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Encephalopathy and Stroke After Coronary Artery Bypass Grafting
Incidence, Consequences, and Prediction
Guy M. McKhann, MD;
Maura A. Grega, MSN;
Louis M. Borowicz, Jr, MS;
Michon Bechamps, MHS;
Ola A. Selnes, PhD;
William A. Baumgartner, MD;
Richard M. Royall, PhD
Arch Neurol. 2002;59:1422-1428.
ABSTRACT
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Background In contrast to perioperative stroke, much less attention has been paid
to those with evidence of diffuse brain encephalopathy, presenting as delirium,
confusion, coma, and seizures in the immediate postoperative period.
Objective To determine the incidence, consequences, and predictive factors for
encephalopathy and stroke following coronary artery bypass grafting.
Methods In a prospective evaluation of 2711 patients operated on between January
1, 1997, and December 31, 2000, preoperative risk factors were obtained before
surgery and postoperative outcomes, encephalopathy and stroke, were determined
on a daily basis. All strokes were confirmed by neurologic consultation and,
in most instances, by imaging. Logistic regression analyses were performed
to determine risk factors for these outcomes.
Results The incidence of encephalopathy was 6.9% and of stroke, 2.7%. For patients
without either of these outcomes, the average length of stay in the hospital
was 6.6 days and the mortality was 1.4%. In contrast, patients with encephalopathy
had a length of stay of 15.2 days and a mortality of 7.5%, and those with
stroke, a length of stay of 17.5 days and a mortality of 22.0%. Predictive
models were developed for encephalopathy involving 5 preoperative factors
(age, past stroke, carotid bruit, hypertension, and diabetes) and 1 perioperative
factor (time on cardiopulmonary bypass). The model for stroke involved only
3 preoperative risk factors (past stroke, hypertension, and diabetes).
Conclusions Encephalopathy or stroke is associated with significant increases in
length of stay and mortality after coronary artery bypass grafting. Patients
at higher risk for these outcomes can be identified before surgery.
INTRODUCTION
CONSIDERABLE attention has been paid to the incidence, consequences,
and prediction of stroke associated with coronary artery bypass grafting (CABG).
In contrast, much less attention has been paid to patients with evidence of
diffuse encephalopathy presenting as delirium, confusion, coma, and seizures
in the immediate postoperative period. Only a few studies quantify the risk
of encephalopathy after CABG.1-2
This is somewhat surprising because encephalopathy is more common than stroke
and, as we demonstrate in this study, is also associated with an increased
length of hospital stay (LOS) and a greater mortality. Furthermore, it is
not known whether the presence of postoperative encephalopathy is predictive
of cognitive declines months or years after CABG.3-4
The ability to predict, before surgery, those likely to have encephalopathy
could improve the care of these patients.
In this report, based on the prospective study of 2711 patients undergoing
CABG, we describe the incidence, the immediate consequences in terms of LOS
and mortality, and predictive factors for each of these 2 postoperative outcomes,
encephalopathy and stroke, as well as the aggregate of patients having either
outcome.
PATIENTS AND METHODS
PATIENTS
Between January 1, 1997, and December 31, 2000, 2711 patients underwent
isolated CABG at The Johns Hopkins Medical Institutions, Baltimore, Md. There
were 10 intraoperative deaths, and 2701 patients had data allowing determinations
of postoperative encephalopathy and stroke. Complete information about variables
used in the analysis for encephalopathy was available in 2669 patients and
for stroke in 2668. Patients with concomitant cardiac procedures, such as
valve replacement, repair of a congenital defect, or carotid endarterectomy,
were excluded, as were patients undergoing surgery without a bypass pump.
The study was approved by the institutional review board of The Johns Hopkins
Medical Institutions.
PREOPERATIVE AND OPERATIVE VARIABLES
The following data were collected before surgery by members of the study
team (M.A.G. and L.M.B.): (1) history of a previous stroke, (2) history of
hypertension, (3) history of diabetes mellitus, (4) presence of carotid bruit,
and (5) age. With the use of this information, probabilities of encephalopathy,
stroke, and the aggregate of either were developed. The only operative variable
analyzed was time on cardiopulmonary bypass (CPB). We did not analyze aortic
cross-clamping time as a separate variable, because in our data this variable
was closely associated with CPB.
SURGICAL PROCEDURES, ANESTHESIA, AND PERFUSION
Eight cardiac surgeons were involved in this study. Although there were
some individual variations in technique, most procedures were standardized.
All patients underwent median sternotomy. Anesthetic technique was standardized
and consisted of low- to intermediate-dose narcotics, inhalation agents, and
paralytics. Cardiopulmonary bypass was carried out with nonpulsatile flow
(in most cases), alpha-stat pH blood gas management, antegrade crystalloid
cardioplegia (in most cases) with topical hypothermia, moderate systemic hypothermia
(28°C-32°C), and pump flow rates to achieve a mean arterial pressure
of 60 to 80 mm Hg. The placement of the aortic cross-clamp varied. Some surgeons
used the single clamp technique exclusively, while others used this technique
only in certain clinical situations. This variable was not collected as part
of this study.
OUTCOME VARIABLES
Postoperatively, members of the study team followed up patients in the
cardiac surgery care units daily, in collaboration with the medical and nursing
staff.
LOS and Death
Postoperative LOS referred to the number of days the patient remained
in the hospital after surgery either before discharge or before death. Mortality
was defined as the deaths of patients that occurred during their postoperative
hospital stay.
Encephalopathy
The diagnosis of encephalopathy was made by 2 members of the study team
(M.A.G. and L.M.B.), who were not aware of the patient's risk factors at the
time of evaluation. We included in the encephalopathy group patients having
delirium, coma, or seizures at any time during the postoperative stay, after
the first 24 hours following surgery. Neither the duration nor severity of
encephalopathy was included in the analysis.
The criteria for delirium were similar to those outlined in Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition5 and included any of the following: episodes of confusion,
agitation, and/or combativeness; alterations and fluctuations in levels of
consciousness; acute problems with cognition, including memory; and changes
in perception, including hallucinations. The presence of delirium, coma, or
seizures was documented by the nursing or medical staff, and the documentation
was collected and evaluated daily by study observers.
Stroke
A standard clinical examination was used to determine the presence of
any neurologic deficit. When patients were suspected of having a focal deficit,
a neurology consultation was obtained. Stroke was defined as any persistent
focal neurologic deficit lasting 24 hours or more. All stroke outcomes in
this study were diagnosed by a neurologist and, in most cases, were localized
by imaging studies, either head computed tomography or magnetic resonance
imaging. Of note, in this study the diagnoses of stroke and encephalopathy
were mutually exclusive.
STATISTICAL ANALYSES
Prediction of Encephalopathy
Logistic regression analyses were performed to measure the risk of postoperative
encephalopathy. Two models were developed: one that used only those 5 variables
available preoperatively (age, history of previous stroke, hypertension, diabetes
mellitus, and the presence of a carotid bruit) and a second that used these
5 preoperative variables plus CBP time.
Prediction of Stroke
In the first set of analyses presented herein, a logistic regression
model developed previously for the prediction of stroke using variables available
preoperatively was applied to the current patient population. This previously
derived model included 5 variables (age, history of previous stroke, hypertension,
diabetes mellitus, and the presence of a carotid bruit) that had been selected
from a total of 42 variables (26 demographic and medical history variables
and 16 intraoperative variables) by a series of univariate and multivariate
analyses.
Two stroke risk models were presented in a previously published article,6 one based on the 5 preoperative variables indicated
above and another that included these preoperative variables as well as the
operative variable CPB time. With the use of these 5 preoperative variables
and the CPB time variable, a revised model was created for the new population.
In this analysis, only 3 variables were significant: age, hypertension, and
history of previous stroke. Thus, a simplified model for the prediction of
stroke was developed.
Prediction of Encephalopathy or Stroke
The final logistic regression used the 5 preoperative variables indicated
above for prediction of the aggregate outcome "encephalopathy or stroke."
Time on CPB was also combined with these preoperative variables in a second
analysis for this outcome.
RESULTS
The average age of the patients was 64 years, and the population included
73% men. The incidence of hypertension was 69%; diabetes, 31%; carotid bruit,
10%; and previous stroke, 6%. Encephalopathy occurred in 186 patients in the
population (an incidence of 6.9%), and there were 72 episodes of stroke (an
incidence of 2.7%). Both of these outcomes, as well as the aggregate of those
having either, were associated with longer LOS in the hospital and with greater
mortality than in those without these outcomes (Table 1).
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Table 1. Consequences of Encephalopathy or Stroke
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PREDICTION OF POSTOPERATIVE ENCEPHALOPATHY
When the 5 preoperative variables specified above were used in a logistic
regression to predict the development of post-CABG encephalopathy, all were
significant (Table 2). With these
5 factors, the probability of postoperative encephalopathy for an individual
patient can be calculated, as shown in Figure
1.
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Table 2. Prediction of Encephalopathy*
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Figure 1. Probability of postoperative encephalopathy.
To determine a patient's risk of developing encephalopathy, ask the following
questions and then proceed to the correct part of the flowchart: has the patient
had a previous stroke, yes or no; does the patient have a carotid bruit (CB),
yes or no; does the patient have a diagnosis of hypertension (HTN), yes or
no; does the patient have a diagnosis of diabetes mellitus (DM), yes or no.
Next, determine the patient's age and proceed to the correct row of age groupings
to see the probability for that patient.
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PREDICTION OF STROKE
When preoperative variables were used to predict the presence of stroke
in this current population with the previous model,6
more than twice as many strokes were predicted than actually occurred (161
vs 71). Moreover, this lack of accuracy was not uniform across levels of risk.
In the high-risk group, the model predicted almost 3 times the number of observed
strokes (141 vs 50, respectively). In the low-risk group, the model predicted
fewer strokes than occurred (8 vs 13, respectively). As a result of the unreliable
predictions produced by the model from 1994, we developed a logistic regression
model applying the same 5 risk factors to the current population. Two of the
variables (presence of carotid bruit and history of diabetes) were no longer
significant. Thus, a simpler model, using only 3 variables (age, history of
previous stroke, and history of hypertension), was developed. Table 3 presents the odds ratios, significance levels, and confidence
intervals for the 3 risk factors in this new model. With this simpler model,
the risk of stroke for an individual is indicated in Figure 2.
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Table 3. Stroke Risk Model Based on Current Population*
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Figure 2. Probability of postoperative stroke.
To determine a patient's risk of developing a stroke, ask the following questions
and then proceed to the correct part of the flowchart: has the patient had
a previous stroke, yes or no; does the patient have a diagnosis of hypertension
(HTN), yes or no. Next, determine the patient's age and proceed to the correct
row of age groupings to see the probability for that patient.
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PREDICTION OF ENCEPHALOPATHY OR STROKE
When taken together, 258 patients had either stroke or encephalopathy
(incidence of 9.6%). We therefore examined the ability of the logistic regression
model to predict the development of either stroke or encephalopathy after
CABG. Similar to the model predicting encephalopathy, all 5 preoperative variables
were significant (Table 4). Time
on CPB was also significant for this outcome.
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Table 4. Prediction of Encephalopathy or Stroke*
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ASSOCIATION OF TIME ON CPB WITH ENCEPHALOPATHY AND STROKE
Time on CPB was strongly associated with the prediction of postoperative
encephalopathy (P = .006). As indicated in Table 5, for patients without multiple
risk factors, there was a 50% increase in the probability of encephalopathy
and stroke for each 30 minutes of additional CPB time. For patients with multiple
risk factors, the increase in probability was 30% for each additional 30 minutes
of CPB time.
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Table 5. Risk of Encephalopathy and Effects of Cardiopulmonary Bypass
Time
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In our previous model for prediction of stroke, the only significant
operative variable was time on CPB. When this variable was added to the current
model for the prediction of stroke, the variable was not significant (P = .86). Thus, we did not include bypass time in the current
model for stroke prediction.
COMMENT
In this study we have demonstrated that both postoperative encephalopathy
and stroke are associated with significantly longer LOS and greater mortality.
Mortality after encephalopathy is 5 times that for patients without encephalopathy
or stroke (7.5% vs 1.4%). Postoperative stroke has received considerable attention
in previous studies, and the effect of a stroke on postoperative morbidity
and mortality is well documented, whereas the morbidity and mortality associated
with postoperative encephalopathy are not. This may be due to a tendency to
ascribe this condition to age, anesthesia, fever, infections, medications,
preoperative cognitive status, or a combination of these factors. Our findings
suggest, however, that there are specific characteristics of patients undergoing
CABG that allow one to predict those at risk for encephalopathy: the patient's
age, cerebrovascular status, and time on the bypass pump. Identification of
this subpopulation sets the stage for studying the mechanisms of encephalopathy
after CABG and possible approaches to either prevent or treat this outcome.
PREDICTION OF POSTOPERATIVE ENCEPHALOPATHY
In the prediction of encephalopathy, all 5 preoperative factors (increasing
age, history of stroke, hypertension, diabetes, and the presence of a carotid
bruit) were significant. When these preoperative variables were combined with
time on CPB, there was a relationship between bypass time and the odds in
favor of postoperative encephalopathy. An additional hour on CPB was associated
with an approximate doubling of the probability of postoperative encephalopathy.
These findings are consistent with previous studies that suggested that history
of a stroke and time on CPB are risk factors for encephalopathy.1-2
The relationship between bypass time and encephalopathy may reflect
a longer exposure to anesthesia. On the basis of autopsy studies, however,
longer bypass time is also associated with an increased embolic load, with
a 90% increase in embolic load for each 1-hour increase in bypass time.7 This diffuse showering of embolic material into subcortical
and cortical areas, either by itself or in the setting of variable degrees
of hypoperfusion, may account for the increasing encephalopathy.7-8
Postoperative delirium after noncardiac surgical procedures has been
reported with remarkable variations in incidence (0% to 73.5%).9
However, in recent prospective studies of patients undergoing a variety of
noncardiac surgical procedures, the incidence of delirium ranged from 9% to
11.4%.10-13
The literature regarding encephalopathy is confusing, in part because different
terminology may be used for the same conditions. In some reports patients
with stroke are included in the definition of delirium. Other authors have
reported on these patients by using descriptions such as "neurologic complications,"14 "cognitive disorders,"1
and patients with both coma and stroke.15 In
this report we have considered encephalopathy and stroke as separate outcomes.
In attempting to define factors that could be predictive of postoperative
encephalopathy, we did not analyze a wide range of preoperative and operative
risk factors for postoperative encephalopathy (eg, medical history, physical
findings, operative factors other than bypass time, or postoperative factors)
but instead focused on the risk factors for cardiovascular disease. In addition,
we did not have the data to include 2 cardiovascular risk factors: the arteriosclerotic
state of the aorta, as indicated by transesophageal echocardiography,16 and the patient's preoperative cardiac function.17 A more comprehensive approach might result in a different
predictive model.9
However, in a single hospital setting, the preoperative status, surgical
procedures, anesthesia, and postoperative medications are relatively standardized
for a given patient population. Nevertheless, postoperative encephalopathy
is still a common outcome among the elderly after major surgical procedures
other than CABG.10-13
This suggests that there are factors other than those we have listed that
are important in the determination of which patients will have encephalopathy.
Because cardiovascular risk factors predicted post-CABG encephalopathy, these
factors may also be predictive of postoperative encephalopathy in patients
undergoing other forms of surgery.
PREDICTION OF STROKE
In this study, a model for prediction of stroke after CABG developed
8 to 10 years ago6 was no longer valid. When
applied to a current population, this previous model overpredicted the occurrence
of strokes, particularly in the high-risk group, and underpredicted in the
low-risk group. With the use of a more recent surgical population, a simpler
model that used only 3 variables (increasing age, history of previous stroke,
and hypertension) was highly significant. This finding is in agreement with
those of other studies of predictive factors for stroke.6, 18-23
In all of these studies, including our own, the predictive factors are evidence
of cerebral and/or peripheral vascular disease.
PREDICTION OF STROKE OR ENCEPHALOPATHY
In addition to separate predictive models for stroke and encephalopathy,
a predictive model for an aggregate of these outcomes was developed. This
analysis demonstrated that the same cardiovascular factors, with or without
time on CPB, can be used to predict this aggregate. As discussed in the next
subsection, this aggregate may, at least in part, represent a continuum of
vascular insult to the brain.
MECHANISMS OF ENCEPHALOPATHY AND STROKE
The mechanisms underlying postoperative encephalopathy are not entirely
clear. There are many possible causes, including medications, cardiac failure,
infections, and renal failure.9-10
However, as stated already, in this relatively homogeneous population, medications
were used in a standardized way, and the incidence of infection, renal failure,
and cardiac failure was quite low. Regardless of these possible precipitating
factors, the presence of vascular risk factors predicted postoperative encephalopathy.
Diffusion-weighted imaging (DWI) studies indicate multiple small vascular
lesions in patients after CABG, some of whom have encephalopathy,24 supporting the role of these factors. In patients
with strokes after CABG, DWI also shows numerous small lesions in areas of
the brain that are in addition to those involved in the major ischemic stroke.
Thus, it is possible that, at least in some patients, postoperative encephalopathy
and stroke after CABG represent a continuum of vascular insult to the brain.
On the basis of current data, it is clear that patients with risk factors
for cerebrovascular disease are at greater risk of these outcomes and associated
adverse sequelae, including increased LOS and death.
It has been generally assumed that perioperative stroke is caused by
embolic material deposited in larger vessels.25
This hypothesis has been supported by studies with DWI, which indicates new
areas of ischemia in the postoperative period.24
These areas of new ischemia are often not detectable with conventional magnetic
resonance imaging techniques, because conventional magnetic resonance imaging
cannot readily distinguish between new and preexisting small vascular lesions.
The prevalence of silent infarcts in populations with coronary artery disease
is high, with some studies reporting a 30% rate.26
In candidates for CABG, the prevalence of silent infarcts is likely to be
even higher. One recent study27 from Japan
reported that 50% of patients undergoing CABG had one or more lacunar infarcts
that are shown on their preoperative magnetic resonance images.27
To our knowledge, careful preoperative and postoperative magnetic resonance
imaging and DWI of patients at risk for encephalopathy have not been performed.
The ability to predict outcomes associated with surgery has important
implications. First, the added information available to patients, their families,
and physicians assists with decisions concerning possible therapies. For patients
at higher risk of stroke, interventional cardiology procedures, modification
of existing CABG procedures, and alternative surgical procedures, such as
surgery without a bypass pump, are possible options.
Our studies indicate that postoperative encephalopathy is associated
with increased LOS and mortality. Several studies have indicated that identifying
patients at risk of delirium and instigating specific measures can improve
these outcomes.28-30
Notably, in all of these models the important preoperative factors can be
easily determined by a physician while counseling patients and their families
about surgery, thus permitting more educated decisions.
A second implication is concerned with identifying patients at higher
risk of adverse outcomes so that they could be included in studies of the
effects of neuroprotective agents or practices. For example, with a stroke
rate of 2% to 3% in the overall CABG population, very large numbers of patients
would be required to demonstrate any efficacy, whereas in a population at
greater risk, the predicted stroke rate may be twice as high or more. Including
patients at risk for encephalopathy in such a study would substantially increase
the risks of adverse outcomes and thus reduce the numbers of patients required
to show a definite effect. We base this suggestion on the demonstration that
a predictive model for this combined outcome involves cardiovascular risk
factors. If correct, the probabilities of an adverse outcome reach remarkably
high levels (Figure 3).
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Figure 3. Probability of either postoperative
stroke or encephalopathy. To determine a patient's risk of developing either
stroke or encephalopathy, ask the following questions and then proceed to
the correct part of the flowchart: has the patient had a previous stroke,
yes or no; does the patient have a carotid bruit (CB), yes or no; does the
patient have a diagnosis of hypertension (HTN), yes or no; does the patient
have a diagnosis of diabetes mellitus (DM), yes or no. Next, determine the
patient's age and proceed to the correct row of age groupings to see the probability
for that patient.
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Finally, we strongly suggest that encephalopathy after CABG should not
be considered an inevitable outcome for elderly patients. The consequences
in terms of morbidity and mortality are too high. Careful prospective studies,
including postoperative DWI, are indicated to determine which patients have
encephalopathy related to vascular insults. As is being done with delirium
after other surgical procedures, attempts to understand this phenomenon and
to modify its outcome are warranted.
AUTHOR INFORMATION
Accepted for publication May 2, 2002.
Author contributions: Study
concept and design (Drs McKhann, Selnes, and Royall; Mss Grega and
Bechamps; and Mr Borowicz); acquisition of data (Ms
Grega, Mr Borowicz, and Dr Baumgartner); statistical analysis (Dr Royall); analysis and interpretation of data (Drs McKhann, Selnes, Baumgartner, and Royall; Mss Grega and Bechamps;
and Mr Borowicz); drafting of the manuscript (Drs
McKhann, Selnes, Baumgartner, and Royall; Mss Grega and Bechamps; and Mr Borowicz); critical revision of the manuscript for important intellectual
content (Drs McKhann, Selnes, Baumgartner, and Royall; Mss Grega and
Bechamps; and Mr Borowicz); obtaining funding (Drs
McKhann and Baumgartner); administrative, technical, and
material support (Drs McKhann and Baumgartner); and study supervision (Drs McKhann and Selnes).
This study was supported by grant 5 R01 NS35610-05 from the National
Institutes of Health, Bethesda, Md, and by the Charles A. Dana Foundation,
New York, NY.
We thank Robert Wityk, MD, and Pamela Talalay, PhD, for helpful comments
on analysis, interpretation, and presentation.
Corresponding author and reprints: Guy M. McKhann, MD, Zanvyl Krieger
Mind/Brain Institute, The Johns Hopkins University, 338 Krieger Hall, 3400
N Charles St, Baltimore, MD 21218-2685 (e-mail: Guy.Mckhann{at}jhu.edu).
From the Department of Neurology (Drs McKhann and Selnes), Division
of Cardiac Surgery, Department of Surgery (Ms Grega and Dr Baumgartner), and
Department of Neuroscience (Dr McKhann), Johns Hopkins School of Medicine;
the Zanvyl Krieger Mind/Brain Institute (Dr McKhann and Mr Borowicz); and
the Department of Biostatistics, The Johns Hopkins University Bloomberg School
of Public Health (Dr Royall), The Johns Hopkins University, Baltimore, Md;
and the MD Program, Eastern Virginia Medical School, Norfolk (Ms Bechamps).
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