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Anesthesia & Analgesia:
doi: 10.1213/01.ane.0000189614.98906.43
Cardiovascular Anesthesia: Research Report

A Meta-Analytic Comparison of Preoperative Stress Echocardiography and Nuclear Scintigraphy Imaging

Beattie, W Scott MD, PhD, FRCPC; Abdelnaem, Esam MD; Wijeysundera, Duminda N. MD, FRCPC; Buckley, D Norman MD, FRCPC

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Author Information

The Department of Anesthesia and Pain Management University Health Network (Toronto General Hospital), University of Toronto; Department of Anesthesia and Department of Anesthesia, McMaster University, Toronto, Ontario

Supplemental data available at www.anesthesia-analgesia.org.

Accepted for publication August 31, 2005.

Address correspondence to: W. Scott Beattie MD, PhD, FRCPC, R. Fraser Elliot Professor of Cardiac Anesthesia, University Health Network (General Division), Director of Clinical Research and Pre-operative Assessment, 200 Elizabeth Street, 3EN 462, Toronto, Ontario M5G 2C4. Address e-mail to scott.beattie@uhn.on.ca.

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Abstract

In this meta-analysis we compared thallium imaging (TI) and stress echocardiography (SE) in patients at risk for myocardial infarction (MI) scheduled for elective noncardiac surgery. Two searches of published articles were used to identify relevant articles. We included all studies that stated the criteria for a positive test and detailed the frequency of postoperative MI and in-hospital death. Data were abstracted by two authors and captured preoperative patient characteristics, study design, blinding, and outcome adjudication. We defined a positive test as a test with a reversible defect and, where possible, quantified the size of the defects in each study. MI and/or death were the only postoperative outcomes of interest. We calculated the sensitivity, specificity, and likelihood ratio (LR) and, where possible, the Receiver Operating Characteristic (ROC) curve of a cardiac event in each study. The LR and ROC were combined by meta-analyses using the random effects model. Heterogeneity was assessed using the I2 test. The search revealed 68 studies of 10,049 patients. There were 25 SE studies and 50 TI studies. There were 7 studies with a direct comparison of the two methodologies. The quality of studies differed; routine screening for MI was used more frequently in SE studies (47.8% versus 21.2%; P = 0.008) and screening dictated treatment more often after TI (72.1%) than after SE (46.3%) (P = 0.027). The LR for SE was more indicative of a postoperative cardiac event than TI (LR, 4.09; 95% CI, 3.21–6.56 versus 1.83; 1.59–2.10; P = 0.001). This difference was attributable to fewer false-negative SEs. There was no difference in the cumulative ROC curves from qualitative studies (SE, 0.80; 95% CI, 0.76–.84 versus TI, 0.75; 95% CI, 0.70–081). Again, the LR for a negative SE was less (0.23; 95% CI, 0.17–0.32 versus 0.44; 95% CI, 0.36–0.54). A moderate-to-large defect, seen in 14% of patients, by either method predicts a postoperative cardiac event (LR, 8.35; 95% CI, 5.6–12.45). This meta-analysis possesses the statistical power to demonstrate that SE has better negative predicative characteristics than TI. A moderate-to-large perfusion defect by either SE or TI predicts postoperative MI and death. We conclude the SE is superior to TI in predicting postoperative cardiac events.

Preoperative cardiac assessment is designed to identify patients at risk for major cardiovascular complications. Preoperative risk indices (1–3) perform better when coupled with the demonstration of ischemia on a stress test (4). Ergometric preoperative exercise stress testing is limited as a result of disease status (e.g., arthritis, claudication) and/or cardiac status. Pharmacologic tests were developed to avoid these problems. There have been 5 meta-analyses assessing preoperative pharmacologic stress testing (5–9). Two of these analyses are now outdated (5,6). A third meta-analysis was limited to stress testing before transplant surgery (7). A recent comparative meta-analysis evaluated only vascular patients (10) while excluding patients sent to angiography. In the final and eloquent meta-analysis of quantitative thallium imaging (TI), Etchells et al. (8) demonstrated 3 findings: first, large perfusion defects of more than 30% were found to increase risk, although this was only seen in 12% of patients. Second, smaller perfusion defects were not found to confer any added risk. Finally, a negative test did not significantly decrease the probability of a postoperative cardiac event. To restate these findings, the only stress result that changed the overall risk of a cardiac event was the finding of a moderate-to-large perfusion defect. A similar analysis of stress echocardiography (SE) is lacking. It is not clear if there are differences in the accuracy of these tests.

The need for accurate risk assessment of perioperative risk seems obvious. Therapies are not without adverse effects. Beta-blockade has been demonstrated to reduce perioperative cardiac events only in higher risk patients (10) but carries serious side effects (10). Lower risk patients may actually be harmed with therapy (11). Moreover, the Coronary Artery Revascularization Before Elective Major Vascular Surgery trial (CARP) (12) suggests that patients with moderate-to-large perfusion defects may benefit from revascularization. We are now left to determine how to identify those populations that may benefit from interventions. The purpose of this meta-analysis was to assess and compare the reliability of TI with SE in predicting postoperative cardiac events.

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Methods

We designed our search to identify all studies assessing cardiac risk for any type of noncardiac surgery. Separate sensitivity analyses were planned a priori to assess vascular and nonvascular surgery.

We conducted 2 MEDLINE searches (one for TI and the second for SE). First, we searched the terms dipyridamole (exploded) (6319 citations), thallium (exploded) (3761 citations), sestamibi (exploded) (3303 citations), or adenosine (exploded) (3409 citations); these were combined with the OR function (12,973 citations). In a second step we then searched under postoperative complications (26,943 citations) and these 2 searches were combined using the AND function (439 citations) and limited to human studies (381 citations). The cardiac surgery citations were then eliminated, leaving 79 citations. Second, we searched dobutamine (exploded) (4268 citations), adenosine (exploded) (34,090 citations), dipyridamole (exploded) (6319 citations), and these were combined using the OR function for 43,530 citations. We then searched the term echocardiography (exploded) (60,840 citations). These searches were combined using the AND function, resulting in 2143 citations. We then combined this with the postoperative complication search using the AND function for 91 citations. After limiting this search to human studies and eliminating cardiac surgery, we identified 32 citations. The sum of the 2 separate searches left 111 citations. The search was last conducted on March 7, 2005. All 111 articles were then obtained in hard copy and read in full by 2 authors. There was no language restriction used. After identifying relevant studies each bibliography was hand-searched for further articles, then each article was searched in PubMed under “related articles.” To reduce the chance of duplicate inclusion of patients resulting from groups of authors having multiple publications, we recorded the dates of enrollment for each study; where there was overlap, only the study with the largest population was included in the analysis.

Data abstraction initially involved assessment of methodology noting prospective data collection, consecutive patient enrollment, routine screening for postoperative myocardial infarction (MI), selection of patients for coronary angiography, and the number of patients revascularized. Next, we recorded the number of patients with risk factors for coronary disease, history of revascularization, and the use of β-adrenergic antagonists. Third, we abstracted the stress test results: no defect, a fixed defect, a reversible defect, and, where possible, recorded the size of any defects. The results were then correlated to the number of MIs or death in each study. Patients who did not have surgery were excluded from the analysis. Sensitivity and specificity were calculated for each study. The likelihood ratio (LR) was chosen a priori as our primary outcome measure (13). The LR is calculated as follows: LR = Sensitivity/(1 − Specificity).

This equation uses the same parameters describing a receiver operating curve. The Receiver Operating Characteristic (ROC) curve is composed of the LR at differing positive levels of the stress test. A ROC curve provides a common scale for comparing tests even though they measure different parameters and use different units. The prevalence of the target disorder has little influence on the ROC. Finally, the product of pretest probability and LR yields posttest probability of the target disorder. The ROC curve and 95% confidence interval (CI) were calculated for each quantitative study using SAS software (SAS, Cary, NC). The quantitative data included the number of negative tests, the number of tests with baseline abnormalities, a positive test, and the number of tests with moderate-to-large defects and/or 2 or more areas of perfusion defect (13). Two authors (WSB and EA) abstracted the data set. Discrepancies were resolved by discussion and consensus.

The standard principles of meta-analysis were applied to combine studies. In this review we focused on the differences between imaging techniques; we did not subdivide the analysis to consider the stressor (dobutamine, dipyridamole, atropine) separately. A summary ROC (SROC) was calculated for TI and SE, respectively (14,15). All data were entered in REVMAN 4.2 (Cochrane Collaboration), ROC curves from the quantitative studies were combined meta-analytically using the random-effects model (16). Sensitivity analysis was planned a priori for the effect of study quality and in patients having vascular procedures. Heterogeneity, defined as the variation among the results of individual trials beyond that expected by chance, was evaluated using the I2 test (17).

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Results

The results of this meta-analysis represent data from 68 studies in 10,278 patients. Forty-five studies were excluded for the following reasons: 31 publications were clinical management papers lacking new data, 10 were re-publication of previously published series, and in four cases we could not determine a sensitivity or specificity. The PubMed “Related Article Search” and bibliographic search found 2 new studies. There were 25 studies assessing SE (18–42 and 50 reports (31,34,35,37,41–46,46–87) of TI. Seven studies were direct comparisons examining both SE and TI (18,30,31,34,35,37,42). Characteristics of the studies are seen in Table 1. The following aspects of the studies were similar: average number of patients, number of vascular surgeries, number of retrospective studies, and number of blinded studies. Routine screening for MI was more frequent in SE studies (48% versus 21% P = 0.008) whereas results of the test were used to refer to angiography more often in TI studies (71% versus 46%; P = 0.027).

Table 1
Table 1
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The populations are compared in Table 2. The numbers of patients with cardiac disease, diabetes, or history of congestive failure were similar. This analysis found that patients evaluated with SE had more previous coronary revascularization and that twice as many patients were using β-adrenergic antagonists, but these differences did not achieve statistical significance.

Table 2
Table 2
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Comparisons of the outcome data for each stress test are seen in Table 3. The unadjusted MI or death rates were 8.1% for TI and 7.5% for SE. Figure 1 illustrates the SROC and shows the LR of each study in this meta-analysis. A positive SE results in a LR that is 2 times more predictive than a positive TI. SE was found to be superior after the planned sensitivity analysis (Table 3). In post hoc sensitivity analyses we excluded all studies conducted on or before 1995, matched the studies by the year and again the difference was maintained. We also performed a regression analysis of the year of study against both the sensitivity and LR (see online appendix at www.anesthesia-analgesia.org). In the 7 studies, where direct comparisons between SE and TI were made, the difference in LR was not statistically different. However, in this sensitivity analysis the LR for the TI studies was not statistically significant i.e., did not improve the prediction of postoperative MI or death.

Table 3
Table 3
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Figure 1
Figure 1
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There was significant heterogeneity in all these analyses. In an attempt to explain the heterogeneity, 2 separate post hoc analyses were conducted. Heterogeneity was not explained on the basis of the stressor (dobutamine, dipyridamole, or atropine) or the year the study was conducted. We used the more conservative random effects model in all calculations of summary LR.

There were 20 studies (9 SE and 13 TI with 2 common studies) where a ROC curve could be constructed. The cumulative ROC for SE was 0.80 (95% CI, 0.76–0.84) and 0.75 (95% CI, 0.70–0.80; not significant) for TI (Fig. 2). In a further analysis of quantitative SE the LR of a negative SE was a better predictor of an uneventful operation than TI (LR, 0.23; 95% CI, 0.17-0.32 versus 0.44; 95% CI, 0.36–0.54; P < 0.02). The finding of a moderate-to-large abnormality occurred in 16.2% of SE tests and 14.6% of TI tests. These findings were associated with a LR 8.35 (95% CI, 5.6–12.45) with no difference between the two techniques. This evaluation of cumulative ROC again revealed mild heterogeneity. The heterogeneity was no longer significant when we eliminated the 2 studies with ROC more than 0.96 (I2 = 0%).

Figure 2
Figure 2
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The results of stress testing were used, in 37 studies, to refer patients for coronary angiography. The rate of referral to angiography was more than 2 times more frequent in patients screened with TI. The percentage of patients who were revascularized was the same whether they were screened with TI or SE.

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Discussion

This meta-analysis shows SE has better predictive powers compared to TI. The LR of a positive SE was twice that of positive TI. A negative SE reduces the probability of MI or death. Sensitivity analysis confirmed these findings. There were fewer false negative SE results after analysis of vascular patients, including only higher quality studies, and after eliminating all studies conducted before 1996. We also found fewer false negative SEs in the quantitative studies where ROC was calculated. The second major finding of this study revealed, in quantitative screening tests, that a moderate-to-large defect, detected by either SE or TI, is highly predictive of postoperative events.

A negative TI does not reliably reduce the probability of a postoperative cardiac event. This meta-analysis has found that more than one third of the cardiac events occurred in patients with a negative test. This finding has important clinical implications because careful patient selection is required to make safe interventions. Medical therapy is not without significant side effects. Beta-adrenergic antagonists started de novo after cardiac surgery increase length of hospital stay (88). In noncardiac surgery, β-adrenergic blockade increases the need to treat hypotension and bradycardia and may increase the incidence of heart failure (10). In lower risk patients β-adrenergic antagonists may cause harm (11). A finding of a moderate-to-larger defect also has important implications.

The recently completed CARP trial has been used by some to advocate for no preoperative testing. We disagree with this assessment of the results (89). First, many of the patients in the trial did not conform to the current America Heart Association/American College of Cardiology guidelines for testing. Second, the trial did not have the power to assess in-hospital cardiac events. There was a trend toward a 20%–25% reduction in MI. Third, in subgroup analysis, the patients who would most benefit from testing (moderate-to-high risk Eagle criteria and Revised Cardiac Risk Index patients) seemed to benefit from revascularization if a moderate or large defect was demonstrated. Regrettably, this landmark trial was underpowered to demonstrate an effect in this subgroup of patients. The present meta-analysis shows that patients with moderate-to-large defects, by either test, have an almost ninefold increase in the risk of MI or death after noncardiac surgery. In a surgical population with a perioperative MI incidence of 5%, the finding of a moderate perfusion defect carries a 40%–50% chance of a perioperative MI. Based on the CARP trial and this meta-analysis, any patient in our institution with moderate-to-large perfusion defect continues to be referred for coronary angiography. The false negative rate we describe suggests that fewer patients will be missed if SE is used. The results of this meta-analysis extend the findings of Etchells et al. (8) by showing that moderate or multiple defects on SE are at least as accurate as the demonstration of a large perfusion defect on TI. A negative test does not reliably confirm less risk of perioperative cardiac event, although a positive SE is 2 times more predictive than a positive TI. We continue to support the contention that an accurate and quantitative ischemic assessment is required in all moderate-to-high risk patients.

There are important differences in the way these studies were conducted. Postoperative MI is often clinically silent, and many postoperative MIs go undetected. Our finding that routine screening protocols exist more frequently in SE studies would have been expected to inflate the sensitivity measurement of SE. We have attempted to control for this effect by using a sensitivity analysis entering only those trials in either group that used routine screening and blinding. The sensitivity analysis showed that the comparative LRs were not changed and the statistical significance of the differences between the groups was maintained. The sensitivity and specificity of SE and TI may have been artificially changed by postoperative care. It is natural for physicians to alter the care of patients with positive preoperative screening tests to try to diminish postoperative morbidity. Knowledge of increased risk may increase monitoring. A variety of measures are thought to decrease perioperative MI, including β-blockade (90,91), administration of α-adrenergic agonists (92), calcium channel blockers (93), and thoracic epidural analgesia (94). We contend that therapeutic interventions do not explain the results of this meta-analysis. First, in studies that supply these data, we could not detect a difference in perioperative treatment regimens. Second, the rates of preoperative revascularization are similar. Finally, the crude MI and death rates are not different when the 2 study groups are compared.

We have chosen the LR and ROC as our primary outcome measurements. These measures have been used in the last 2 meta-analyses on this subject (8,9). Odds ratios and relative risk have been criticized and can be inaccurate for classifying or predicting risk (13). The LR incorporates elements of both the sensitivity and specificity and expresses the odds that a given level of test result (a perfusion defect or regional wall motion abnormality) would be expected in the target disorder, in this case the odds of a postoperative MI or death.

The shortcomings of meta-analysis are well recognized and we have documented them (92–94). These shortcomings are even more pronounced when evaluating diagnostic testing because a variety of definitions may be used as end-points. We have tried to control for this in our analysis by using a standardized end-point from which to calculate sensitivity and specificity. Several other deficiencies must be addressed.

First, studies in this meta-analysis were conducted over more than 2 decades. In a post hoc sensitivity analysis we could not demonstrate a difference based on the date of study or a change in accuracy over the span of these studies (see online appendix at www.anesthesia-analgesia.org). Second, as was noted by others (8), the general quality of the publications is poor. The sensitivity analyses show that the differential between SE and TI is largest in the studies where blinding was incorporated. The analysis is also limited in that there has been no control of the planned interventions after a positive test. Third, it is possible that the underlying patient characteristics are different. We tried to control for this by evaluating the baseline characteristic where possible, but little information was actually given. The overall morbidities among studies were not different nor was there a difference in the percentage of patients who were revascularized as a result of these investigations. Fourth, we noted a large amount of heterogeneity. Accordingly we used the conservative random effects model. Our attempt to explain the heterogeneity was not successful. We note that there was little heterogeneity in the analysis of quantitative studies. The results of the quantitative studies mirror the finding of the whole study. Finally, the method used to combine the ROC curves uses the inverse of the variance to weight studies. In this case, more weighting is given to studies with an ROC approaching 1. The analysis found 2 TI studies with an ROC of 0.5 and 2 studies with values at 0.6, whereas the lowest SE ROC was 0.73. These low values are underweighted, and this meta-analysis may have minimized the difference between SE and TI studies. A strength of this analysis is the number of studies and the number of subjects evaluated. Funnel plots do not suggest a publication bias. Furthermore, it is unlikely that any missed studies, should they exist, would influence the major findings of this study. Systematic reviews and meta-analysis are best for hypothesis generation but not for testing. To demonstrate a superior negative predictive test, in a randomized controlled trial based on an event rate of 6% and a 25% reduction, more than 10,000 patients would be required. This would necessitate incorporation of a standardized management algorithm for positive study results and a routine screening protocol for perioperative events.

In conclusion, in this meta-analysis we adjusted for the known problems in combining diagnostic tests and used the identical diagnostic criteria for each study. The preoperative risks of both SE and TI appear to be similar. We used several sensitivity analyses; the results show that SE has superior negative predictive ability. Second, moderately large defects, detected by either method, are highly predictive of subsequent postoperative cardiac events. In considering the clinical utility of our analysis, we would suggest that a negative TI should result in little change in perioperative management. All patients with a positive test should be considered at increased risk for an event and managed with maximal medical therapy. Patients with moderately large defects should be referred for angiography. SE, as a screening tool in patients with suspected cardiac disease before noncardiac surgery, has many positive features, including better negative predictive power, and we conclude that it is superior to TI in predicting postoperative cardiac events.

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