Medical history for prognostic risk assessment and diagnosis of stable patients with suspected coronary artery disease

Min JK, Dunning A, Gransar H, Achenbach S, Lin FY, Al-Mallah M, Budoff MJ, Callister TQ, Chang HJ, Cademartiri F, Maffei E, Chinnaiyan K, Chow BJW, D'Agostino R, Delago A, Friedman J, Hadamitzky M, Hausleiter J, Hayes SW, Kaufmann P, Raff GL, Shaw LJ, Thomson L, Villines T, Cury RC, Feuchtner G, Kim YJ, Leipsic J, Marques H, Berman DS, Pencina M (2015)

Publication Type: Journal article

Publication year: 2015

Journal

Book Volume: 128

Pages Range: 871-8

Journal Issue: 8

DOI: 10.1016/j.amjmed.2014.10.031

Abstract

To develop a clinical cardiac risk algorithm for stable patients with suspected coronary artery disease based upon angina typicality and coronary artery disease risk factors.Between 2004 and 2011, 14,004 adults with suspected coronary artery disease referred for cardiac imaging were followed: 1) 9093 patients for coronary computed tomography angiography (CCTA) followed for 2.0 years (CCTA-1); 2) 2132 patients for CCTA followed for 1.6 years (CCTA-2); and 3) 2779 patients for exercise myocardial perfusion scintigraphy (MPS) followed for 5.0 years. A best-fit model from CCTA-1 for prediction of death or myocardial infarction was developed, with integer values proportional to regression coefficients. Discrimination was assessed using C-statistic. The validated model was tested for estimation of the likelihood of obstructive coronary artery disease, defined as >=50% stenosis, as compared with the method of Diamond and Forrester. Primary outcomes included all-cause mortality and nonfatal myocardial infarction. Secondary outcomes included prevalent angiographically obstructive coronary artery disease.In CCTA-1, best-fit model discriminated individuals at risk of death or myocardial infarction (C-statistic 0.76). The integer model ranged from 3 to 13, corresponding to 3-year death risk or myocardial infarction of 0.25% to 53.8%. When applied to CCTA-2 and MPS cohorts, the model demonstrated C-statistics of 0.71 and 0.77, respectively. Both best-fit (C = 0.76; 95% confidence interval [CI], 0.746-0.771) and integer models (C = 0.71; 95% CI, 0.693-0.719) performed better than Diamond and Forrester (C = 0.64; 95% CI, 0.628-0.659) for estimating obstructive coronary artery disease.For stable symptomatic patients with suspected coronary artery disease, we developed a history-based method for prediction of death and obstructive coronary artery disease.

Authors with CRIS profile

Involved external institutions

Baptist Health South Florida United States (USA) (US) Cornell University United States (USA) (US) Cedars-Sinai Medical Center United States (USA) (US) New York Presbyterian Hospital United States (USA) (US) Wayne State University (WSU) United States (USA) (US) Tennessee Heart & Vascular United States (USA) (US) Yonsei University Health System (YUHS) Korea, Republic of (KR) Casa di Cura Giovanni XXIII Italy (IT) Beaumont Health System United States (USA) (US) University of Ottawa Canada (CA) Boston University United States (USA) (US) Capitol Cardiology Associates United States (USA) (US) Deutsches Herzzentrum München Germany (DE) Ludwig-Maximilians-Universität (LMU) Germany (DE) Emory University United States (USA) (US) Walter Reed Army Medical Center (WRAMC) United States (USA) (US) Medizinische Universität Innsbruck Austria (AT) Seoul National University (SNU) / 서울대학교 Korea, Republic of (KR) University of British Columbia Canada (CA) Hospital da Luz Portugal (PT) Universitätsspital Zürich (USZ) Switzerland (CH)

How to cite

APA:

Min, J.K., Dunning, A., Gransar, H., Achenbach, S., Lin, F.Y., Al-Mallah, M.,... Pencina, M. (2015). Medical history for prognostic risk assessment and diagnosis of stable patients with suspected coronary artery disease. American Journal of Medicine, 128(8), 871-8. https://doi.org/10.1016/j.amjmed.2014.10.031

MLA:

Min, James K., et al. "Medical history for prognostic risk assessment and diagnosis of stable patients with suspected coronary artery disease." American Journal of Medicine 128.8 (2015): 871-8.

BibTeX: Download