chen TM, Wong KL, Goin JE, Mancini DM. Development and prospective validation of a clinical index to predict survival in ambulatory patients referred for cardiac transplant evaluation. Circulation. 1997; 95: 2660–2667.
26. Levy WC, Mozaffarian D, Linker DT, Sutradhar SC, Anker SD, Cropp AB, Anand I, Maggioni A, Burton P, Sullivan MD, Pitt B, Poole-Wilson PA, Mann DL, Packer M. The Seattle Heart Failure Model: prediction of survival in heart failure. Circulation. 2006; 113: 1424–1433.
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