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From Durban to Boston, a “Modest Proposal” to Improve Perioperative Cardiovascular Risk Stratification

London, Martin J. MD

doi: 10.1213/ANE.0000000000000613
Editorials: Editorial

From the Department of Anesthesia and Perioperative Care, University of California, San Francisco, San Francisco, California.

Accepted for publication November 25, 2014.

Funding: None.

The author declares no conflicts of interest.

Reprints will not be available from the author.

Address correspondence to Martin J. London, MD, Department of Anesthesia, VA Medical Center, 4150 Clement St., San Francisco, CA 94121. Address e-mail to

In this issue of Anesthesia & Analgesia, Biccard1 presents a state-of-the-art review of the widely used Revised Cardiac Risk Index (RCRI),2 incorporating a systematic review of other risk prediction studies that have used this index as a comparator. Using standards for the development of clinical risk prediction models proposed by Steyerberg and Vergouwe,3 he presents a thorough analysis of the strengths and weaknesses of the RCRI, along with an elegant and understandable road map of where future research efforts need to be focused, including a concise explanation of the most commonly used statistical techniques relevant to this arena. I invited this review because we need a discussion on the limits of existing risk indices and a thoughtful approach to address these.

Biccard hails from South Africa, a country with its feet planted in both the developed and the developing world. In South Africa, and in the United Kingdom where he studied, Biccard and his colleagues have a stellar track record of evaluating scoring systems that predict perioperative cardiac risk for patients undergoing noncardiac surgery.4–8 In South Africa, Biccard daily assesses the risks of major noncardiac surgery in patients with human immunodeficiency virus (HIV) disease. This adds a unique global public health perspective to the discussion.9–11 In this setting, he has faced challenges predicting cardiovascular risk using a system developed in a single tertiary care metropolitan medical center in the northeastern United States, a population with few similarities to the population he cares for in South Africa. In a country (and continent) with severely constrained resources, the appeal of the RCRI is the simplicity of using just 6 additive predictors. Certainly, this simplicity is just as appealing to United States physicians confronted daily by information overload in their clinical practice. As Biccard explains, in the years since the initial publication of the RCRI, researchers have “tweaked” it adding factors while attempting to maintain its simplicity. These include age, ASA physical class, peripheral vascular disease, functional status, expanded surgical procedure type, the presence of HIV, and concurrent medications.

The definitions of what constitutes perioperative cardiac morbidity have evolved over the past decade. Biccard, through his involvement in the multinational Vascular events In noncardiac Surgery patIents cOhort evaluatioN (VISION) study and his own literature review,12–14 understands the need to systematically reevaluate the predictive abilities of the RCRI. The original RCRI considered several cardiac outcomes in aggregate: myocardial infarction, pulmonary edema, ventricular fibrillation or primary cardiac arrest, and complete heart block.2 At that time, the available cardiac biomarker was creatine kinase (CK) and its MB isoenzyme fraction. CK has been replaced by the troponins, assays for which are also evolving rapidly in their sensitivity (although CK-MB fraction can still be of clinical value in evaluating reinfarction given it shorter half-life in plasma). Readers of this journal are aware of the burgeoning literature on perioperative troponin leaks, including the newly proposed classification of myocardial injury after noncardiac surgery promulgated by the VISION investigators.12–17 The controversy surrounding the significance of troponin as a marker of primary myocardial injury versus troponin release secondary to noncardiac etiologies (most of which are more common than myocardial injury) has been expertly reviewed in recent editorials.18,19

There are controversial methodologic questions related to outcomes assessment in the original RCRI publication.2 The use of a single individual to classify all complications was controversial at the time of the study. Today, it would not be acceptable, “data monitoring boards” are the accepted standard to ensure uniform and unbiased adjudication. Inclusion of pulmonary edema as an outcome is likewise controversial, given the dynamic changes in blood pressure, intravascular volume, or lung function that may occur perioperatively. However, the original authors did present a carefully thought-out schema consistent with their desires to segregate “cardiac” from “noncardiac” etiologies (including their explicit definition of a “primary” cardiac arrest). Whether or not this was truly realized remains controversial. This issue continues to engender controversy as illustrated by a contentious letter to the editor by Lee and Goldman20 and reply by the authors of the new Gupta American College of Surgeons National Surgical Quality Improvement Program risk calculator, debating which outcomes really are cardiac (or not).

Risk calculators based on the American College of Surgeons National Surgical Quality Improvement Program system21–24 use considerably more risk factors and are tailored to specific surgical procedures. Biccard opines that given newer systems that “the preeminence of the RCRI is now in question.” He also reviews the newly released American College of Cardiology/American Heart Association Guidelines on Perioperative Cardiovascular Evaluation and Management of Patents undergoing Noncardiac Surgery,25 in which the new American College of Surgeons National Surgical Quality Improvement Program systems are given considerable attention (and directly compared with the RCRI in a comprehensive table). Biccard suggests that the RCRI may have an “uncertain future in the American College of Cardiology/American Heart Association Guidelines.” His predictions may or may not come to pass. However, the trends toward analysis of perioperative “big data,” as evidenced by efforts of the Anesthesia Quality Institute, the Multicenter Perioperative Outcomes Group, and others, seem to favor multivariate risk calculators that likely will improve predictive accuracy for risk prediction substituting computer horsepower for the 6-factor additive simplicity of the RCRI.

Perioperative medicine is rapidly evolving. To practitioners who worked in the early 1990s, current surgical technologies border on the realm of science fiction. Anesthesia practice is safer and more sophisticated. Transesophageal or transthoracic perioperative echocardiography is now routine, allowing us a much clearer window on our patients’ cardiac condition. Cardiac pathologies are generally better managed, often using evidenced-based guidelines. Newer clinical entities including stress-related cardiomyopathies,26 damage related to chemotherapy (engendering a new specialty of cardio-oncology),27 and HIV-induced atherosclerosis28,29 are increasingly appreciated as potential risk factors. Complex multivariate relations among cardiovascular risk factors, race, gender, and long-term outcome have evolved.30 However, as evidenced by the recent firestorm over the new American Heart Association cholesterol management guidelines (and their very liberal statin recommendations),31 precise delineation of cardiovascular risk factors continues to challenge our diagnostic and therapeutic acumen. Most recently, evidence points to substantially elevated long-term risk of the nonobstructive coronary artery disease, raising new management concerns for cardiologists,32 complicating our perioperative risk assessment.

Medicine constantly advances, based on new science, new findings, and new therapies. The RCRI has had a very good run. It may well be of value into the future, one of the successful examples of perioperative risk assessment. Biccard presents a clear path to follow in developing the next successful risk assessment tool. His approach should be embraced by researchers. I welcome the spirited discussion that I hope his thoughtful and provocative proposal will engender, a discussion that will further our quest to improve global cardiovascular perioperative outcomes.

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Name: Martin J. London, MD.

Contribution: This author conceived and wrote the manuscript.

Attestation: Martin J. London approved the final manuscript.

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Dr. Martin London is the Section Editor for Perioperative Echocardiography and Cardiovascular Education for Anesthesia & Analgesia. This manuscript was handled by Dr. Steven L. Shafer, Editor-in-Chief, and Dr. London was not involved in any way with the editorial process or decision.

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1. Biccard B. Proposed research plan for the derivation of a new Cardiac Risk Index. Anesth Analg. 2015;120:543–53
2. Lee TH, Marcantonio ER, Mangione CM, Thomas EJ, Polanczyk CA, Cook EF, Sugarbaker DJ, Donaldson MC, Poss R, Ho KK, Ludwig LE, Pedan A, Goldman L. Derivation and prospective validation of a simple index for prediction of cardiac risk of major noncardiac surgery. Circulation. 1999;100:1043–9
3. Steyerberg EW, Vergouwe Y. Towards better clinical prediction models: seven steps for development and an ABCD for validation. Eur Heart J. 2014;35:1925–31
4. Rodseth RN, Biccard BM, Le Manach Y, Sessler DI, Lurati Buse GA, Thabane L, Schutt RC, Bolliger D, Cagini L, Cardinale D, Chong CP, Chu R, Cnotliwy M, Di Somma S, Fahrner R, Lim WK, Mahla E, Manikandan R, Puma F, Pyun WB, Radović M, Rajagopalan S, Suttie S, Vanniyasingam T, van Gaal WJ, Waliszek M, Devereaux PJ. The prognostic value of pre-operative and post-operative B-type natriuretic peptides in patients undergoing noncardiac surgery: B-type natriuretic peptide and N-terminal fragment of pro-B-type natriuretic peptide: a systematic review and individual patient data meta-analysis. J Am Coll Cardiol. 2014;63:170–80
5. Biccard BM, Rodseth RN. What evidence is there for intraoperative predictors of perioperative cardiac outcomes? A systematic review. Perioper Med (Lond). 2013;2:14
6. Biccard BM, Lurati Buse GA, Burkhart C, Cuthbertson BH, Filipovic M, Gibson SC, Mahla E, Leibowitz DW, Rodseth RN. The influence of clinical risk factors on pre-operative B-type natriuretic peptide risk stratification of vascular surgical patients. Anaesthesia. 2012;67:55–9
7. Rodseth RN, Lurati Buse GA, Bolliger D, Burkhart CS, Cuthbertson BH, Gibson SC, Mahla E, Leibowitz DW, Biccard BM. The predictive ability of pre-operative B-type natriuretic peptide in vascular patients for major adverse cardiac events: an individual patient data meta-analysis. J Am Coll Cardiol. 2011;58:522–9
8. Biccard BM, Rodseth RN. Utility of clinical risk predictors for preoperative cardiovascular risk prediction. Br J Anaesth. 2011;107:133–43
9. Moodley Y, Naidoo P, Biccard BM. The South African Vascular Surgical Cardiac Risk Index (SAVS-CRI): a prospective observational study. S Afr Med J. 2013;103:746–50
10. Biccard BM. Surgery and cardiovascular outcomes: an untapped public health benefit that potentially saves lives. Anaesthesia. 2012;67:106–9
11. Biccard BM, Bandu R. Clinical risk predictors associated with cardiac mortality following vascular surgery in South African patients. Cardiovasc J Afr. 2007;18:216–20
12. Botto F, Alonso-Coello P, Chan MT, Villar JC, Xavier D, Srinathan S, Guyatt G, Cruz P, Graham M, Wang CY, Berwanger O, Pearse RM, Biccard BM, Abraham V, Malaga G, Hillis GS, Rodseth RN, Cook D, Polanczyk CA, Szczeklik W, Sessler DI, Sheth T, Ackland GL, Leuwer M, Garg AX, Lemanach Y, Pettit S, Heels-Ansdell D, Luratibuse G, Walsh M, Sapsford R, Schünemann HJ, Kurz A, Thomas S, Mrkobrada M, Thabane L, Gerstein H, Paniagua P, Nagele P, Raina P, Yusuf S, Devereaux PJ, Devereaux PJ, Sessler DI, Walsh M, Guyatt G, McQueen MJ, Bhandari M, Cook D, Bosch J, Buckley N, Yusuf S, Chow CK, Hillis GS, Halliwell R, Li S, Lee VW, Mooney J, Polanczyk CA, Furtado MV, Berwanger O, Suzumura E, Santucci E, Leite K, Santo JA, Jardim CA, Cavalcanti AB, Guimaraes HP, Jacka MJ, Graham M, McAlister F, McMurtry S, Townsend D, Pannu N, Bagshaw S, Bessissow A, Bhandari M, Duceppe E, Eikelboom J, Ganame J, Hankinson J, Hill S, Jolly S, Lamy A, Ling E, Magloire P, Pare G, Reddy D, Szalay D, Tittley J, Weitz J, Whitlock R, Darvish-Kazim S, Debeer J, Kavsak P, Kearon C, Mizera R, O’Donnell M, McQueen M, Pinthus J, Ribas S, Simunovic M, Tandon V, Vanhelder T, Winemaker M, Gerstein H, McDonald S, O’Bryne P, Patel A, Paul J, Punthakee Z, Raymer K, Salehian O, Spencer F, Walter S, Worster A, Adili A, Clase C, Cook D, Crowther M, Douketis J, Gangji A, Jackson P, Lim W, Lovrics P, Mazzadi S, Orovan W, Rudkowski J, Soth M, Tiboni M, Acedillo R, Garg A, Hildebrand A, Lam N, Macneil D, Mrkobrada M, Roshanov PS, Srinathan SK, Ramsey C, John PS, Thorlacius L, Siddiqui FS, Grocott HP, McKay A, Lee TW, Amadeo R, Funk D, McDonald H, Zacharias J, Villar JC, Cortés OL, Chaparro MS, Vásquez S, Castañeda A, Ferreira S, Coriat P, Monneret D, Goarin JP, Esteve CI, Royer C, Daas G, Chan MT, Choi GY, Gin T, Lit LC, Xavier D, Sigamani A, Faruqui A, Dhanpal R, Almeida S, Cherian J, Furruqh S, Abraham V, Afzal L, George P, Mala S, Schünemann H, Muti P, Vizza E, Wang CY, Ong GS, Mansor M, Tan AS, Shariffuddin II, Vasanthan V, Hashim NH, Undok AW, Ki U, Lai HY, Ahmad WA, Razack AH, Malaga G, Valderrama-Victoria V, Loza-Herrera JD, De Los Angeles Lazo M, Rotta-Rotta A, Szczeklik W, Sokolowska B, Musial J, Gorka J, Iwaszczuk P, Kozka M, Chwala M, Raczek M, Mrowiecki T, Kaczmarek B, Biccard B, Cassimjee H, Gopalan D, Kisten T, Mugabi A, Naidoo P, Naidoo R, Rodseth R, Skinner D, Torborg A, Paniagua P, Urrutia G, Maestre ML, Santaló M, Gonzalez R, Font A, Martínez C, Pelaez X, De Antonio M, Villamor JM, García JA, Ferré MJ, Popova E, Alonso-Coello P, Garutti I, Cruz P, Fernández C, Palencia M, Díaz S, Del Castillo T, Varela A, de Miguel A, Muñoz M, Piñeiro P, Cusati G, Del Barrio M, Membrillo MJ, Orozco D, Reyes F, Sapsford RJ, Barth J, Scott J, Hall A, Howell S, Lobley M, Woods J, Howard S, Fletcher J, Dewhirst N, Williams C, Rushton A, Welters I, Leuwer M, Pearse R, Ackland G, Khan A, Niebrzegowska E, Benton S, Wragg A, Archbold A, Smith A, McAlees E, Ramballi C, Macdonald N, Januszewska M, Stephens R, Reyes A, Paredes LG, Sultan P, Cain D, Whittle J, Del Arroyo AG, Sessler DI, Kurz A, Sun Z, Finnegan PS, Egan C, Honar H, Shahinyan A, Panjasawatwong K, Fu AY, Wang S, Reineks E, Nagele P, Blood J, Kalin M, Gibson D, Wildes TVascular events In noncardiac Surgery patIents cOhort evaluatioN (VISION) Writing Group, on behalf of The Vascular events In noncardiac Surgery patIents cOhort evaluatioN (VISION) Investigators; Appendix 1. The Vascular events In noncardiac Surgery patIents cOhort evaluatioN (VISION) Study Investigators Writing Group; Appendix 2. The Vascular events In noncardiac Surgery patIents cOhort evaluatioN Operations Committee; Vascular events In noncardiac Surgery patIents cOhort evaluatioN VISION Study Investigators. . Myocardial injury after noncardiac surgery: a large, international, prospective cohort study establishing diagnostic criteria, characteristics, predictors, and 30-day outcomes. Anesthesiology. 2014;120:564–78
13. Devereaux PJ, Chan MT, Alonso-Coello P, Walsh M, Berwanger O, Villar JC, Wang CY, Garutti RI, Jacka MJ, Sigamani A, Srinathan S, Biccard BM, Chow CK, Abraham V, Tiboni M, Pettit S, Szczeklik W, Lurati Buse G, Botto F, Guyatt G, Heels-Ansdell D, Sessler DI, Thorlund K, Garg AX, Mrkobrada M, Thomas S, Rodseth RN, Pearse RM, Thabane L, McQueen MJ, VanHelder T, Bhandari M, Bosch J, Kurz A, Polanczyk C, Malaga G, Nagele P, Le Manach Y, Leuwer M, Yusuf S. Association between postoperative troponin levels and 30-day mortality among patients undergoing noncardiac surgery. JAMA. 2012;307:2295–304
14. Kavsak PA, Walsh M, Srinathan S, Thorlacius L, Buse GL, Botto F, Pettit S, McQueen MJ, Hill SA, Thomas S, Mrkobrada M, Alonso-Coello P, Berwanger O, Biccard BM, Cembrowski G, Chan MT, Chow CK, de Miguel A, Garcia M, Graham MM, Jacka MJ, Kueh JH, Li SC, Lit LC, Martínez-Brú C, Naidoo P, Nagele P, Pearse RM, Rodseth RN, Sessler DI, Sigamani A, Szczeklik W, Tiboni M, Villar JC, Wang CY, Xavier D, Devereaux PJ. High sensitivity troponin T concentrations in patients undergoing noncardiac surgery: a prospective cohort study. Clin Biochem. 2011;44:1021–4
15. Nagele P, Brown F, Gage BF, Gibson DW, Miller JP, Jaffe AS, Apple FS, Scott MG. High-sensitivity cardiac troponin T in prediction and diagnosis of myocardial infarction and long-term mortality after noncardiac surgery. Am Heart J. 2013;166:325–32.e1
16. van Waes JA, Nathoe HM, de Graaff JC, Kemperman H, de Borst GJ, Peelen LM, van Klei WACardiac Health After Surgery (CHASE) Investigators. . Myocardial injury after noncardiac surgery and its association with short-term mortality. Circulation. 2013;127:2264–71
17. Foucrier A, Rodseth R, Aissaoui M, Ibanes C, Goarin JP, Landais P, Coriat P, Le Manach Y. The long-term impact of early cardiovascular therapy intensification for postoperative troponin elevation after major vascular surgery. Anesth Analg. 2014;119:1053–63
18. Beckman JA. Postoperative troponin screening: a cardiac Cassandra? Circulation. 2013;127:2253–6
19. Nathoe HM, van Klei WA, Beattie WS. Perioperative troponin elevation: always myocardial injury, but not always myocardial infarction. Anesth Analg. 2014;119:1014–6
20. Lee TH, Goldman L. Letter by Lee and Goldman regarding article, “Development and validation of a risk calculator for prediction of cardiac risk after surgery”. Circulation. 2012;125:e385
21. Gupta PK, Franck C, Miller WJ, Gupta H, Forse RA. Development and validation of a bariatric surgery morbidity risk calculator using the prospective, multicenter NSQIP dataset. J Am Coll Surg. 2011;212:301–9
22. Gupta PK, Gupta H, Sundaram A, Kaushik M, Fang X, Miller WJ, Esterbrooks DJ, Hunter CB, Pipinos II, Johanning JM, Lynch TG, Forse RA, Mohiuddin SM, Mooss AN. Development and validation of a risk calculator for prediction of cardiac risk after surgery. Circulation. 2011;124:381–7
23. Gupta PK, Ramanan B, Lynch TG, Sundaram A, MacTaggart JN, Gupta H, Fang X, Pipinos II. Development and validation of a risk calculator for prediction of mortality after infrainguinal bypass surgery. J Vasc Surg. 2012;56:372–9
24. Cohen ME, Ko CY, Bilimoria KY, Zhou L, Huffman K, Wang X, Liu Y, Kraemer K, Meng X, Merkow R, Chow W, Matel B, Richards K, Hart AJ, Dimick JB, Hall BL. Optimizing ACS NSQIP modeling for evaluation of surgical quality and risk: patient risk adjustment, procedure mix adjustment, shrinkage adjustment, and surgical focus. J Am Coll Surg. 2013;217:336–46.e1
25. Fleisher LA, Fleischmann KE, Auerbach AD, Barnason SA, Beckman JA, Bozkurt B, Davila-Roman VG, Gerhard-Herman MD, Holly TA, Kane GC, Marine JE, Nelson MT, Spencer CC, Thompson A, Ting HH, Uretsky BF, Wijeysundera DN. 2014 ACC/AHA guideline on perioperative cardiovascular evaluation and management of patients undergoing noncardiac surgery: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation. 2014;64:e77–e137
26. Steptoe A, Kivimäki M. Stress and cardiovascular disease. Nat Rev Cardiol. 2012;9:360–70
27. Curigliano G, Cardinale D, Suter T, Plataniotis G, de Azambuja E, Sandri MT, Criscitiello C, Goldhirsch A, Cipolla C, Roila F. Cardiovascular toxicity induced by chemotherapy, targeted agents and radiotherapy: ESMO Clinical Practice Guidelines. Ann Oncol. 2012;23(Suppl 7):vii155–66
28. Zanni MV, Schouten J, Grinspoon SK, Reiss P. Risk of coronary heart disease in patients with HIV infection. Nat Rev Cardiol. 2014;11:728–41
29. Post WS, Budoff M, Kingsley L, Palella FJ Jr, Witt MD, Li X, George RT, Brown TT, Jacobson LP. Associations between HIV infection and subclinical coronary atherosclerosis. Ann Intern Med. 2014;160:458–67
30. Goff DC Jr, Lloyd-Jones DM, Bennett G, Coady S, D’Agostino RB, Gibbons R, Greenland P, Lackland DT, Levy D, O’Donnell CJ, Robinson JG, Schwartz JS, Shero ST, Smith SC Jr, Sorlie P, Stone NJ, Wilson PW, Jordan HS, Nevo L, Wnek J, Anderson JL, Halperin JL, Albert NM, Bozkurt B, Brindis RG, Curtis LH, DeMets D, Hochman JS, Kovacs RJ, Ohman EM, Pressler SJ, Sellke FW, Shen WK, Smith SC Jr, Tomaselli GFAmerican College of Cardiology/American Heart Association Task Force on Practice Guidelines. . 2013 ACC/AHA guideline on the assessment of cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation. 2014;129:S49–73
31. Stone NJ, Robinson JG, Lichtenstein AH, Bairey Merz CN, Blum CB, Eckel RH, Goldberg AC, Gordon D, Levy D, Lloyd-Jones DM, McBride P, Schwartz JS, Shero ST, Smith SC Jr, Watson K, Wilson PW, Eddleman KM, Jarrett NM, LaBresh K, Nevo L, Wnek J, Anderson JL, Halperin JL, Albert NM, Bozkurt B, Brindis RG, Curtis LH, DeMets D, Hochman JS, Kovacs RJ, Ohman EM, Pressler SJ, Sellke FW, Shen WK, Smith SC Jr, Tomaselli GFAmerican College of Cardiology/American Heart Association Task Force on Practice Guidelines. . 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation. 2014;129:S1–45
32. Maddox TM, Stanislawski MA, Grunwald GK, Bradley SM, Ho PM, Tsai TT, Patel MR, Sandhu A, Valle J, Magid DJ, Leon B, Bhatt DL, Fihn SD, Rumsfeld JS. Nonobstructive coronary artery disease and risk of myocardial infarction. JAMA. 2014;312:1754–63
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