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ORIGINAL ARTICLE  CAROTID DISEASE 

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

DOI: 10.23736/S0392-9590.20.04338-2

Copyright © 2020 EDIZIONI MINERVA MEDICA

lingua: Inglese

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

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