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Jamthikar A, Gupta D, Saba L, Khanna NN, Araki T, Viskovic K, Mavrogeni S, Laird JR, Pareek G, Miner M, Sfikakis PP, Protogerou A, Viswanathan V, Sharma A, Nicolaides A, Kitas GD, Suri JS. Cardiovascular/stroke risk predictive calculators: a comparison between statistical and machine learning models. Cardiovasc Diagn Ther 2020; 10:919-938. [PMID: 32968651 DOI: 10.21037/cdt.2020.01.07] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Background Statistically derived cardiovascular risk calculators (CVRC) that use conventional risk factors, generally underestimate or overestimate the risk of cardiovascular disease (CVD) or stroke events primarily due to lack of integration of plaque burden. This study investigates the role of machine learning (ML)-based CVD/stroke risk calculators (CVRCML) and compares against statistically derived CVRC (CVRCStat) based on (I) conventional factors or (II) combined conventional with plaque burden (integrated factors). Methods The proposed study is divided into 3 parts: (I) statistical calculator: initially, the 10-year CVD/stroke risk was computed using 13 types of CVRCStat (without and with plaque burden) and binary risk stratification of the patients was performed using the predefined thresholds and risk classes; (II) ML calculator: using the same risk factors (without and with plaque burden), as adopted in 13 different CVRCStat, the patients were again risk-stratified using CVRCML based on support vector machine (SVM) and finally; (III) both types of calculators were evaluated using AUC based on ROC analysis, which was computed using combination of predicted class and endpoint equivalent to CVD/stroke events. Results An Institutional Review Board approved 202 patients (156 males and 46 females) of Japanese ethnicity were recruited for this study with a mean age of 69±11 years. The AUC for 13 different types of CVRCStat calculators were: AECRS2.0 (AUC 0.83, P<0.001), QRISK3 (AUC 0.72, P<0.001), WHO (AUC 0.70, P<0.001), ASCVD (AUC 0.67, P<0.001), FRScardio (AUC 0.67, P<0.01), FRSstroke (AUC 0.64, P<0.001), MSRC (AUC 0.63, P=0.03), UKPDS56 (AUC 0.63, P<0.001), NIPPON (AUC 0.63, P<0.001), PROCAM (AUC 0.59, P<0.001), RRS (AUC 0.57, P<0.001), UKPDS60 (AUC 0.53, P<0.001), and SCORE (AUC 0.45, P<0.001), while the AUC for the CVRCML with integrated risk factors (AUC 0.88, P<0.001), a 42% increase in performance. The overall risk-stratification accuracy for the CVRCML with integrated risk factors was 92.52% which was higher compared all the other CVRCStat. Conclusions ML-based CVD/stroke risk calculator provided a higher predictive ability of 10-year CVD/stroke compared to the 13 different types of statistically derived risk calculators including integrated model AECRS 2.0.
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Affiliation(s)
- Ankush Jamthikar
- Department of Electronics and Communication Engineering, Visvesvaraya National Institute of Technology, Nagpur, Maharashtra, India
| | - Deep Gupta
- Department of Electronics and Communication Engineering, Visvesvaraya National Institute of Technology, Nagpur, Maharashtra, India
| | - Luca Saba
- Department of Radiology, University of Cagliari, Cagliari, Italy
| | - Narendra N Khanna
- Department of Cardiology, Indraprastha APOLLO Hospitals, New Delhi, India
| | - Tadashi Araki
- Division of Cardiovascular Medicine, Toho University, Tokyo, Japan
| | - Klaudija Viskovic
- Department of Radiology and Ultrasound, University Hospital for Infectious Diseases, Zagreb, Croatia
| | - Sophie Mavrogeni
- Cardiology Clinic, Onassis Cardiac Surgery Center, Athens, Greece
| | - John R Laird
- Heart and Vascular Institute, Adventist Health St. Helena, St Helena, CA, USA
| | - Gyan Pareek
- Minimally Invasive Urology Institute, Brown University, Providence, Rhode Island, USA
| | - Martin Miner
- Men's Health Center, Miriam Hospital Providence, Rhode Island, USA
| | - Petros P Sfikakis
- Rheumatology Unit, National and Kapodistrian University of Athens, Athens, Greece
| | - Athanasios Protogerou
- Department of Cardiovascular Prevention & Research Unit Clinic & Laboratory of Pathophysiology, National and Kapodistrian University of Athens, Athens, Greece
| | - Vijay Viswanathan
- MV Hospital for Diabetes and Professor M Viswanathan Diabetes Research Centre, Chennai, India
| | - Aditya Sharma
- Division of Cardiovascular Medicine, University of Virginia, Charlottesville, VA, USA
| | - Andrew Nicolaides
- Vascular Screening and Diagnostic Centre and University of Nicosia Medical School, Nicosia, Cyprus
| | - George D Kitas
- R & D Academic Affairs, Dudley Group NHS Foundation Trust, Dudley, UK
| | - Jasjit S Suri
- Stroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA, USA
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