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November 30, 2021 Circulation. 2021;144:e368–e454. DOI: 10.1161/CIR.0000000000001029 e436 CLINICAL STATEMENTS AND GUIDELINES 27 Altintas E, Yigit F, Taskintuna N. The impact of psychiatric disorders with cardiac syndrome X on quality of life: 3 months prospective study. Int J Clin Exp Med. 2014;7:3520–3527. 28. Schwarz J, Prashad A, Winchester DE. Prevalence and implications of severe anxiety in a prospective cohort of acute chest pain patients. Crit Pathw Cardiol. 2015;14:44–47. 29. Foldes-Busque G, Denis I, Poitras J, et al. A closer look at the relationships between panic attacks, emergency department visits and non-cardiac chest pain. J Health Psychol. 2017; 1359105316683785. 30. Campbell KA, Madva EN, Villegas AC, et al. Non-cardiac chest pain: a review for the consultation-liaison psychiatrist. Psychosomatics. 2017;58:252–265. 4.3.3 Evaluation of Acute Chest Pain in Patients With Sickle Cell Disease 1. Platt OS, Brambilla DJ, Rosse WF, et al. Mortality in sickle cell disease. Life expectancy and risk factors for early death. N Engl J Med. 1994;330:1639–1644. 2. Thomas AN, Pattison C, Serjeant GR. Causes of death in sickle-cell disease in Jamaica. Br Med J (Clin Res Ed). 1982;285:633–635. 3. Vichinsky EP, Styles LA, Colangelo LH, et al. Acute chest syndrome in sickle cell disease: clinical presentation and course. Cooperative Study of Sickle Cell Disease. Blood. 1997;89:1787–1792. 4. Martin CR, Johnson CS, Cobb C, et al. Myocardial infarction in sickle cell disease. J Natl Med Assoc. 1996;88:428–432. 5. Ogunbayo GO, Misumida N, Olorunfemi O, et al. Comparison of outcomes in patients having acute myocardial infarction with versus without sickle-cell anemia. Am J Cardiol. 2017;120:1768–1771. 5 EVALUATION OF PATIENTS WITH STABLE CHEST PAIN 5.1 Patients With No Known CAD Presenting With Stable Chest Pain 1 Juarez-Orozco LE, Saraste A, Capodanno D, et al. Impact of a decreasing pre-test probability on the performance of diagnostic tests for coronary artery disease. Eur Heart J Cardiovasc Imaging. 2019;20:1198–1207. 2. Winther S, Schmidt SE, Mayrhofer T, et al. Incorporating coronary calcifica- tion into pre-test assessment of the likelihood of coronary artery disease. J Am Coll Cardiol. 2020;76:2421–2432. 5.1.1 Pretest Risk Probability to Guide Need for Stress and Anatomic Tests 1 Juarez-Orozco LE, Saraste A, Capodanno D, et al. Impact of a decreasing pre-test probability on the performance of diagnostic tests for coronary artery disease. Eur Heart J Cardiovasc Imaging. 2019;20:1198–1207. 2. Winther S, Schmidt SE, Mayrhofer T, et al. Incorporating coronary calcification into pre-test assessment of the likelihood of coronary artery disease. J Am Coll Cardiol. 2020;76:2421–2432. 3. Genders TS, Steyerberg EW, Alkadhi H, et al. A clinical prediction rule for the diagnosis of coronary artery disease: validation, updating, and extension. Eur Heart J. 2011;32:1316–1330. 4. Fordyce CB, Douglas PS, Roberts RS, et al. Identification of patients with stable chest pain deriving minimal value from noninvasive testing: the PROMISE minimal-risk tool, a secondary analysis of a randomized clinical trial. JAMA Cardiol. 2017;2:400–408. 5. Genders TS, Steyerberg EW, Hunink MG, et al. Prediction model to estimate presence of coronary artery disease: retrospective pooled analysis of existing cohorts. BMJ. 2012;344:e3485. 5.1.2 Low-Risk Patients With Stable Chest Pain and No Known CAD 1. Genders TS, Steyerberg EW, Alkadhi H, et al. A clinical prediction rule for the diagnosis of coronary artery disease: validation, updating, and extension. Eur Heart J. 2011;32:1316–1330. 2. Fordyce CB, Douglas PS, Roberts RS, et al. Identification of patients with stable chest pain deriving minimal value from noninvasive testing: the PROMISE minimal-risk tool, a secondary analysis of a randomized clinical trial. JAMA Cardiol. 2017;2:400–408. 3. Genders TS, Steyerberg EW, Hunink MG, et al. Prediction model to estimate presence of coronary artery disease: retrospective pooled analysis of existing cohorts. BMJ. 2012;344:e3485. 4. Juarez-Orozco LE, Saraste A, Capodanno D, et al. Impact of a decreasing pre-test probability on the performance of diagnostic tests for coronary artery disease. Eur Heart J Cardiovasc Imaging. 2019;20:1198–1207. 5. Winther S, Schmidt SE, Mayrhofer T, et al. Incorporating coronary calcification into pre-test assessment of the likelihood of coronary artery disease. J Am Coll Cardiol. 2020;76:2421–2432. 6. Lubbers M, Coenen A, Kofflard M, et al. Comprehensive cardiac CT with myocardial perfusion imaging versus functional testing in suspected coronary artery disease: the multicenter, randomized CRESCENT-II trial. J Am Coll Cardiol Img. 2018;11:1625–1636. 7. Lubbers M, Dedic A, Coenen A, et al. Calcium imaging and selective computed tomography angiography in comparison to functional testing for suspected coronary artery disease: the multicentre, randomized CRESCENT trial. Eur Heart J. 2016;37:1232–1243. 8. Chang SM, Nabi F, Xu J, et al. The coronary artery calcium score and stress myocardial perfusion imaging provide independent and complementary prediction of cardiac risk. J Am Coll Cardiol. 2009;54:1872–1882. 9. Budoff MJ, Mayrhofer T, Ferencik M, et al. Prognostic value of coronary artery calcium in the PROMISE study (prospective multicenter imaging study for evaluation of chest pain) Circulation. 2017;136:1993–2005. 10. Shaw LJ, Mieres JH, Hendel RH, et al. Comparative effectiveness of exercise electrocardiography with or without myocardial perfusion single photon emission computed tomography in women with suspected coronary artery disease: results from the What Is the Optimal Method for Ischemia Evaluation in Women (WOMEN) trial. Circulation. 2011;124:1239–1249. 11. Douglas PS, Hoffmann U. Anatomical versus functional testing for coronary artery disease. N Engl J Med. 2015;373:91. 12. Hochman JS, Reynolds HR, Bangalore S, et al. Baseline characteristics and risk profiles of participants in the ISCHEMIA randomized clinical trial. JAMA Cardiol. 2019;4:273–286. 13. Spertus JA, Jones PG, Maron DJ, et al. Health status after invasive or conservative care in coronary and advanced kidney disease. N Engl J Med. 2020;382:1619–1628. 14. Rozanski A, Gransar H, Hayes SW, et al. Temporal trends in the frequency of inducible myocardial ischemia during cardiac stress testing: 1991 to 2009 J Am Coll Cardiol. 2013;61:1054–1065. 15. Cheng VY, Berman DS, Rozanski A, et al. Performance of the traditional age, sex, and angina typicality-based approach for estimating pretest probability of angiographically significant coronary artery disease in patients undergoing coronary computed tomographic angiography: results from the multinational coronary CT angiography evaluation for clinical outcomes: an international multicenter registry (CONFIRM) Circulation. 2011;124:2423–2432; 1-8. 16. Baskaran L, Danad I, Gransar H, et al. A comparison of the updated Diamond-Forrester, CAD Consortium, and CONFIRM history-based risk scores for predicting obstructive coronary artery disease in patients with stable chest pain: the SCOT-HEART Coronary CTA cohort. J Am Coll Cardiol Img. 2019;12:1392–1400. 17. Ferreira AM, Marques H, Tralhao A, et al. Pre-test probability of obstructive coronary stenosis in patients undergoing coronary CT angiography: comparative performance of the modified diamond-Forrester algorithm versus methods incorporating cardiovascular risk factors. Int J Cardiol. 2016;222:346–351. 18. Foldyna B, Udelson JE, Karady J, et al. Pretest probability for patients with suspected obstructive coronary artery disease: re-evaluating Diamond-Forrester for the contemporary era and clinical implications: insights from the PROMISE trial. Eur Heart J Cardiovasc Imaging. 2019;20:574–581. 19. Bittencourt MS, Hulten E, Polonsky TS, et al. European Society of Cardiology-recommended coronary artery disease consortium pretest probability scores more accurately predict obstructive coronary disease and cardiovascular events than the Diamond and Forrester score: the Partners registry. Circulation. 2016;134:201–211. 20. Patel MR, Peterson ED, Dai D, et al. Low diagnostic yield of elective coronary angiography. N Engl J Med. 2010;362:886–895. 21. Patel MR, Dai D, Hernandez AF, et al. Prevalence and predictors of nonobstructive coronary artery disease identified with coronary angiography in contemporary clinical practice. Am Heart J. 2014;167:846–852 e2. 22. Knuuti J, Wijns W, Saraste A, et al. 2019 ESC guidelines for the diag- nosis and management of chronic coronary syndromes. Eur Heart J. 2020;41:407–477. Downloaded from http://ahajournals.org by on October 7, 2026