Goldman and colleagues13 established a multivariable model of cardiac risk for noncardiac surgery, later named the original Cardiac Risk Index, which dramatically improved the prior American Society of Anesthesiologists (ASA) classification.14 There have been other models developed to assess risk for perioperative complications emphasizing different aspects. All use clinical assessment, medical history, and a few basic laboratory assessments and now serve as a routine component of preoperative screening.
Original Cardiac Risk Index
In their original study, Goldman and colleagues13enrolled 1001 patients 40 years or older undergoing major noncardiac surgery. They derived a multivariable model using 9 clinical signs and standard laboratory measurements to generate a weighted cardiac index with 4 classifications predicting cardiac risk independent of surgery.13 This served as the basis for many years for most physicians assessing preoperative risk. However, limitations such as lack of model validation, unknown interobserver variability, and expectation bias due to event classification by investigators led to the development of other risk indices.
Modified Cardiac Risk Index
The next major development arose from a study of 455 consecutive patients referred to a general medical consultation service.15 Detsky and colleagues15 found an area under the receiver operator characteristic (ROC) curve of 0.69 for the original Cardiac Risk Index, which was lower than that in the original study by Goldman and colleagues.13 They simplified the point system, added angina severity, and modified the criteria for HF, providing an improved c-index of 0.76. While the efforts of Detsky and colleagues15 were a substantial improvement, there were concerns of referral bias given that surgeons or anesthesiologists had to ask for a medical consultation. Overall, the main limitations were the single institution design, lack of end point adjudication, and the limits of generalizability of the risk index to "real-world" consultation.
Revised Cardiac Risk Index
In an effort to further improve available risk stratification tests, Lee and colleagues16 proposed an even easier risk stratification tool composed of 6 simple factors derived from the largest study cohort to date—4315 patients 50 years or older identified through the hospital's Preadmission Test Center or in the hospital (Table 1) and (Table 2). Through this mass screening process, approximately 80% of patients undergoing major noncardiac surgery were approached for enrollment into the study. Major cardiac complications were seen in 2% of patients in the derivation cohort and 2.5% in the validation cohort. Independent predictors of risk in this cohort were high-risk type of surgery (intraperitoneal, intrathoracic, or suprainguinal vascular), history of ischemic heart disease, history of HF, history of cerebrovascular disease, preoperative treatment with insulin, and preoperative serum creatinine level greater than 2.0 mg/dL (>176.8 µmol/L). The area under the ROC curve for this model was 0.806 in the validation cohort, compared with 0.582 for the Modified Cardiac Risk Index, 0.701 for the original Cardiac Risk Index, and 0.706 for ASA class.
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Table 1. Revised Cardiac Risk Index
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Table 2. Major Cardiac Complication Rates Using the Revised Cardiac Risk Index
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Overall, this simplified approach effectively grouped patients into 3 groups. What to do for low-risk patients is straightforward, but those classified as intermediate or high risk still require clinical judgment for the best approach. The investigators used an improved study design by having study personnel who did not participate in subjects' care perform daily medical review to collect data, and a reviewer blinded to preoperative clinical data classified all postoperative outcomes. Of note, possibly related to the smaller size of the validation cohort, was that insulin therapy and preoperative serum creatinine level did not prove to be as important in the validation phase. Another limitation is that the model cannot take into account changes in a patient's clinical status over time. For example, if a patient has decompensated HF today, the physician delays surgery for 1 month, and the patient clinically improves, the patient's calculated risk remains the same, which may or may not reflect reality. The same applies to a patient with a recent acute coronary syndrome who has surgery delayed for months after coronary revascularization.
HF AND NONCARDIAC SURGERY
Role of HF in Risk Indices
In the original Cardiac Risk Index by Goldman and colleagues,13 clinical signs of HF including an S3 gallop or jugular venous distention (JVD) were the most significant predictors of postoperative life-threatening or fatal cardiac complications. In the final analysis, signs of HF carried the highest weight in the original Cardiac Risk Index. In addition, 36 of the 39 patients manifesting 1 or more life-threatening cardiac complications had pulmonary edema (Table 3).
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Table 3. Event Comparison of Different Cardiac Risk Indices*
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Owing to the diverse group of clinicians evaluating numerous patients, in actual practice, the prior assessment for HF soon was recognized to be impractical. In the study by Detsky and colleagues,15 the interobserver agreement for S3 and JVD was poor (
statistic, 0.42 and 0.50, respectively). Therefore, to make the diagnosis of HF more objective and reproducible preoperatively, Detsky and colleagues grouped HF into 2 categories as the presence of alveolar pulmonary edema within 1 week or ever. Although the definition was stricter, HF still had a major role in predicting events as well as being a major outcome. Of the 43 serious events, there were 10 new or worsened episodes of HF without alveolar pulmonary edema, and 5 episodes of alveolar pulmonary edema.15
In the Revised Cardiac Risk Index study population, HF was both an important predictor and a key complication. The outcome required a formal reading of pulmonary edema on the chest radiograph by a radiologist with a plausible clinical setting. In the validation set, it provided the highest odds ratio (4.3) for major cardiac complications. In addition, it was an important outcome similar to MIs.16 Other models have shown HF as an important predictor of perioperative events and the degree of HF appears to correlate with complications.17
Diagnosis of HF in Risk Indices
Despite use of the standard Framingham criteria for HF in a number of large epidemiological studies, investigators have not clearly applied these same standard definitions in preoperative risk studies.18-19 Table 4 summarizes the definitions of HF that have been used in the major preoperative risk studies.
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Table 4. Heart Failure (HF) Evaluation Definitions of the Different Cardiac Risk Indices
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Preoperative assessment of HF has shifted from emphasizing physical examination signs to simply having a history of HF. In doing so, problems of interobserver variability and reproducibility in general application were reduced. In the Revised Cardiac Risk Index, the investigators defined HF by a combination of symptoms and signs that incorporated some of the Framingham criteria, but important elements were still missing such as orthopnea and dyspnea on exertion that are now recommended by the American College of Cardiology/American Heart Association (ACC/AHA) guidelines for the definition of HF.16, 18, 20
The studies required a postoperative chest radiograph for confirmation of HF, which helped standardize the diagnosis.13, 15-16 However, all of the studies depended on the primary provider to order chest radiographs since it was not done routinely in the postoperative period, causing end points to be missed. For most of the studies, a single reviewer classified events rather than a central events classification committee.13, 15-17,21-22
Over the last several years, numerous studies have highlighted the importance of natriuretic peptides as diagnostic and prognostic markers in HF.23-26 With the recent approval of commercial assays for B-type natriuretic peptide and N-terminal pro–B-type natriuretic peptide, it may be possible to improve both preoperative classification of HF and diagnosis of HF as a postoperative complication by incorporating the markers in routine assessment. Further studies will be needed to assess the utility of such a strategy.
Echocardiography
Although echocardiography appears to be very accessible and potentially useful test for preoperative evaluation, it has limited prognostic value as a routine test. To help determine the value of routine echocardiography in preoperative screening, Halm et al27 evaluated 339 of 474 consecutive men in a Veterans Affairs medical center with known or suspected CAD. In this study, 8% of patients had HF and 3% had ischemic events postoperatively. Although an ejection fraction less than 40% and wall motion score were associated with some outcomes, both had poor predictor characteristics.
In a more recent study, Rohde and colleauges28 evaluated 570 patients enrolled in the Revised Cardiac Risk Index cohort who underwent transthoracic echocardiography at the discretion of their physician within 3 months of surgery. Overall, models including the reported echocardiographic data predicted major cardiac complications better than models with only clinical variables (c-statistic, 0.73 vs 0.68; P<.05). An abnormal echocardiogram with any degree of systolic dysfunction, moderate to severe left ventricle (LV) hypertrophy, moderate to severe mitral regurgitation, or aortic gradient of 20 mm Hg or greater provided a sensitivity of 80%, specificity of 52%, positive predictive value of 12%, and negative predictive value of 97%. However, severe LV dysfunction compared with mild to moderate LV dysfunction did not have as strong an association with cardiogenic pulmonary edema and MI. The heterogeneity of these findings likely points out that HF and ischemic heart disease comprise a combination of factors that change every day, while we usually only measure a few at 1 point in time. Therefore, in the end, adding echocardiography added little to risk models.
Preoperative Stress Imaging and HF
A number of studies have evaluated stress imaging in preoperative risk assessment; the largest experience using dipyridamole thallium-201 imaging.29 Eagle and colleagues21 used a combination of clinical and thallium data for preoperative assessment in patients with vascular disease. The latest study from his group used a model incorporating the clinical variables of advanced age (>70 years), angina, history of MI, diabetes mellitus, history of HF, and prior coronary revascularization.22 Importantly, even in that study that emphasized ischemic heart disease, HF was an important predictor of the primary outcome (nonfatal MI, fatal MI, or cardiac death) in the training set and validation set with odds ratios of 2.7 and 3.2, respectively. Although thallium scoring correlated with events, the results showed that only the intermediate-risk group based on clinical assessment benefited from further testing to stratify patients into low- and high-risk categories.
As observed by Eagle and colleagues,21 HF played a major role as a clinical predictor in other studies evaluating perfusion imaging. In a meta-analysis combining 5 studies using thallium imaging for preoperative risk assessment in 1188 patients, HF was the second most important predictor of cardiac events behind reversible thallium defect (odds ratio, 3.6; P<.001).29
Risk Factors for Postoperative HF
With today's current approach to preoperative care, it is unclear what the risk factors for postoperative HF are. In a 1990 study by Mangano and colleagues,30 a history of dysrhythmia, diabetes, duration of anesthesia, vascular surgery, and narcotic anesthesia were all associated with postoperative HF while postoperative ischemia was not. They speculated that vascular surgery placed patients at higher risk because of the length of the procedure and volume of intravenous fluids. In another study, Charlson and colleagues31 found that the risk for postoperative HF was limited to patients with preoperative symptomatic cardiac disease, especially in patients with diabetes. Another possible factor in postoperative HF may be the inability to administer some HF medications because of the inability to use an oral route postoperatively. Finally, it appears that surgery leads to activation of the renin-angiotensin system and postoperative elevations in cortisol as well as epinephrine levels.32
Timing of HF Perioperatively
Manifestations of perioperative HF usually develop during the day of surgery or the second to third postoperative day, although this is not well studied.31 Theoretically, there are 2 potential periods when HF may worsen: (1) immediately after surgery because of the length of surgery, myocardial ischemia, and rapid fluid shifts and (2) a few days later, when HF may occur because of reabsorption of third-spaced fluid.33 In the study by Mangano and colleaugues,30 48% of HF occurred after the third postoperative day.
Perioperative Care
The exact approach to patients with HF in the perioperative period is uncertain, but understanding the degree and cause may be helpful. The ACC/AHA guidelines state, "Every effort must be made to detect unsuspected HF by a careful history and physical examination."34
The mainstay of perioperative care is to identify patients with intermediate to high risk features and either perform preoperative evaluation with noninvasive testing followed by revascularization or use perioperative 
-blockers (Table 5). There are no randomized controlled trials indicating the effect of revascularization preoperatively, and previous observational studies provide a mixed picture.35-40 Until a large randomized trial is done, the benefit of revascularization remains to be definitively proven for prevention of perioperative cardiac events.
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Table 5. Tests and Strategies for Managing Patients With Heart Failure (HF) in the Perioperative Setting
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Randomized controlled trials support -blocker therapy perioperatively, but there have only been 30 patients with HF in these trials.41-45 The first major trial using atenolol in 200 patients with CAD or at risk for CAD showed a reduction in deaths and combined cardiovascular outcomes.45 However, the benefit was not apparent until after discharge and was largely seen during the first 6 to 8 months after surgery, although the protocol only stipulated therapy during hospitalization.
The Dutch Echocardiographic Cardiac Risk Evaluation Applying Stress Echocardiography (DECREASE) study also supports the merits of perioperative -blocker therapy.44 Of the 846 patients screened with dobutamine echocardiography, 112 with positive test results were ultimately randomized to perioperative treatment with bisoprolol or standard care. The primary end point of death from cardiac causes or nonfatal MI was significantly different between the randomized groups; 2 patients (3.4%) in the bisoprolol group compared with 18 patients (34%) in the standard care group (P<.001) experienced the primary end point. Of note, 8 patients with extensive wall-motion abnormalities either at rest or during stress testing were excluded. If the Revised Clinical Risk Index is considered, dobutamine stress echocardiography only adds significant prognostic information for patients with 3 or more risk factors.46 Thus, in most patients who have fewer than 3 risk factors, use of perioperative -blockade without having to undergo substantial testing appears reasonable.47 However, the study was limited in describing an approach for patients with HF since it only had 14 patients with HF and HF was not an outcome.
One issue that arises in surgical patients that may be particularly important for patients with HF is how to administer their medications appropriately if patients are not able to take anything orally. Clinicians use intravenous medications such as -blockers in the perioperative period, but timing or duration is uncertain in patients with worsening HF, given the small number of patients in clinical trials. Moreover, the pharmacodynamics of intravenous medications may not be as well appreciated by clinicians compared with the more routinely used oral agents.
Intraoperative Monitoring
For patients with HF, some investigators recommend right heart catheterization (RHC) in the perioperative period depending on the clinical situation.48-49 Intraoperative hemodynamic changes are associated with increased complication rates, so logically most would assume invasive monitoring would reduce perioperative complications.50
In an observational cohort study of 4059 patients who underwent major noncardiac surgery (excluding abdominal aortic aneurysm repair), the value of RHC was underwhelming. Over 200 patients had an RHC, with an overall 3-fold increase in the incidence of major postoperative cardiac events and an adjusted odds ratio of 2.0 for postoperative major cardiac events.51
In the most recent study evaluating RHC, investigators showed no benefit for perioperative RHC in a randomized controlled trial of elderly patients undergoing major noncardiac surgery.52 Almost 2000 patients 60 years or older with ASA's class III-IV scheduled for major surgery followed by a stay in an intensive care unit were randomized to RHC or usual care. There was no benefit to RHC-directed therapy over standard care, and there was a higher rate of pulmonary embolism in the catheter group. One limitation of this study is that New York Heart Association (NYHA) class III-IV HF patients only composed 13% of the study population. Thus, it is unknown whether RHC helps in this group, but the trend favored standard care in the subgroup analysis. The study provided hemodynamic goals for the RHC group resulting in higher use of inotropic agents (48.9% vs 32.8% in the standard care group), which may be a reason for the lack of benefit. Thus, we see another area in which clinical logic does not correlate with clinical outcome.
Transesophageal echocardiography (TEE) and continuous electrocardiogram evaluation have also been evaluated to determine if routine use in patients at high risk for CAD adds to the identification of perioperative outcomes beyond clinical assessment. However, sensitivity and positive predictive value were low for TEE prediction of ischemic outcomes. In a multivariable analysis, the odds ratio for the association of TEE findings with outcomes was 2.6 and was most predictive of ventricular tachycardia. In evaluating ischemic outcomes alone, TEE was not predictive beyond routine clinical data.53
LIMITATIONS OF PREVIOUS STUDIES
