ORIGINAL ARTICLE  CAROTID DISEASE Free access

International Angiology 2020 August;39(4):290-306

DOI: 10.23736/S0392-9590.20.04338-2

Copyright © 2020 EDIZIONI MINERVA MEDICA

language: English

Integration of estimated glomerular filtration rate biomarker in image-based cardiovascular disease/stroke risk calculator: a south Asian-Indian diabetes cohort with moderate chronic kidney disease

Vijay VISWANATHAN ¹, Ankush D. JAMTHIKAR ², Deep GUPTA ², Anudeep PUVVULA ³, Narendra N. KHANNA ⁴, Luca SABA ⁵, Klaudija VISKOVIC ⁶, Sophie MAVROGENI ⁷, Monika TURK ⁸, John R. LAIRD ⁹, Gyan PAREEK ¹⁰, Martin MINER ¹¹, Jna AJULUCHUKWU ¹², Petros P. SFIKAKIS ¹³, Athanasios PROTOGEROU ¹⁴, George D. KITAS ¹⁵, Andrew NICOLAIDES ¹⁶, Aditya SHARMA ¹⁷, Jasjit S. SURI ¹⁸ ✉

¹ MV Hospital for Diabetes and Professor M Viswanathan Diabetes Research Centre, Chennai, India; ² Department of Electronics and Communications, Visvesvaraya National Institute of Technology, Nagpur, India; ³ Annu’s Hospitals for Skin and Diabetes, Nellore, India; ⁴ Department of Cardiology, Indraprastha APOLLO Hospitals, New Delhi, India; ⁵ Department of Radiology, University of Cagliari, 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 Center Maribor, Maribor, Slovenia; ⁹ Heart and Vascular Institute, Adventist Health St. Helena, St Helena, CA, USA; ¹⁰ Minimally Invasive Urology Institute, Brown University, Providence, RI, USA; ¹¹ Men’s Health Center, Miriam Hospital, Providence, RI, USA; ¹² Department of Medicine, LUTH (Lagos University Teaching Hospital), Lagos, Nigeria; ¹³ Unit of Rheumatology, National Kapodistrian University, Athens, Greece; ¹⁴ Department of Cardiovascular Prevention and, Research Unit Clinic, Laboratory of Pathophysiology, National and Kapodistrian University, Athens, Greece; ¹⁵ R & D Academic Affairs, Dudley Group NHS Foundation Trust, Dudley, UK; ¹⁶ Vascular Screening and Diagnostic Center, University of Nicosia Medical School, Nicosia, Cyprus; ¹⁷ Division of Cardiovascular Medicine, University of Virginia, Charlottesville, VA, USA; ¹⁸ Division of Stroke Monitoring and Diagnostics, AtheroPoint™, Roseville, CA, USA

BACKGROUND: Recently, a 10-year image-based integrated calculator (called AtheroEdge Composite Risk Score-AECRS1.0) was developed which combines conventional cardiovascular risk factors (CCVRF) with image phenotypes derived from carotid ultrasound (CUS). Such calculators did not include chronic kidney disease (CKD)-based biomarker called estimated glomerular filtration rate (eGFR). The novelty of this study is to design and develop an advanced integrated version called-AECRS2.0 that combines eGFR with image phenotypes to compute the composite risk score. Furthermore, AECRS2.0 was benchmarked against QRISK3 which considers eGFR for risk assessment.
METHODS: The method consists of three major steps: 1) five, current CUS image phenotypes (CUSIP) measurements using AtheroEdge system (AtheroPoint, CA, USA) consisting of: average carotid intima-media thickness (cIMTave), maximum cIMT (cIMTmax), minimum cIMT (cIMTmin), variability in cIMT (cIMTV), and total plaque area (TPA); 2) five, 10-year CUSIP measurements by combining these current five CUSIP with 11 CCVRF (age, ethnicity, gender, body mass index, systolic blood pressure, smoking, carotid artery type, hemoglobin, low-density lipoprotein cholesterol, total cholesterol, and eGFR); 3) AECRS2.0 risk score computation and its comparison to QRISK3 using area-under-the-curve (AUC).
RESULTS: South Asian-Indian 339 patients were retrospectively analyzed by acquiring their left/right common carotid arteries (678 CUS, mean age: 54.25±9.84 years; 75.22% males; 93.51% diabetic with HbA1c ≥6.5%; and mean eGFR 73.84±20.91 mL/min/1.73m²). The proposed AECRS2.0 reported higher AUC (AUC=0.89, P<0.001) compared to QRISK3 (AUC=0.51, P<0.001) by ~74% in CKD patients.
CONCLUSIONS: An integrated calculator AECRS2.0 can be used to assess the 10-year CVD/stroke risk in patients suffering from CKD. AECRS2.0 was much superior to QRISK3.

KEY WORDS: Atherosclerosis; Stroke; Cardiovascular diseases; Risk assessment