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Anaesthesia 2012, 67, 389–395                                                                                  doi:10.1111...
Anaesthesia 2012, 67, 389–395                            Biccard et al. | Biomarkers and Holter monitoring for risk strati...
Biccard et al. | Biomarkers and Holter monitoring for risk stratification                                      Anaesthesia ...
Anaesthesia 2012, 67, 389–395                                   Biccard et al. | Biomarkers and Holter monitoring for risk...
Biccard et al. | Biomarkers and Holter monitoring for risk stratification                                      Anaesthesia ...
Anaesthesia 2012, 67, 389–395                          Biccard et al. | Biomarkers and Holter monitoring for risk stratific...
Biccard et al. | Biomarkers and Holter monitoring for risk stratification                                           Anaesth...
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  1. 1. Anaesthesia 2012, 67, 389–395 doi:10.1111/j.1365-2044.2011.07020.xOriginal ArticleWhat is the best pre-operative risk stratification tool for majoradverse cardiac events following elective vascular surgery? Aprospective observational cohort study evaluating pre-operativemyocardial ischaemia monitoring and biomarker analysisB. M. Biccard,1 P. Naidoo2 and K. de Vasconcellos11 Consultant, Perioperative Research Unit, Department of Anaesthesia, 2 Specialist, National Health Laboratory Services,Department of Chemical Pathology, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban,KwaZulu-Natal, South AfricaSummaryAlthough brain natriuretic peptide has been shown to be superior to the revised cardiac risk index for risk stratificationof vascular surgical patients, it remains unknown whether it is superior to alternative dynamic risk predictors, such asother pre-operative biomarkers (C-reactive protein and troponins) or myocardial ischaemia monitoring. The aim of thisprospective observational study was to determine the relative clinical utility of these risk predictors for the prediction ofpostoperative cardiac events in elective vascular surgical patients. Only pre-operative troponin elevation (OR 56.8, 95%CI 6.5–496.0, p < 0.001) and brain natriuretic peptide above the optimal discriminatory point (OR 6.0, 95% CI 2.7–12.9,p < 0.001) were independently associated with cardiac events. Both brain natriuretic peptide and troponin riskstratification significantly improved overall net reclassification (74.6% (95% CI 51.6%–97.5%) and 38.5% (95% CI 22.4–54.6%, respectively)); however, troponin stratification decreased the correct classification of patients with cardiaccomplications ()59%, p < 0.001). Pre-operative brain natriuretic peptide evaluation was the only clinically usefulpredictor of postoperative cardiac complications.. ..............................................................................................................................................................Correspondence to: Dr B. BiccardEmail: 19 November 2011It is estimated that nearly a million patients each year risk-stratify patients in a clinically useful manner, onlyworldwide sustain major cardiac complications such as the revised cardiac risk index (RCRI) [2] has beencardiac death, myocardial infarction and cardiac arrest incorporated into both American and European guide-following non-cardiac surgery [1]. A number of pre- lines for pre-operative non-cardiac risk assessment [5, 6].operative strategies have been used to identify at risk However, with regards to risk stratification forpatients, including clinical risk scores [2], the detection vascular surgical patients, there has been significantof myocardial ischaemia by ambulatory Holter progress in determining appropriate stratification be-monitoring [3], and biomarker analysis [4]. Although yond the RCRI, by incorporating the pre-operativeindividually, all of these approaches have been used to brain natriuretic peptide (BNP) concentration. First, itAnaesthesia ª 2012 The Association of Anaesthetists of Great Britain and Ireland 389
  2. 2. Anaesthesia 2012, 67, 389–395 Biccard et al. | Biomarkers and Holter monitoring for risk stratificationhas been shown, using appropriate reclassification was added to the protocol, also measured in the 24 hstatistics [7, 8], that BNP has clinical utility for pre- before surgery [11].operative risk stratification of vascular patients [9], even Starting in June 2008, a sub-cohort of patientsin the presence of RCRI risk stratification. Subse- underwent pre-operative Holter monitoring for myo-quently, a collaborative group conducted an individual cardial ischaemia using a Schiller MT-200 ECG Holterpatient data meta-analysis, and based on the sample size monitor (Shiller AG, Baar, Switzerland). Monitoringwas able to determine that neither the RCRI score, nor started the day before surgery and was continued rightany of its components, was able to improve on a up to patients’ arrival in the operating theatre forBNP-based pre-operative risk stratification for elective surgery. The number of patients recruited for this sub-vascular surgical patients [10]. These studies have cohort was limited by the availability of the monitors.established the superiority of BNP over the RCRI and The Holter data were only analysed (by KV) at the endits individual component risk factors in pre-operative of the study, and the analysis was blinded as to outcome.risk stratification. An a priori decision was taken to analyse the number of However, it has not yet been shown whether BNP episodes of ST depression lasting > 10 min. We definedwill still retain its powerful predictive ability when ST depression as a deviation > 1 mV from baselinecompared with other dynamic risk predictors such as measured 60 ms after the J point. The end of the episodepre-operative troponin levels and myocardial ischaemia of ST depression was defined as the return of the STmonitoring. To address this question, we conducted a deviation to < 1 mV from baseline for 60 s. The STprospective observational study to determine the relative segments were inspected visually and ST deviations dueimportance and clinical utility of the RCRI, pre-operative to artefact were not considered. Modified V5 and V2myocardial ischaemia and pre-operative elevation of the leads were analysed. The mean heart rate, maximumbiomarkers C-reactive protein (CRP), BNP and tropo- heart rate and longest duration of time abovenins, in the prediction of postoperative major adverse 100 beats.min)1 were also analysed.cardiac events within 30 days of elective vascular surgery. The peri-operative anaesthetic technique was at the discretion of the attending anaesthetist. There was noMethods study protocol for the management of an elevatedThis study was conducted at Inkosi Albert Luthuli postoperative troponin, and management was deter-Central Hospital, in KwaZulu-Natal, South Africa, with mined by the anaesthetic and surgical team on aninstitutional ethics approval, and was registered with the individual patient basis. Attending clinicians were notnational administrative body (South African National blinded to the pre-operative biomarker results.Clinical Trials Register). We recruited elective vascular The samples for BNP and Troponin I were collectedsurgical patients between February 2008 and March in EDTA and serum separator tubes (Greiner Bio-One,2011 who gave informed consent. Patients consented Frickenhausen, Germany), respectively. All samplesfor: collection of clinical risk factors alone; collection of were centrifuged and analysed on receipt, using theclinical risk factors with pre-operative biomarkers; or Advia CentaurÒ Xp (Siemens Healthcare, Malvern, PA,collection of clinical risk factors and pre-operative USA), which involves chemiluminescent technology.biomarkers, with ambulatory Holter monitoring. The CRP analysis was performed on serum samples, All patients’ characteristics and cardiac clinical risk using the latex enhanced immunoturbidimetric method.predictors were collected as per the definition of the The primary outcome was major adverse cardiacRCRI [2]. The clinical risk factor dataset was complete events, defined as a composite of death within 30 days offor all recruited patients and was reviewed by BB for surgery, or a serum troponin result above the upperaccuracy; part of this dataset has been used for a reference limit within the first three postoperative days.previous publication [9]. Troponin and CRP levels were Categorical data were analysed using the Fisher’s exactmeasured at some point in the 24 h before surgery. In test or Pearson’s chi-squared test where appropriate; allApril 2008, the hospital changed the troponin assay continuous data were compared using independentfrom troponin T to troponin I, and in August 2008, BNP samples t-test or Mann–Whitney U-test. The statistical390 Anaesthesia ª 2012 The Association of Anaesthetists of Great Britain and Ireland
  3. 3. Biccard et al. | Biomarkers and Holter monitoring for risk stratification Anaesthesia 2012, 67, 389–395analysis was conducted in two stages; in the first stage, a Resultsunivariate analysis was conducted for all the patients who Nine hundred and seventy-eight patients were eligiblehad both pre-operative biomarker and Holter monitor- for the study in the 3-year-period, of whom 788 patientsing data. All risk factors with a univariate association of consented. The compositions of the cohorts are shownp < 0.1 with the study outcome were entered into in Fig. 1. The study outcome occurred in 136 out of themultivariate analysis, using binary logistic regression. If 788 recruited patients (17%, 95% CI 15–20%) and wasnone of the Holter risk factors were found to be similar between the four cohorts: pre-operative troponinindependent predictors of the study outcome, then the cohort (98 ⁄ 534, 18%, 95% CI 15–22%); pre-operativesecond stage of the analysis consisted of a multivariate BNP cohort (65 ⁄ 403, 16%, 95% CI 13–20%), pre-analysis using the larger biomarker cohort. By only operative CRP cohort (87 ⁄ 508, 17%, 95% CI 14–20%);including univariate predictors with p < 0.1 into a and pre-operative Holter cohort (58 ⁄ 318, 18%, 95% CIsubsequent multivariate regression, the events per var- 14–23).iable ratio were kept above ten, thus minimising the bias The baseline patient characteristics are shown inassociated with the estimate of risk [12]. A backward Table 1. Patients who sustained major adverse cardiacstepwise modelling technique was also performed, based events were older, had significantly more ischaemicon likelihood ratios with entry and removal probabilities heart disease, diabetes and pre-operative troponin levelset at 0.05 and 0.1, respectively. For biomarker analysis, above the upper reference limit, and they also hadcategorical data were used. Positive pre-operative tropo- significantly higher pre-operative BNP and CRP levels.nin levels were defined as above the upper reference level, They were also taking significantly more beta-blockerand positive pre-operative BNP and CRP levels were and aspirin therapy pre-operatively.defined as above the optimal discriminatory point Univariate analysis of the Holter cohort is shown indetermined using a receiver-operating characteristic Table 2; the only Holter variable associated withcurve for the study outcome. major adverse cardiac events with a p < 0.1 was the Finally, to determine whether any of the indepen-dent predictors identified in the logistic regressionsignificantly improved pre-operative risk prediction forpostoperative major adverse cardiac events, a category- Eligible patients (n = 978)free net reclassification was used. This reclassificationmethod is deemed the most objective statistical tool forevaluating the prognostic performance of a risk predic- Recruited patients (n = 788)tor. The results from a category-free net reclassification Clinical risk factors (n = 788)are independent of the clinical risk stratification toolused during the study, and so can be used for objectivecomparisons with potential future risk predictors [13].Patients were reclassified into a high-(positive indepen- Preoperative biomarker cohortdent risk predictors) or low-(negative independent risk Troponins (n = 560)predictors) risk category. The success of this reclassifi- BNP (n = 403)cation is described by the change in net reclassification,where a positive change reflects an improvement in risk CRP (n = 508)stratification. Net reclassification is the differencebetween the proportion of patients correctly and incor-rectly reclassified [8] according to the study outcome. Holter cohort (n = 318)SPSS 15.0 for Windows (IBM, NY, USA), EpiCalc 2000(Version 1.2, Brixton Health, UK) and SAS Software 9.1(SAS Institute Inc., Cary, NC, USA) were used for data Figure 1 Flow diagram of recruited patients. BNP, brainanalysis. natriuretic peptide; CRP, C-reactive protein.Anaesthesia ª 2012 The Association of Anaesthetists of Great Britain and Ireland 391
  4. 4. Anaesthesia 2012, 67, 389–395 Biccard et al. | Biomarkers and Holter monitoring for risk stratificationTable 1 Baseline patient characteristics. Values are mean (SD) number (proportion), or median [IQR (range)]. Total cohort Patients with Patients without (n = 788) MACE (n = 136) MACE (n = 652) p value Clinical risk factors Age 58.2 (14.2) 62.4 (13.4) 57.4 (14.2) < 0.001 Men 512 (65%) 80 (59%) 432 (66%) 0.11 Ischaemic heart disease 275 (35%) 74 (54%) 201 (31%) < 0.001 Diabetes 338 (43%) 78 (57%) 260 (40%) < 0.001 Cardiac failure 37 (5%) 11 (8%) 26 (4%) 0.46 Cerebrovascular accident 159 (20%) 23 (17%) 136 (21%) 0.35 Creatinine > 177 lmol.l)1 18 ⁄ 730 (3%) 4 ⁄ 130 (3%) 14 ⁄ 600 (2%) 0.62 Pre-operative medications Beta-blockers 267 (34%) 82 (60%) 185 (28%) < 0.001 Statins 685 (87%) 125 (92%) 560 (86%) 0.07 Aspirin 714 (91%) 131 (96%) 583 (89%) 0.009 Pre-operative biomarkers Troponin I elevation 25 ⁄ 509 (5%) 20 ⁄ 98 (20%) 5 ⁄ 436 (1%) < 0.001 BNP; 33.6 [12.5–93.8 76.8 [39.4–337.7 28.7 [11.1–74.7 < 0.001 (2.1–3893.0)] (4.5–3893.0)] (2.1–3138.0)] CRP; g.dl)1 19 [5.4–67 28 [8–108 17.3 [5.0–62.2 0.008 (0–263.0)] (0.1–263.0)] (0–210.0)]BNP, brain natriuretic peptide; CRP, C-reactive protein; MACE major adverse cardiac events.pre-operative overnight mean heart rate. Pre-operative larger biomarker cohort was used for the subsequentBNP and troponin elevation also had an association of logistic regression of independent predictors associatedp < 0.1 for postoperative major adverse cardiac events. with major adverse cardiac events.However, on multivariate analysis, the mean pre-oper- The univariate associations of the biomarker cohortsative heart rate was removed from the model, leaving with major adverse cardiac events are shown in Table 3.only pre-operative troponin and BNP elevation inde- The RCRI, pre-operative BNP, CRP and troponinpendently associated with the outcome. As a result, the elevation were entered into the multivariate analysis, with pre-operative troponin (OR 57, 95% CI 6–496,Table 2 Univariate predictors of major adverse cardiac p < 0.001) and BNP (OR 6.0, 95% CI 2.7–12.9,events in the Holter cohort. p < 0.001) elevation being the only independent risk factors associated with major adverse cardiac events. OR (95% CI) p value The pre-operative BNP optimal cut-off had an area Clinical risk factors RCRI score 1.3 (1.0–1.7) 0.11 under the curve of 0.69 (95% CI 0.62–0.75, p = 0.035). Holter risk predictors Episodes of ST depression 1.0 (0.9–1.2) 0.66 Table 3 Univariate predictors of major adverse cardiac Mean heart rate 1.02 (0.99–1.04) 0.09 events in the biomarker cohort. Maximum heart rate 1.00 (0.99–1.02) 0.58 Longest duration 1.00 (1.00–1.00) 0.12 above 100 beats.min)1 OR (95% CI) p value Pre-operative biomarkers Clinical risk factors BNP; 1.00 (1.00–1.00) < 0.001 RCRI score 1.5 (1.2–1.8) < 0.001 BNP above optimal 4.6 (2.1–10.0) < 0.001 Pre-operative biomarkers discriminatory point BNP above optimal 5.0 (2.7–9.4) < 0.001 of 48.1 discriminatory point CRP; g.dl)1 1.01 (0.99–1.01) 0.12 of 39.4 CRP above optimal 1.7 (0.9–3.4) 0.13 CRP above the optimal 1.8 (1.1–2.9) 0.012 discriminatory point discriminatory point of 22 g.dl)1 of 22 g.dl)1 Troponin I > 0.1 38.3 (4.6–320.0) 0.001 Troponin I > 0.1 22.1 (8.1–60.0) < 0.001BNP, brain natriuretic peptide; bpm, beats.min)1; CRP, C- BNP, brain natriuretic peptide; CRP, C-reactive protein; RCRI,reactive protein; RCRI, revised cardiac risk index. revised cardiac risk index.392 Anaesthesia ª 2012 The Association of Anaesthetists of Great Britain and Ireland
  5. 5. Biccard et al. | Biomarkers and Holter monitoring for risk stratification Anaesthesia 2012, 67, 389–395Table 4 Net reclassification change for postoperative major adverse cardiac events using pre-operative BNP and tro-ponins. Reclassification change of patients without Reclassification change MACE of patients with MACE Overall net reclassification change Cohort proportion p-value proportion p-value proportion p value BNP above the optimal +21% < 0.0001 +54% < 0.0001 +75% (95% CI 52–98%) < 0.0001 discriminatory point Troponin above the +98% < 0.0001 )59% < 0.0001 +39% (95% CI 22–55%) 0.0006 upper reference limitBNP, brain natriuretic peptide; MACE, major adverse cardiac event. The reclassification improvement for postoperative major adverse cardiac event by classifying many of themmajor adverse cardiac events associated with pre-oper- as low-risk. As this would have significant negativeative troponin and BNP elevation is shown in Table 4. clinical impact, we do not advocate using pre-operativeBoth pre-operative troponin and BNP analysis signifi- troponins as a screening test to exclude high-riskcantly improved overall risk stratification. However, patients. In contrast, pre-operative BNP was an inde-pre-operative troponin risk stratification significantly pendent predictor of major adverse cardiac events anddecreased correct classification of patients who devel- significantly improved the risk stratification of patientsoped major adverse cardiac events. with and without major adverse cardiac events. There are a number of potential reasons why pre-Discussion operative BNP may be a better predictor of postoper-This study has shown that, in elective vascular surgical ative cardiac complications than troponins. Brainpatients, only pre-operative BNP and troponins have the natriuretic peptide is rapidly secreted from ventricularcapacity to change risk prediction significantly. Impor- myocytes when exposed to even minor elevations intantly, this ability to risk-stratify is independent of the ventricular pressure or volume loading [18], or frompre-operative clinical risk factors found in the RCRI, a myocardial ischaemia [18, 19]. This allows pre-operativefinding consistent with earlier work on pre-operative BNP elevation to identify a vulnerable ventricle at risk ofBNP in vascular patients [14]. As a result of the RCRI’s a major adverse event. In contrast, troponin elevations,poor ability to risk-stratify vascular surgical patients [15, as detected by standard sensitivity troponin assays, most16], it is important to identify whether alternative risk commonly reflect myocyte necrosis as the final commonstratification tools (i.e. pre-operative ECG and pre- pathway of a damaged ventricle. Pre-operative troponinoperative biomarkers) are appropriate for this popula- elevation probably reflects a ventricle that is too fartion. down the pathway of cardiovascular injury to provide We statistically defined a risk factor with clinical further clinically useful pre-operative risk stratificationutility as one that was both independently associated information. This is further emphasised by the patternwith the outcome and also significantly improved pre- of troponin increase commonly seen in the postopera-operative risk category classification for subsequent tive period, where only 12% of patients who sustain amajor adverse cardiac events [7, 17]. Adopting the risk peri-operative myocardial infarction have troponinpredictors identified in this study should result in a elevation on postoperative day 1, while 77% havesignificant change in pre-operative risk categorisation, troponin elevation by day 3 [20]. Similarly, in ourwhich could potentially alter pre-operative clinical study, only 4.7% of patients had pre-operative troponinmanagement. elevation, compared with 15.9% with postoperative Pre-operative troponins significantly improved pa- troponin elevation. These findings demonstrate thattient risk reclassification overall, but worsened the pre-operative troponin elevation is poorly associatedreclassification of the sub-cohort of patients who had a with postoperative cardiac events.Anaesthesia ª 2012 The Association of Anaesthetists of Great Britain and Ireland 393
  6. 6. Anaesthesia 2012, 67, 389–395 Biccard et al. | Biomarkers and Holter monitoring for risk stratification With regards to the Holter monitoring used for this Acknowledgementsstudy, only two channels (modified V2 and V5) were We thank Tecmed South Africa for providing us withanalysed. This is certainly not equivalent to the 12-lead Holter hardware and software at cost price. The studyECG monitoring used in other studies of peri-operative itself was funded through a grant from the Medicalmyocardial ischaemia, and may have decreased the Research Council of South Africa, awarded to BB.sensitivity of our Holter data. However, we do notconsider this to be a significant limitation, as the Competing interestscombination of two precordial leads has a reported No competing interests declared.sensitivity of over 90% for the detection of myocardialischaemia [21]. References This is the first study to compare the performance of 1. Devereaux PJ, Goldman L, Cook DJ, Gilbert K, Leslie K, Guyatt GH. Perioperative cardiac events in patients undergoing noncardiacthree different pre-operative risk stratification tech- surgery: a review of the magnitude of the problem, theniques (i.e., clinical risk predictors, biochemical risk pathophysiology of the events and methods to estimate and communicate risk. Canadian Medical Association Journal 2005;markers and ECG Holter monitoring) simultaneously. 173: 627–34.These findings have important implications for the 2. Lee TH, Marcantonio ER, Mangione CM, et al. Derivation anddevelopment of an evidence-based clinical approach to prospective validation of a simple index for prediction of cardiac risk of major noncardiac surgery. Circulation 1999; 100: 1043–9.risk prediction in vascular surgical patients, and warrant 3. Mangano DT, Browner WS, Hollenberg M, London MJ, Tubau JF,verification in an independent cohort. Tateo IM. Association of perioperative myocardial ischemia with cardiac morbidity and mortality in men undergoing noncardiac We can now summarise our understanding of the surgery. The Study of Perioperative Ischemia Research Group.role of BNP in pre-operative risk stratification for New England Journal of Medicine 1990; 323: 1781–8.vascular surgical patients as follows: (1) BNP improves 4. Choi JH, Cho DK, Song YB, et al. Preoperative NT-proBNP and CRP predict perioperative major cardiovascular events in noncardiacRCRI risk stratification [9]; (2) BNP is superior to and surgery. Heart 2010; 96: 56–62.independent of the RCRI and its individual compo- 5. Fleisher LA, Beckman JA, Brown KA, et al. ACC ⁄ AHA 2007 Guidelines on Perioperative Cardiovascular Evaluation and Carenents [10]; and (3) BNP remains independently for Noncardiac Surgery: Executive Summary: A Report of thepredictive even in the presence of pre-operative American College of Cardiology ⁄ American Heart Association Tasktroponin evaluation and myocardial ischaemia Force on Practice Guidelines (Writing Committee to Revise the 2002 Guidelines on Perioperative Cardiovascular Evaluation formonitoring. Noncardiac Surgery): Developed in Collaboration With the Based on the recommended process for the critical American Society of Echocardiography, American Society of Nuclear Cardiology, Heart Rhythm Society, Society of Cardiovas-evaluation of novel biomarkers of cardiovascular risk cular Anesthesiologists, Society for Cardiovascular Angiographybefore integration in clinical practice, a progressive six- and Interventions, Society for Vascular Medicine and Biology, andphase evaluation has been recommended [22]. Brain Society for Vascular Surgery. Circulation 2007; 116: 1971–96. 6. Poldermans D, Bax JJ, Boersma E, et al. Guidelines for pre-natriuretic peptide evaluation has now reached the operative cardiac risk assessment and perioperative cardiacfourth stage (that of clinical utility). As it has been management in non-cardiac surgery: the Task Force for Preop- erative Cardiac Risk Assessment and Perioperative Cardiacshown significantly to outperform the RCRI as well as Management in Non-cardiac Surgery of the European Societyother methods, we believe that we have now established of Cardiology (ESC) and European Society of AnaesthesiologyBNP as the modality of choice for estimating risk in (ESA). European Heart Journal 2009; 30: 2769–812. 7. Cook NR. Statistical evaluation of prognostic versus diagnosticthese patients. models: beyond the ROC curve. Clinical Chemistry 2008; 54: We propose that future research into risk stratifi- 17–23. 8. Pencina MJ, D’Agostino RB Sr, D’Agostino RB Jr, Vasan RS.cation for vascular surgical patients should include the Evaluating the added predictive ability of a new marker: fromverification of these results in an independent vascular area under the ROC curve to reclassification and beyond.surgical cohort and determination of whether pre- Statistics in Medicine 2008; 27: 157–72; discussion 207–12. 9. Biccard BM, Naidoo P. The role of brain natriuretic peptide inoperative management of vascular surgical patients prognostication and reclassification of risk in patients undergo-based on pre-operative BNP levels improves clinical ing vascular surgery. Anaesthesia 2011; 66: 379–85. 10. Biccard BM, Lurati Buse GA, Burkhart C, et al. The influence ofoutcome (stage 5 of the evaluation of novel biomarkers) clinical risk factors on pre-operative B-type natriuretic peptide[22]. These findings should also be evaluated in non- risk stratification of vascular surgical patients. Anaesthesiavascular, non-cardiac surgery. 2012; 67: 55–59.394 Anaesthesia ª 2012 The Association of Anaesthetists of Great Britain and Ireland
  7. 7. Biccard et al. | Biomarkers and Holter monitoring for risk stratification Anaesthesia 2012, 67, 389–39511. Rodseth RN, Padayachee L, Biccard BM. A meta-analysis of the 16. Biccard BM, Rodseth RN. Utility of clinical risk predictors for utility of pre-operative brain natriuretic peptide in predicting preoperative cardiovascular risk prediction. British Journal of early and intermediate-term mortality and major adverse Anaesthesia 2011; 107: 133–43. cardiac events in vascular surgical patients. Anaesthesia 2008; 17. Ray P, Le Manach Y, Riou B, Houle TT. Statistical evaluation of a 63: 1226–33. biomarker. Anesthesiology 2010; 112: 1023–40.12. Peduzzi P, Concato J, Kemper E, Holford TR, Feinstein AR. A 18. Rodseth RN. B type natriuretic peptide-a diagnostic break- simulation study of the number of events per variable in logistic through in peri-operative cardiac risk assessment? Anaesthesia regression analysis. Journal of Clinical Epidemiology 1996; 49: 2009; 64: 165–78. 1373–9. 19. Struthers A, Lang C. The potential to improve primary prevention13. Pencina MJ, D’Agostino RB Sr, Steyerberg EW. Extensions of net in the future by using BNP ⁄ N-BNP as an indicator of silent reclassification improvement calculations to measure usefulness ‘pancardiac’ target organ damage: BNP ⁄ N-BNP could become of new biomarkers. Statistics in Medicine 2011; 30: 11–21. for the heart what microalbuminuria is for the kidney. European14. Rodseth RN, Lurati Buse GA, Bolliger D, et al. The predictive Heart Journal 2007; 28: 1678–82. ability of pre-operative B-type natriuretic peptide in vascular 20. Biccard BM, Rodseth RN. The pathophysiology of peri-operative patients for major adverse cardiac events an individual patient myocardial infarction. Anaesthesia 2010; 65: 733–41. data meta-analysis. Journal of the American College of Cardi- 21. Landesberg G. Monitoring for myocardial ischemia. Best Practice ology 2011; 58: 522–9. and Research Clinical Anaesthesiology 2005; 19: 77–95.15. Ford MK, Beattie WS, Wijeysundera DN. Systematic review: 22. Hlatky MA, Greenland P, Arnett DK, et al. Criteria for evaluation prediction of perioperative cardiac complications and mortality of novel markers of cardiovascular risk: a scientific statement by the revised cardiac risk index. Annals of Internal Medicine from the American Heart Association. Circulation 2009; 119: 2010; 152: 26–35. 2408–16.Anaesthesia ª 2012 The Association of Anaesthetists of Great Britain and Ireland 395