[1] Writing Committee for the VISION Study Investigators, Devereaux PJ, Biccard BM, et al. Association of postoperative high-sensitivity troponin levels with myocardial injury and 30-day mortality among patients undergoing noncardiac surgery. JAMA, 2017; 317, 1642−51. doi:  10.1001/jama.2017.4360
[2] Weiser TG, Regenbogen SE, Thompson KD, et al. An estimation of the global volume of surgery: a modelling strategy based on available data. Lancet, 2008; 372, 139−44. doi:  10.1016/S0140-6736(08)60878-8
[3] Polanczyk CA, Goldman L, Marcantonio ER, et al. Supraventricular arrhythmia in patients having noncardiac surgery: clinical correlates and effect on length of stay. Ann Intern Med, 1998; 129, 279−85. doi:  10.7326/0003-4819-129-4-199808150-00003
[4] Fleisher LA, Beckman JA, Brown KA, et al. ACC/AHA 2007 guidelines on perioperative cardiovascular evaluation and care for noncardiac surgery: executive summary: a report of the american college of cardiology/american heart association task force on practice guidelines (writing committee to revise the 2002 guidelines on perioperative cardiovascular evaluation for noncardiac surgery). Anesth Analg, 2008; 106, 685−712. doi:  10.1213/01/ane.0000309024.28586.70
[5] Devereaux PJ, Goldman L, Yusuf S, et al. Surveillance and prevention of major perioperative ischemic cardiac events in patients undergoing noncardiac surgery: a review. Can Med Assoc J, 2005; 173, 779−88. doi:  10.1503/cmaj.050316
[6] Kristensen SD, Knuuti J, Saraste A, et al. 2014 ESC/ESA Guidelines on non-cardiac surgery: cardiovascular assessment and management: the Joint Task Force on non-cardiac surgery: cardiovascular assessment and management of the European Society of Cardiology (ESC) and the European Society of Anaesthesiology (ESA). Eur J Anaesthesiol, 2014; 31, 517−73. doi:  10.1097/EJA.0000000000000150
[7] Pearse RM, Moreno RP, Bauer P, et al. Mortality after surgery in Europe: a 7 day cohort study. Lancet, 2012; 380, 1059−65. doi:  10.1016/S0140-6736(12)61148-9
[8] Rodseth RN, Biccard BM, Le Manach Y, et al. The prognostic value of pre-operative and post-operative B-type natriuretic peptides in patients undergoing noncardiac surgery. J Am Coll Cardiol, 2014; 63, 170−80. doi:  10.1016/j.jacc.2013.08.1630
[9] Maile MD, Jewell ES, Engoren MC. Timing of preoperative troponin elevations and postoperative mortality after noncardiac surgery. Anesth Analg, 2016; 123, 135−40. doi:  10.1213/ANE.0000000000001309
[10] Larmann J, Handke J, Scholz AS, et al. Preoperative neutrophil to lymphocyte ratio and platelet to lymphocyte ratio are associated with major adverse cardiovascular and cerebrovascular events in coronary heart disease patients undergoing non-cardiac surgery. BMC Cardiovasc Disord, 2020; 20, 230. doi:  10.1186/s12872-020-01500-6
[11] Shaydenfish D, Scheffenbichler FT, Kelly BJ, et al. Effects of anticholinesterase reversal under general anesthesia on postoperative cardiovascular complications: a retrospective cohort study. Anesth Analg, 2020; 130, 685−95. doi:  10.1213/ANE.0000000000004099
[12] Nicklas JY, Diener O, Leistenschneider M, et al. Personalised haemodynamic management targeting baseline cardiac index in high-risk patients undergoing major abdominal surgery: a randomised single-centre clinical trial. Br J Anaesth, 2020; 125, 122−32. doi:  10.1016/j.bja.2020.04.094
[13] Gan TJ. Poorly controlled postoperative pain: prevalence, consequences, and prevention. J Pain Res, 2017; 10, 2287−98. doi:  10.2147/JPR.S144066
[14] Khuri SF, Henderson WG, Depalma RG, et al. Determinants of long-term survival after major surgery and the adverse effect of postoperative complications. Ann Surg, 2005; 242, 326−43. doi:  10.1097/01.sla.0000179621.33268.83
[15] Dimick JB, Chen SL, Taheri PA, et al. Hospital costs associated with surgical complications: a report from the private-sector national surgical quality improvement program. J Am Coll Surg, 2004; 199, 531−7. doi:  10.1016/j.jamcollsurg.2004.05.276
[16] Eappen S, Lane BH, Rosenberg B, et al. Relationship between occurrence of surgical complications and hospital finances. JAMA, 2013; 309, 1599−606. doi:  10.1001/jama.2013.2773
[17] Wijeysundera DN, Pearse RM, Shulman MA, et al. Assessment of functional capacity before major non-cardiac surgery: an international, prospective cohort study. Lancet, 2018; 391, 2631−40. doi:  10.1016/S0140-6736(18)31131-0
[18] Lee TH, Marcantonio ER, Mangione CM, et al. Derivation and prospective validation of a simple index for prediction of cardiac risk of major noncardiac surgery. Circulation, 1999; 100, 1043−9. doi:  10.1161/01.CIR.100.10.1043
[19] Gupta PK, Gupta H, Sundaram A, et al. Development and validation of a risk calculator for prediction of cardiac risk after surgery. Circulation, 2011; 124, 381−7. doi:  10.1161/CIRCULATIONAHA.110.015701
[20] Bilimoria KY, Liu YM, Paruch JL, et al. Development and evaluation of the universal ACS NSQIP surgical risk calculator: a decision aid and informed consent tool for patients and surgeons. J Am Coll Surg, 2013; 217, 833-42. e3.
[21] Miotto R, Wang F, Wang S, et al. Deep learning for healthcare: review, opportunities and challenges. Brief Bioinform, 2018; 19, 1236−46. doi:  10.1093/bib/bbx044
[22] Oh AR, Park J, Shin SJ, et al. Prediction model for myocardial injury after non-cardiac surgery using machine learning. Sci Rep, 2023; 13, 1475. doi:  10.1038/s41598-022-26617-w
[23] Shin SJ, Park J, Lee SH, et al. Predictability of mortality in patients with myocardial injury after noncardiac surgery based on perioperative factors via machine learning: retrospective study. JMIR Med Inform, 2021; 9, e32771. doi:  10.2196/32771
[24] Weng SF, Reps J, Kai J, et al. Can machine-learning improve cardiovascular risk prediction using routine clinical data? PLoS One, 2017; 12, e0174944.
[25] Goldstein BA, Navar AM, Carter RE. Moving beyond regression techniques in cardiovascular risk prediction: applying machine learning to address analytic challenges. Eur Heart J, 2017; 38, 1805−14.
[26] Canet J, Gallart L, Gomar C, et al. Prediction of postoperative pulmonary complications in a population-based surgical cohort. Anesthesiology, 2010; 113, 1338−50. doi:  10.1097/ALN.0b013e3181fc6e0a
[27] Cao SJ, Zhang Y, Zhang YX, et al. Long-term survival in older patients given propofol or sevoflurane anaesthesia for major cancer surgery: follow-up of a multicentre randomised trial. Br J Anaesth, 2023; 131, 266−75. doi:  10.1016/j.bja.2023.01.023
[28] Kursa MB, Rudnicki WR. Feature selection with the boruta package. J Stat Software, 2010; 36, 1−13.
[29] Riley RD, Snell KI, Ensor J, et al. Minimum sample size for developing a multivariable prediction model: PART II - binary and time-to-event outcomes. Stat Med, 2019; 38, 1276−96. doi:  10.1002/sim.7992
[30] Fleisher LA, Fleischmann KE, Auerbach AD, et al. 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; 130, E278−333.
[31] Devereaux PJ, Sessler DI. Cardiac complications in patients undergoing major noncardiac surgery. N Engl J Med, 2015; 373, 2258−69. doi:  10.1056/NEJMra1502824
[32] Zhang XY, Zhang WX, Lou HY, et al. Risk factors for prolonged intensive care unit stays in patients after cardiac surgery with cardiopulmonary bypass: a retrospective observational study. Int J Nurs Sci, 2021; 8, 388−93.
[33] Aseni P, Orsenigo S, Storti E, et al. Current concepts of perioperative monitoring in high-risk surgical patients: a review. Patient Saf Surg, 2019; 13, 32. doi:  10.1186/s13037-019-0213-5
[34] Kristensen SD, Knuuti J, Saraste A, et al. 2014 ESC/ESA Guidelines on non-cardiac surgery: cardiovascular assessment and management: the Joint Task Force on non-cardiac surgery: cardiovascular assessment and management of the European Society of Cardiology (ESC) and the European Society of Anaesthesiology (ESA). Eur Heart J, 2014; 35, 2383−431. doi:  10.1093/eurheartj/ehu282
[35] London MJ, Hur K, Schwartz GG. Association of perioperative β-blockade with mortality and cardiovascular morbidity following major noncardiac surgery. J Vasc Surg, 2013; 58, 550.
[36] Lloyd-Jones DM, Wang TJ, Leip EP, et al. Lifetime risk for development of atrial fibrillation: the framingham heart study. Circulation, 2004; 110, 1042−6. doi:  10.1161/01.CIR.0000140263.20897.42
[37] Charlson ME, Pompei P, Ales KL, et al. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis, 1987; 40, 373−83. doi:  10.1016/0021-9681(87)90171-8
[38] Mangano DT, Tudor IC, Dietzel C. The risk associated with aprotinin in cardiac surgery. N Engl J Med, 2006; 354, 353−65. doi:  10.1056/NEJMoa051379
[39] Xin NX, Yan W, Jin SF. Efficacy of analgesic propofol/esketamine and propofol/fentanyl for painless induced abortion: a randomized clinical trial. Biomed Res Int, 2022; 2022, 5095282.
[40] Chawla NV, Bowyer KW, Hall LO, et al. SMOTE: synthetic minority over-sampling technique. J Artif Intell Res, 2002; 16, 321−57. doi:  10.1613/jair.953
[41] Han H, Wang WY, Mao BH. Borderline-SMOTE: a new over-sampling method in imbalanced data sets learning. In: Proceedings of the International Conference on Intelligent Computing on Advances in Intelligent Computing. Springer. 2005, 878-87.
[42] Lang M, Binder M, Richter J, et al. mlr3: a modern object-oriented machine learning framework in R. J Open Sour Softw, 2019; 4, 1903. doi:  10.21105/joss.01903
[43] Petch J, Di S, Nelson W. Opening the black box: the promise and limitations of explainable machine learning in cardiology. Can J Cardiol, 2022; 38, 204−13. doi:  10.1016/j.cjca.2021.09.004