1 Academic Unit of Anaesthesia, University of Leeds, Leeds General Infirmary, Great George Street, Leeds LS1 3EX, UK. 2 Nuffield Department of Anaesthetics, University of Oxford, John Radcliffe Hospital, Headley Way, Headington, Oxford OX3 9DU, UK
*Corresponding author. E-mail: s.howell{at}leeds.ac.uk
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Introduction |
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Perioperative cardiac events: the population burden of disease |
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However, although the incidence of perioperative cardiac complications is almost certainly lower in patients undergoing major surgery other than vascular (or cardiac) surgery than in those undergoing cardiovascular operations, these patients may contribute much the greater population burden of perioperative cardiac events. The Hospital Episode Statistics for England and Wales indicate that in the year 20022003 there were 65 567 operations with codes OPCS4 in the range L16 to L31 and L37 to L75.11 These codes broadly cover major vascular surgical operations on arteries, but exclude operations on the cerebral arteries with codes in the range L33 to L35. In the same period 3 135 784 operations in people aged 6074 yr and 2 323 902 operations in people aged 75 yr or more were recorded. Thus, in total 5 459 686 operations were reported in patients aged over 59 yr. The Hospital Episode Statistics report crude data and include many minor and diagnostic procedures. Perhaps only 510% of the procedures recorded were major operations. However, this still represents between a quarter and half a million people aged over 60 yr in England and Wales undergoing major surgery each year. It is clear that vascular surgery patients represent only a fraction of the surgical population. Several million major and minor procedures are undertaken on people aged 60 yr or over in England and Wales each year. It seems likely that, although the cardiac event rate may be higher in patients undergoing major vascular surgery, in any given year, more patients will suffer a perioperative infarction after other types of major non-cardiac surgery. If this is the case, there are considerable implications for the benefits to be gained from strategies to reduce perioperative cardiac events.
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Preventing perioperative cardiac events: the population perspective |
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While an intervention may yield a several-fold reduction in perioperative risk, if the baseline risk is relatively small the absolute risk reduction will also be small. In the randomized study of Oliver and colleagues comparing mivazerol and placebo, patients undergoing vascular surgery who were randomized to mivazerol had a relative risk of perioperative cardiac death of 0.33 (95% confidence interval 0.180.91).36 The absolute risk of cardiac death among vascular surgery patients randomized to placebo was 4% and mivazerol reduction reduced this to 1.3%, an absolute risk reduction of 2.7%. This small benefit is reflected in the number needed to treat (NNT) of 37. That is to say, 37 patients undergoing major vascular surgery need to be treated with mivazerol in order to prevent one cardiac event. In fact, this NNT is not dissimilar to that seen for some well-established interventions in other fields. For example, amongst patients aged between 65 and 74 yr presenting with myocardial infarction, 37 need to be treated with thrombolysis to prevent one death between presentation and 35 days. For patients aged between 55 and 64 yr, 56 patients need to be treated, while for patients aged less than 55 yr 91 patients need to be treated.19 Thus, it may be argued that the therapies that may be used to prevent perioperative infarction and those used to treat patients presenting with a myocardial infarction offer similar levels of benefit. From a public health perspective, the difference between patients presenting with myocardial infarction and those suffering perioperative myocardial infarction is that, while very many people undergo surgery, very few of these suffer a perioperative infarction, so the population burden of disease from perioperative infarction is less than that from acute non-operative infarction. In the 12-month period covered by the hospital episode statistics for 2002 to 2003 there were 105 476 consultant episodes and 69 116 admissions for acute myocardial infarction.11 Lee and colleagues, in their study of patients undergoing major surgery, reported an overall in-hospital perioperative myocardial infarction rate in their derivation cohort of 1%.30 A total of 5 459 686 operations in patients aged 60 yr or over are recorded as having taken place in England and Wales in the period 20022003 (see above). However, this included a large number of diagnostic procedures and minor operations. One might estimate that perhaps only 10% of the operations were major procedures. If this is the case, one can estimate that perhaps five and a half thousand patients suffered a perioperative infarction in the study period. Thus, it seems likely at first sight that the absolute number of patients likely to suffer perioperative infarction is considerably lower than the number of patients presenting with infarction in the non-operative setting. The implication is that greater population benefit will be obtained from aggressive management of non-operative infarction than of perioperative infarction. This assumption will be challenged below.
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Risk scoring |
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To be of value for any of these applications, a risk score should be robust, have been tested in a number of settings, and produce reliable estimates of risk in a range of operative settings. It is not clear that the tools currently available to us fulfil these requirements. The earliest, and perhaps still the best known, cardiac risk score is the Goldman Multifactorial Cardiac Risk Index.16 This was derived in a prospective study of 1001 patients who between them suffered 58 cardiac events (19 patients died from a cardiac cause and 39 suffered one or more life-threatening cardiac complications, but did not die). Approximately 45 possible predictors of perioperative cardiac morbidity were examined. An unspecified number of further predictors were created by the combination of raw factors. All of these potential predictors were then subjected to discriminant function analysis. Nine predictors of perioperative cardiac events were identified and given numerical weights for inclusion in the final model. Depending on their total risk score derived using these weights, patients were divided into four categories of increasing risk.
The Goldman index is important both because it is still cited and used and because it led the way for subsequent work. However, it suffers from a number of weaknesses. Almost every conceivable cardiac symptom and sign was included in the initial analysis. Thus, the factors relevant to heart failure that were examined included dyspnoea, orthopnoea, oedema, New York Heart Association Score, jugular venous distension, the presence of a third or fourth heart sound, rales, pulmonary vasculature appearance on X-ray, heart size and QRS axis. No account is taken of the fact that these risk factors are not independent. That is to say, the presence of one of these factors is likely to be reflected by the presence of several others. The result is that rather than the clinical condition of heart failure being included in the risk score, it is represented by one or more of its symptoms or signs. Heart failure is represented in the final index by an elevated jugular venous pressure and/or the presence of a third heart sound. These signs may or may not be present in any individual patient with heart failure.
Nine risk factors emerged from the discriminant function analysis as significant, with weights ranging from 0.123 to 0.451. These were translated into scores of between 3 and 11 points. However, there has to be some suspicion about the robustness of the weights. It is difficult, if not impossible, to perform a formal power calculation for a multivariate analysis because one cannot anticipate the relative weightings that will be afforded to individual risk factors. In the Goldman risk index the presence of a third heart sound or jugular venous distension is given a weight of 11 points and the presence of important valvular aortic stenosis a weight of 3 points. These values cannot be known in advance, but the precision with which they are determined will have a considerable impact on the final risk model. In a series of computer simulation studies of logistic regression and proportional hazards analysis, Concato and colleagues demonstrated that, if the weighting afforded to a given variable is to be determined with reasonable precision, then 10 subjects who suffered an adverse event are required for each variable in the final model.9 38 39 Thus, for the nine factors in the Multifactorial risk index, 90 adverse events would be required rather than the 58 actually observed. When tested in populations other than that in which it was derived, the index does not perform especially well.8 30 It appears to be poor at identifying high-risk patients. These formed only a small part of the derivation data set, so relatively few data were available on these patients. At the same time, they are perhaps the group of greatest interest to the clinician. In the validation study conducted by Lee and colleagues, the performance of a modified risk index, derived by these authors and described below, was compared with that of the Goldman risk index.30 The area under the receiver operating characteristic (ROC) curve for the Goldman index was 0.701 (SE 0.043), while that under the ROC curve for the index derived by Lee and colleagues was 0.806 (SE 0.034). While the areas under these two curves were significantly different (P=0.021), the difference does not appear startlingly great. Indeed, the performance of the indices was very similar for the lower risk categories of each index. This was not the case for the highest risk categories of each index, class IV in each case. The Goldman index predicts a 78% cardiac event rate in this group. Neither of the two Goldman class IV patients from the validation cohort, nor the seven Goldman class IV patients in the study population as a whole, suffered a cardiac event. In contrast, 11% of the 109 patients place in class IV by the Lee index suffered a cardiac event. This is very similar to the predicted event rate of 9.1% (95% confidence interval 5.513.8%).
For all its shortcomings, the Goldman index is important because it laid the groundwork for further endeavours in this field.12 29 30 The most current scoring system for cardiac risk in non-cardiac surgery is probably that of Lee and colleagues.30 They studied 4315 patients, dividing them into a derivation cohort of 2893 patients from which a risk score was derived and a validation cohort of 1422 patients on which the performance of the score was examined. This includes six risk factors, as listed in Table 1. It will be seen that these represent clinical conditions such as ischaemic heart disease rather than the signs and symptoms that are in the Goldman risk index. The odds ratios for the individual risk factors are all of the same order of magnitude and in the risk score all the factors are given the same weight. Patients with zero, one, two and three or more risk factors are assigned to classes I, II, III and IV respectively. The score was derived from a data set that included 2893 patients who suffered 56 adverse events, so that there were 9.3 adverse events for each risk factor in the final model.
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The long-term implications of surgery |
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The cardiac troponin assays are described in a review elsewhere in this Postgraduate Issue. The troponins are cardiac-specific proteins released during myocardial injury. Studies using the cardiac troponins in patients presenting with chest pain have led to a revision of our understanding of myocardial infarction. Infarction is no longer viewed as a binary event, such that patients have either suffered a myocardial infarction or they have not. Rather, it is now held that there is a spectrum of myocardial injury characterized by increasing troponin release and ranging from stable angina, through unstable angina to full-blown myocardial infarction.1 Amongst patients presenting with chest pain, some troponin release is seen in many who are not subsequently diagnosed as having suffered a myocardial infarction. The greater the magnitude of this troponin release, the greater the likelihood of a further cardiac event in the ensuing weeks and months.3 18 32 35 45
It is becoming clear that similar considerations apply to myocardial injury in the context of non-cardiac surgery. Several studies, such as that by Haggart and colleagues and the Vascular Anaesthesia Society Study by Howell and colleagues, have shown a continuum of cardiac troponin release in patients undergoing vascular surgery.17 23 Just as increasing troponin release is associated with increasing risk in patients presenting with chest pain, a number of studies suggest that the same is true for non-cardiac surgery patients. Kim and colleagues studied 229 patients undergoing aortic or infra-inguinal surgery or lower extremity amputation.25 Cardiac troponin I (cTnI) levels were measured immediately after surgery and on postoperative days 1, 2 and 3. Ninety-eight patients had cTnI levels above 0.35 ng/ml (the lower detection limit of the assay used). There was a clear doseresponse relationship between the serum cTnI level and the risk of death in the 6 months after surgery. Taking the group of patients with cTnI levels less than 0.35 ng/l as the reference group, the odds ratio for death (95% confidence interval) in the 6 months after surgery was 1.3 (0.44.4) for patients with a troponin level between 0.4 and 1.5 ng/ml. It was 4.3 (0.824.3) for patients with a cTnI level between 1.6 and 3.0 mg/ml, and 4.9 (1.919.0) for patients with cTnI levels greater than 3.0 ng/ml. Landesberg and colleagues obtained similar results in a study of 447 patients undergoing major vascular surgery. Cardiac troponin levels were measured in all patients for the first 3 days after surgery. The odds ratio for death during long-term follow-up (between 1 and 5 yr) increased steadily with increasing postoperative cardiac troponin levels.28 Fewer data exist on the incidence and implications of troponin release in patients undergoing non-vascular surgery. Further data are needed both to determine the incidence of cardiac troponin release in patients undergoing non-cardiac, non-vascular surgery and to determine the long-term implications of such release. One would certainly expect the incidence of myocardial injury to be lower in patients not undergoing vascular surgery but, as already discussed, there are many more of these patients compared with the vascular surgery population. Potentially, perioperative myocardial injury going undetected at the time of operation, but associated with subsequent cardiac events, carries with it a very considerable population burden of disease. If this is indeed the case, the focus of perioperative medicine needs to change from the prevention of perioperative myocardial infarction to the prevention of any perioperative myocardial injury. In many respects the approach will not differ from that to the prevention of perioperative infarction. It remains appropriate for anaesthetists to take due care over identifying at-risk patients and to plan their preoperative assessment and perioperative care appropriately. However, the issue of secondary prevention of cardiovascular disease is thrown into sharper perspective. In the ideal world, all patients with a history of cardiovascular disease who arrive at hospital for surgery and who are found not to be receiving secondary prevention would have this rectified before discharge. It is already clear that patients presenting with peripheral vascular disease benefit from treatment with statins.24 41 It may be argued that patients who present for vascular surgery should receive cardiovascular secondary prevention in the same way as patients with cardiac disease. A consensus statement on the use of antiplatelet therapy in patients with peripheral vascular disease was published in 2003.40 National cardiac guidelines in the UK suggest that patients who have intermittent claudication should be managed in the same way as patients with established coronary artery disease, although we are still some way from achieving this ideal.6 7 It now seems reasonable to ask if patients with one or more risk factors for cardiovascular disease, who undergo surgery, should have pre- and postoperative measurements of cardiac troponin and should receive cardiovascular secondary prevention if any postoperative elevation is detected. This relatively cheap intervention might have a significant impact on the long-term outcome in this group.
In summary, it is clear that perioperative myocardial infarction is a significant issue in patients undergoing vascular surgery. While the incidence of perioperative cardiac complications may be lower in patients undergoing other types of non-cardiac surgery, there are many more of these patients and their impact on the population burden of disease may be greater. Identifying patients at the highest risk of perioperative infarction can be difficult, and risk scores, while potentially of value for population studies, are not an ideal tool for directing care in the individual patient. To some extent this is due to the relatively low incidence of perioperative cardiac events and, thus, the problem in identifying a person likely to suffer such an event. However, studies with cardiac troponins make it clear that the incidence may not be as low as first thought and imply that subclinical perioperative myocardial injury may, in fact, be quite common. Further studies are needed in this field, but if this is the case the development of formal strategies for preventing, identifying and managing subclinical preoperative myocardial injury may be appropriate.
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References |
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