Coronary artery disease grading by cardiac CT for predicting outcome in patients with stable angina
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
Background: The coronary atheroma burden drives major adverse cardiovascular events (MACE) in patients with suspected coronary heart disease (CHD). However, a consensus on how to grade disease burden for effective risk stratification is lacking. The purpose of this study was to compare the effectiveness of common CHD grading tools to risk stratify symptomatic patients. Methods: We analyzed the 5-year outcome of 381 prospectively enrolled patients in the CORE320 international, multicenter study using baseline clinical and cardiac computer-tomography (CT) imaging characteristics, including coronary artery calcium score (CACS), percent atheroma volume, “high-risk” plaque, disease severity grading using the CAD-RADS, and two simplified CAD staging systems. We applied Cox proportional hazard models and area under the curve (AUC) analysis to predict MACE or hard MACE, defined as death, myocardial infarction, or stroke. Analyses were stratified by a history of CHD. Additional forward selection analysis was performed to evaluate incremental value of metrics. Results: Clinical characteristics were the strongest predictors of MACE in the overall cohort. In patients without history of CHD, CACS remained the only independent predictor of MACE yielding an AUC of 73 (CI 67–79) vs. 64 (CI 57–70) for clinical characteristics. Noncalcified plaque volume did not add prognostic value. Simple CHD grading schemes yielded similar risk stratification as the CAD-RADS classification. Forward selection analysis confirmed prominent role of CACS and revealed usefulness of functional testing in subgroup with known CHD. Conclusion: In patients referred for invasive angiography, a history of CHD was the strongest predictor of MACE. In patients without history of CHD, a coronary calcium score yielded at least equal risk stratification vs. more complex CHD grading.
| Originalsprog | Engelsk |
|---|---|
| Tidsskrift | Journal of Cardiovascular Computed Tomography |
| Vol/bind | 17 |
| Udgave nummer | 5 |
| Sider (fra-til) | 310-317 |
| Antal sider | 8 |
| ISSN | 1934-5925 |
| DOI | |
| Status | Udgivet - 2023 |
Bibliografisk note
Funding Information:
This work was funded in part by intramural research support from the NHLBI, National Institutes of Health, USA . The CORE320 cross-sectional study was funded by Canon Medical Systems .
Funding Information:
The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: This work was funded in part by intramural research support from the NHLBI, National Institutes of Health, USA. The CORE320 cross-sectional study was funded by Canon Medical Systems. Dr. Zadeh discloses research grant support from Canon Medical Systems. Dr. Schuijf is a full-time employee of Canon Medical Systems Europe BV. Dr. Dewey discloses institutional research agreements with Siemens, General Electric, Philips, Canon; a patent on fractal analysis of perfusion imaging (jointly with Florian Michallek, PCT/EP2016/071,551 and USPTO 2021 10,991,109 approved); Grants: EU (EC-GA 603266 in HEALTH.2013.2.4.2–2) DFG (DE 1361/14–1, DE 1361/18–1, BIOQIC GRK 2260/1, Radiomics DE 1361/19–1 [428,222,922] and 20–1 [428223139] in SPP 2177/1), Berlin University Alliance (GC_SC_PC 27), Berlin Institute of Health (Digital Health Accelerator). Other authors declare no relevant disclosures. Dr. Oeing discloses institutional funding by DFG (OE 688/4–1) and support by the DZHK (Deutsches Zentrum für Herz-Kreislauf-Forschung).
Funding Information:
Dr. Zadeh discloses research grant support from Canon Medical Systems. Dr. Schuijf is a full time employee of Canon Medical Systems Europe BV. Dr. Dewey discloses institutional research agreements with Siemens, General Electric, Philips, Canon; a patent on fractal analysis of perfusion imaging (jointly with Florian Michallek, PCT/EP2016/071,551 and USPTO 2021 10,991,109 approved); grants: EU (EC-GA 603266 in HEALTH.2013.2.4.2–2), DFG (DE 1361/14–1, DE 1361/18–1, BIOQIC GRK 2260/1, Radiomics DE 1361/19–1 [428,222,922] and 20–1 [428223139] in SPP 2177/1), Berlin University Alliance (GC_SC_PC 27), Berlin Institute of Health (Digital Health Accelerator). Dr. Oeing discloses institutional funding by DFG (OE 688/4–1) and support by the DZHK (Deutsches Zentrum für Herz-Kreislauf-Forschung).
Publisher Copyright:
© 2023 Society of Cardiovascular Computed Tomography
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