Comparison of recent ceramide-based coronary risk prediction scores in cardiovascular disease patients
Autor: | Heinz Drexel, Andreas Leiherer, Mitja Lääperi, Reijo Laaksonen, Antti Jylhä, Axel Mündlein, Peter Fraunberger |
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Rok vydání: | 2021 |
Předmět: |
Ceramide
medicine.medical_specialty Framingham Risk Score Epidemiology Cholesterol business.industry Hazard ratio Disease Ceramides Risk Assessment chemistry.chemical_compound chemistry Cardiovascular Diseases Risk Factors Integrated discrimination improvement Coronary risk Internal medicine Phosphatidylcholines Humans Medicine Cardiology and Cardiovascular Medicine business Cohort study |
Zdroj: | European Journal of Preventive Cardiology. 29:947-956 |
ISSN: | 2047-4881 2047-4873 |
Popis: | AimCholesterol-based risk prediction is often insufficient in cardiovascular disease (CVD) patients. Ceramides are a new kind of biomarkers for CVD. The Coronary Event Risk Test (CERT) is a validated cardiovascular risk predictor that uses only circulating ceramide levels, determined by coupled liquid chromatography–mass spectrometry, to allocate patients into one of four risk categories. This test has recently been modified (CERT2) by additionally including phosphatidylcholine levels.Methods and resultsIn this observational cohort study, we have recruited 999 Austrian patients with CVD and followed them for up to 13 years. We found that CERT and CERT2 both predicted cardiovascular events, cardiovascular mortality, and overall mortality. CERT2 had the higher performance compared to CERT and also to the recent cardiovascular risk score of the ESC/EAS guidelines (Systematic COronary Risk Evaluation (SCORE)) for low-risk European countries. Combining CERT2 with the ESC/EAS-SCORE, predictive capacity was further increased leading to a hazard ratio of 3.58 (2.02–6.36; P ConclusionWe conclude that CERT and CERT2 are powerful predictors of cardiovascular events, cardiovascular mortality, and overall mortality in CVD patients. Including phosphatidylcholine to a ceramide-based score increases the predictive performance and is best in combination with classical risk factors as used in the ESC/EAS-SCORE. |
Databáze: | OpenAIRE |
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