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


Abstract

AIMS: 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.
METHODS AND RESULTS: Between 2004 and 2011, 14,004 adults with suspected coronary artery disease referred for cardiac imaging were followed: 1) 9,093 patients for coronary computed tomography angiography (CCTA) (CCTA-1) followed for 2.0 years; 2) 2,132 patients for CCTA (CCTA-2) followed for 1·6 years, and 3) 2,779 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 to method of Diamond and Forrester. Primary outcomes included all-cause mortality and non-fatal 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 3-13, 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. Both best-fit (C=0·76, 95% 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.
CONCLUSIONS: For stable symptomatic patients with suspected coronary artery disease, we developed a history-based method for prediction of death and obstructive coronary artery disease.

AIMS: 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.
METHODS AND RESULTS: Between 2004 and 2011, 14,004 adults with suspected coronary artery disease referred for cardiac imaging were followed: 1) 9,093 patients for coronary computed tomography angiography (CCTA) (CCTA-1) followed for 2.0 years; 2) 2,132 patients for CCTA (CCTA-2) followed for 1·6 years, and 3) 2,779 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 to method of Diamond and Forrester. Primary outcomes included all-cause mortality and non-fatal 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 3-13, 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. Both best-fit (C=0·76, 95% 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.
CONCLUSIONS: For stable symptomatic patients with suspected coronary artery disease, we developed a history-based method for prediction of death and obstructive coronary artery disease.

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2 citations in Web of Science®
5 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Nuclear Medicine
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:9 April 2015
Deposited On:22 Apr 2015 15:46
Last Modified:05 Apr 2016 19:13
Publisher:Elsevier
ISSN:0002-9343
Publisher DOI:https://doi.org/10.1016/j.amjmed.2014.10.031
PubMed ID:25865923

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