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Atherosclerotic Cardiovascular Risk Stratification in the Rheumatic Diseases:: An Integrative, Multiparametric
Durga Prasanna Misra1, Ellen M Hauge2, Cynthia S Crowson3
1Department of Clinical Immunology and Rheumatology, Sanjay Gandhi Postgraduate Institute of Medical Sciences (SGPGIMS), Rae Bareli Road, Lucknow 226014, India.
Abstract:
Cardiovascular disease (CVD) risk is increased in most inflammatory rheumatic diseases (IRDs), reiterating the role of inflammation in the initiation and progression of atherosclerosis. An inverse association of CVD risk with body weight and lipid levels has been described in IRDs. Coronary artery calcium scores, plaque burden and characteristics, and carotid plaques on ultrasound optimize CVD risk estimate in IRDs. Biomarkers of cardiac injury, autoantibodies, lipid biomarkers, and cytokines also improve risk assessment in IRDs. Machine learning and deep learning algorithms for phenotype and image analysis hold promise to improve CVD risk stratification in IRDs.
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