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(Circulation. 2000;101:1080.)
© 2000 American Heart Association, Inc.
Editorial |
Peak 
O2
A Simple yet Enduring Standard
From the Divisions of Circulatory Physiology and Cardiology, Columbia Presbyterian Medical Center, New York (D.M.); the Albert Einstein College of Medicine, Bronx, New York (T.J.); and the University of Michigan, Ann Arbor (K.A.).
Correspondence to Donna Mancini, MD, 622 West 168th St, Ph-14 West, New York, NY 10032. E-mail dmm31{at}columbia.edu
Key Words: exercise • heart failure • prognosis • transplantation
In this issue of Circulation, Pardaens et
al1 examine the prognostic value of
cardiopulmonary exercise testing in ambulatory patients with
heart failure who are screened for cardiac transplantation. The
investigators failed to demonstrate any significant advantage of
ventilatory data over peak oxygen uptake
(O2). Over the past 10 years,
several investigators have attempted to refine the use of peak
O2 to improve its prognostic
yield. Others have sought methods or equations to estimate peak
O2 from submaximal data, such
as that collected from 6-minute walk tests or during low-level
exercise. Most investigators have concluded that the straightforward
measurement of peak O2
provides the best index of prognosis in patients with ambulatory heart
failure.
The measurement of oxygen consumption
(O2) in patients with heart
failure was first described by Weber et al2 as a
noninvasive method for characterizing cardiac reserve and functional
status in these patients. Its use as a prognostic tool has evolved.
Szlachcic et al3 initially described the prognostic use of
peak O2 in a group of 27
patients. The 1-year mortality rate was 77% for patients with a peak
O2<10 mL ·
kg-1 · min-1 and
21% for those with a peak O2
of 10 to 18 mL · kg-1 ·
min-1. Likoff et al4 reported a
36% mortality rate in 201 patients with heart failure who had a peak
O2
13 mL ·
kg-1 · min-1; the
mortality rate was 15% when peak
O2 exceeded 13 mL ·
kg-1 · min-1.
Exercise data from the first Veterans Administration Heart Failure
Trial (VHeFT)5 also demonstrated that peak
O2 independently predicted
mortality.
To determine whether measuring peak
O2 could help optimally time
cardiac transplantation, we prospectively performed exercise testing
with respiratory gas analysis on all ambulatory patients
referred to the University of Pennsylvania for cardiac transplantation
between October 1986 and December 1989.6 The 116 patients
were divided into 3 groups on the basis of their peak
O2. One group was composed of
patients with a peak O2<14
mL · kg-1 ·
min-1 who were accepted as transplant candidates
(n=35). A second group consisted of patients with a peak
O2>14 mL ·
kg-1 · min-1 who
had transplant deferred (n=52). Patients with a peak
O2<14 mL ·
kg-1 · min-1 but
with a significant comorbidity that precluded transplantation formed a
third group (n=27). Age, left ventricular ejection
fraction, cause of heart failure, and resting
hemodynamic parameters were similar between
the groups. One-year survival was 94% in the patient group with a
O2
14 mL ·
kg-1 · min-1.
Accepted transplant candidates with a
O2<14 mL ·
kg-1 · min-1 had a
1-year survival of 70%, whereas those patients with a significant
comorbidity and reduced O2 had
a 1-year survival of 47%. Patients accepted for cardiac
transplantation had falsely elevated survival because all transplants
were treated as a censored observation. If urgent transplant was
counted as death, 1-year survival fell to 48%. A peak
O2>14 mL ·
kg-1 · min-1
allowed us to identify patients with severe heart failure whose
transplant could be safely deferred. The application of
cardiopulmonary stress testing for the selection of potential
transplant candidates has subsequently gained widespread
acceptance in the United States.7
Peak O2 is affected by age,
sex, muscle mass, and conditioning status; the percent of predicted
peak O2 may yield better risk
stratification than the absolute value.8 Accordingly, peak
O2 was measured in 272
patients with advanced congestive heart failure (CHF) who were
referred for transplant evaluation.8 Predicted
O2 was then calculated for
each patient using the Astrand and Wasserman
equations.8 Patients were then divided into 3
groups on the basis of their peak
O2: <10, 10 to 14, and >14
mL · kg-1 ·
min-1. Strata for percent of predicted peak
O2 were determined by cut
points that would yield strata of similar sizes to the above groups.
Survival curves for patients stratified by absolute and percent of
predicted peak O2 were
similar. Receiver-operating curves were constructed for absolute peak
O2 normalized for body weight
and percentage of predicted peak
O2. The area under the curves
was roughly equal; therefore, normalization of peak exercise
O2 for predicted values added
minimal prognostic information.
In contrast to our study,8 Stelken et
al9 used multivariate analyses in
181 patients; they found that 50% of predicted peak
O2 was the most significant
predictor of cardiac death (P=0.007) and that the area under
the curve for percent of predicted peak
O2 was superior to peak
O2. However, the
prognostic difference between peak
O2 and percent of
predicted peak O2 was
minimal in both studies. Quite frankly, for middle-aged men with severe
heart failure (the stereotypical heart transplant candidate), peak
O2 is just as
prognostically effective as the percent of predicted value. It is only
at the extremes of age and, perhaps, sex that the percent of predicted
peak O2 may provide
additional value.
Peak O2 is a continuous rather
than a discrete variable, and differences in the above 2 studies
may be explained by the fact that both groups attempted to assign a
threshold or cut-off value to determine transplant candidacy.
Stratum-specific likelihood ratios can be used to identify threshold
values. Therefore, we calculated stratum-specific likelihood ratios in
140 ambulatory patients referred for cardiac transplant
evaluation.10 The ratios progressively increased as peak
O2 increased, but no discrete
cut point was identified. Therefore, these stratum-specific likelihood
ratios indicate that peak O2
is a strong and continuous predictor of survival in this population and
that it does not have an absolute threshold.
In a further attempt to enhance the predictive power of peak
exercise O2, investigators
have coupled hemodynamic monitoring with oxygen
consumption measurements. Chomsky et al11 evaluated the
cardiopulmonary and hemodynamic exercise
responses of 185 ambulatory patients with CHF and a mean peak
O2 of 12.9 mL ·
kg-1 · min-1 who
were referred for transplant evaluation. They used the following
formula to define a normal cardiac output response to exercise: cardiac
output=5xO2 (in L/min)+3
L/min. On the basis of this formula, these investigators divided their
cohort into normal and reduced cardiac output groups.
Multivariate analyses found that both a peak
O2<10 mL ·
kg-1 · min-1 and a
reduced cardiac output response to exercise, as defined by the above
equation, were predictive of poor 1-year survival. Whether a
straightforward multivariate analysis using
directly measured values would have yielded similar findings is
unclear. Moreover, the application of invasive
hemodynamic monitoring with ventilatory measurements
greatly increases the complexity, expense, and potential risks of
exercise testing in this population.10
We also investigated whether exercise hemodynamic
measurements rather than peak
O2 alone could better identify
patients at increased mortality risk.12 A total of
65 patients underwent bicycle exercise testing with
simultaneous metabolic and
hemodynamic measurements. Results of
multivariate analysis demonstrated that the
only exercise variable predictive of survival was left
ventricular stroke work index. These results were
consistent with those of Griffin et al13 ; they
used multiple logistic regression analyses and identified peak
exercise stroke work index as the only exercise-derived
hemodynamic predictor of mortality. To be accurate, the
derivation of peak exercise stroke work requires the absence of mitral
regurgitation. Many of our patients with end-stage
heart failure have severe mitral regurgitation, which
makes the accuracy of this finding questionable.
Most studies fail to demonstrate improved risk stratification with the
measurement of exercise hemodynamics beyond the direct
measurement of peak O2. This
is not surprising; the limitations to maximal exercise
performance in CHF patients are a mix of both central and
peripheral factors. Indeed, the value of peak
O2 rests in the fact that this
measurement integrates elements of cardiac reserve, skeletal muscle,
pulmonary, and endothelial dysfunction more
than other, traditional prognostic markers in patients with severe
heart failure.
Osado et al14 attempted to further stratify the high-risk
group of patients with a peak
O2<14 mL ·
kg-1 · min-1 by
performing multivariate analyses using all
noninvasive exercise parameters measured during exercise
testing. Cardiopulmonary exercise testing was performed in 500
patients with CHF who were referred for heart transplantation; 154
patients (31%) had a peak exercise
O214 mL ·
kg-1 · min-1.
Multivariate analyses of exercise and
cardiopulmonary variables (ie, peak exercise heart rate,
systolic blood pressure, respiratory exchange ratio, minute
ventilation, peak O2, percent
predicted peak O2, and
anaerobic threshold) were performed to identify the 3-year
prognostic risk. Peak systolic blood pressure <120 mm Hg
(P=0.0005) and percent predicted peak
O250%
(P=0.04) were significant prognostic variables in
patients with a peak
O214 mL ·
kg-1 · min-1.
Survival was 55% at 3 years for the patients with a peak exercise
O214 mL ·
kg-1 · min-1 and a
peak exercise systolic blood pressure <120 mm Hg; it was
83% in the patients with a systolic blood pressure
120 mm Hg (P=0.004).
Other investigators, such as Chua et al,15 examined the
clinical and prognostic significance of the ventilatory response to
exercise in patients with stable, severe, chronic heart failure. During
exercise, a close linear relationship is observed between carbon
dioxide production and minute ventilation until the ventilatory
threshold is reached, then the slope of this relationship increases.
Patients with a steeper ventilatory response have reduced cardiac
output during exercise, increased pulmonary pressures, an
increased dead space/tidal volume ratio, and potentially augmented
chemoreceptor sensitivity. In their analysis of 173 patients,
Chua et al15 found that the ventilatory response to
exercise did seem to add prognostic information above that provided by
peak O2 alone. This study is
in contrast to the current study of Pardaens et al.1 The
major differences in these studies illustrate the problem with
analyzing all the ancillary data collected during
O2 testing: the interpretation
depends on how you choose to analyze the data. Chua et
al15 used all the data from the start to the end of
exercise to derive the ventilatory equivalent for
CO2, whereas Pardaens et al1 used
the first 6 minutes of exercise. It does make teleologic sense that the
peak O2, which more fully
reflects the pathophysiologic limitations seen in heart failure, should
be a superior prognostic factor than the more focused ventilatory data.
Use of submaximal exercise data may be helpful, however, in those
patients unable to perform maximal exercise.
One can argue that peak O2 is
somewhat dependent on patient motivation as well as investigator
analysis, but this is less true if the patient reaches a
respiratory quotient above 1 and/or the ventilatory threshold. As in
most life circumstances, the simpler the approach, the more direct the
measurement, and the less manipulation, the better.
Although peak O2 is an
excellent isolated predictor of outcome, its value can be enhanced by
combining it with other important and easily obtainable clinical
characteristics. Although peak
O2 is a useful predictor of
prognosis, it should be viewed in the context of the whole clinical
presentation. Pretransplant risk stratification was
improved by developing a predictive model that incorporated multiple
independent predictors of mortality. We developed a Heart Failure
Survival Score (HFSS) from 467 ambulatory patients with severe CHF who
were followed at 2 institutions from July 1986 to September
1994.16 The model was developed using 268 patients from
the University of Pennsylvania hospital who were followed from July
1986 to January 1993, and it was validated in a group of 199 patients
at Columbia Presbyterian Hospital who were followed from July 1993 to
October 1995.
In this model, 80 clinical variables for each patient that were derived from clinical history, physical examination, and laboratory, exercise, and catheterization data were entered into the data set. Univariate survival analyses were performed using Kaplan Meier analyses. Significant univariate factors were then analyzed with multivariate techniques. Variables were grouped, and those prognostic factors thought to represent different aspects of CHF were incorporated into the model. In the construction of the model, we used clinical judgment to guide the selection process. We specifically sought to include variables that reflect multiple aspects of the pathophysiology of heart failure and that rely minimally on investigator or patient interpretation. The model with the smallest number of variables that could most accurately predict survival was derived.
One statistical model, HFSS, only incorporated noninvasive
parameters, including the following 7 variables and
their pathophysiological constructs: presence or
absence of coronary artery disease (myocardial
ischemia), resting heart rate (activation of sympathetic
nervous system), left ventricular ejection fraction (the
degree of systolic dysfunction), mean arterial
blood pressure, presence or absence of
intraventricular conduction defect on baseline ECG
(the extent of myocardial fibrosis), serum sodium (the degree of
activation of the renin angiotensin system), and peak
O2. To calculate a prognostic
score, the value of the variable and the ß-coefficient from the
Cox model are multiplied, the products are added, and the absolute
value is taken as the HFSS. For noncontinuous variables (ie,
coronary artery disease or intraventricular
conduction defects), scoring is based on their presence or absence;
presence is assigned a value of 1, and absence a value of 0.
Model discrimination was excellent. Stratum-specific likelihood ratios revealed 3 distinct groups in the derivation data set. Patients with prognostic scores >8.1 have excellent survival and do not require transplant listing. Medium-risk (HFSS=7.2 to 8.1) and high-risk (HFSS<7.2) patients have a sufficient mortality risk to warrant transplant listing. Similar survival curves could be generated in the validation sample using the same cut points. Thus, the application of this statistical model, which incorporates several prognostic factors, can help risk-stratify patients more effectively.
Is peak O2 by itself as
effective as HFSS in predicting outcome? In the model-derivation
sample, peak O2 did perform as
well as the model; however, this was not true in the validation
sample.
Is the HFSS the best model for predicting survival in patients with heart failure? Presently, no other multivariate models have been validated prospectively. Whether this score is applicable in the era of ß-blockade has not been firmly established.
In conclusion, peak O2
is probably the best single measure of prognosis in ambulatory patients
with severe heart failure, but risk stratification can be enhanced by
using a model that encompasses a variety of prognostic markers,
including peak O2.
Footnotes
The opinions expressed in this editorial are not necessarily those of the editors or of the American Heart Association.
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