217. Guidelines: 2021 ESC Cardiovascular Prevention – Question #14 with Dr. Allison Bailey

By CardioNerds - Last Updated: April 28, 2023

The following question refers to Sections 3.3-3.4 of the 2021 ESC CV Prevention Guidelines.The question is asked bystudent Dr. Adriana Mares, answered first by early career preventive cardiologistDr. Dipika Gopal, andthen by expert facultyDr. Allison Bailey.
Dr. Bailey is a cardiologist at Centennial Heart. She is the editor-in-chief of the American College of Cardiology’s Extended Learning (ACCEL) editorial board and was a member of the writing group for the 2018 American Lipid Guidelines. Dr. Bailey, thank you so much for joining us!
The CardioNerds Decipher The Guidelines Series for the 2021 ESC CV Prevention Guidelinesrepresents a collaboration with theACC Prevention of CVD Section, theNational Lipid Association, andPreventive Cardiovascular Nurses Association.

Question #14
Ms. Soya M. Alone is a 70-year-old woman of Bangladeshi ethnicity with a history of anxiety and depression. She currently lives at home by herself, does not have many friends and family that live nearby, and has had a tough year emotionally after the passing of her husband. She spends most of her time in bed with low daily physical activity and has experienced more weakness and exhaustion over the past year along with loss of muscle mass. Which of the following are potential risk modifiers in this patient when considering her risk for CVD?A. Bangladeshi ethnicity B. Psychosocial factorsC. Frailty D. History of anxiety and depressionE. All of the above
Answer #14
The correct answer is E – All of the above.Traditional 10-year CVD risk scores do not perform adequately in all ethnicities. Therefore, multiplication of calculated risk by relative risk for specific ethnic subgroups should be considered (Class IIa, LOE B). Individuals from South Asia have higher CVD rates. The ESC guidelines recommend using a correction factor by multiplying the predicted risk by 1.3 for Indians and Bangladeshis, and 1.7 for Pakistanis. These correction factors are derived from data from QRISK3. In the UK,

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