Ultrasound-based stroke/cardiovascular risk stratification using Framingham Risk Score and ASCVD Risk Score based on "Integrated Vascular Age" instead of "Chronological Age": a multi-ethnic study of Asian Indian, Caucasian, and Japanese cohorts

Ankush Jamthikar; Deep Gupta; Elisa Cuadrado-Godia; Anudeep Puvvula; Narendra N Khanna; Luca Saba; Klaudija Viskovic; Sophie Mavrogeni; Monika Turk; John R Laird; Gyan Pareek; Martin Miner; Petros P Sfikakis; Athanasios Protogerou; George D Kitas; Chithra Shankar; Andrew Nicolaides; Vijay Viswanathan; Aditya Sharma; Jasjit S Suri

doi:10.21037/cdt.2020.01.16

Ultrasound-based stroke/cardiovascular risk stratification using Framingham Risk Score and ASCVD Risk Score based on "Integrated Vascular Age" instead of "Chronological Age": a multi-ethnic study of Asian Indian, Caucasian, and Japanese cohorts

Cardiovasc Diagn Ther. 2020 Aug;10(4):939-954. doi: 10.21037/cdt.2020.01.16.

Authors

Ankush Jamthikar¹, Deep Gupta¹, Elisa Cuadrado-Godia², Anudeep Puvvula³, Narendra N Khanna⁴, Luca Saba⁵, Klaudija Viskovic⁶, Sophie Mavrogeni⁷, Monika Turk⁸, John R Laird⁹, Gyan Pareek¹⁰, Martin Miner¹¹, Petros P Sfikakis¹², Athanasios Protogerou¹³, George D Kitas¹⁴, Chithra Shankar¹⁵, Andrew Nicolaides¹⁶, Vijay Viswanathan¹⁷, Aditya Sharma¹⁸, Jasjit S Suri¹⁹

Affiliations

¹ Department of Electronics and Communications Engineering, Visvesvaraya National Institute of Technology, Nagpur, Maharashtra, India.
² Department of Neurology, IMIM - Hospital del Mar, Barcelona, Spain.
³ Annu's Hospitals for Skin and Diabetes, Nellore, Andra Pradesh, India.
⁴ Department of Cardiology, Indraprastha APOLLO Hospitals, New Delhi, India.
⁵ Department of Radiology, University of Cagliari, Italy.
⁶ Department of Radiology and Ultrasound, University Hospital for Infectious Diseases, Zagreb, Croatia.
⁷ Cardiology Clinic, Onassis Cardiac Surgery Center, Athens, Greece.
⁸ Department of Neurology, University Medical Centre Maribor, Maribor, Slovenia.
⁹ Heart and Vascular Institute, Adventist Health St. Helena, St Helena, CA, USA.
¹⁰ Minimally Invasive Urology Institute, Brown University, Providence, Rhode Island, USA.
¹¹ Men's Health Center, Miriam Hospital Providence, Rhode Island, USA.
¹² Rheumatology Unit, National Kapodistrian University of Athens, Athens, Greece.
¹³ Department of Cardiovascular Prevention & Research Unit Clinic & Laboratory of Pathophysiology, National and Kapodistrian Univ. of Athens, Athens, Greece.
¹⁴ R & D Academic Affairs, Dudley Group NHS Foundation Trust, Dudley, UK.
¹⁵ Shree Polyclinic and lab, Bangalore, India.
¹⁶ Vascular Screening and Diagnostic Centre and University of Nicosia Medical School, Nicosia, Cyprus.
¹⁷ MV Hospital for Diabetes and Professor M Viswanathan Diabetes Research Centre, Chennai, India.
¹⁸ Division of Cardiovascular Medicine, University of Virginia, Charlottesville, VA, USA.
¹⁹ Stroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA, USA.

Abstract

Background: Vascular age (VA) has recently emerged for CVD risk assessment and can either be computed using conventional risk factors (CRF) or by using carotid intima-media thickness (cIMT) derived from carotid ultrasound (CUS). This study investigates a novel method of integrating both CRF and cIMT for estimating VA [so-called integrated VA (IVA)]. Further, the study analyzes and compares CVD/stroke risk using the Framingham Risk Score (FRS)-based risk calculator when adapting IVA against VA.

Methods: The system follows a four-step process: (I) VA using cIMT based using linear-regression (LR) model and its coefficients; (II) VA prediction using ten CRF using a multivariate linear regression (MLR)-based model with gender adjustment; (III) coefficients from the LR-based model and MLR-based model are combined using a linear model to predict the final IVA; (IV) the final step consists of FRS-based risk stratification with IVA as inputs and benchmarked against FRS using conventional method of CA. Area-under-the-curve (AUC) is computed using IVA and benchmarked against CA while taking the response variable as a standardized combination of cIMT and glycated hemoglobin.

Results: The study recruited 648 patients, 202 were Japanese, 314 were Asian Indian, and 132 were Caucasians. Both left and right common carotid arteries (CCA) of all the population were scanned, thus a total of 1,287 ultrasound scans. The 10-year FRS using IVA reported higher AUC (AUC =0.78) compared with 10-year FRS using CA (AUC =0.66) by ~18%.

Conclusions: IVA is an efficient biomarker for risk stratifications for patients in routine practice.

Keywords: Cardiovascular disease (CVD); carotid intima-media thickness; chronological age (CA); conventional cardiovascular risk factors (CCVRFs); integrated vascular age (IVA); risk assessment; stroke; vascular age (VA).