Ranking of stroke and cardiovascular risk factors for an optimal risk calculator design: Logistic regression approach.

AUC Cardiovascular risk calculator Conventional cardiovascular risk factors Covariates Image-based phenotypes Logistic regression Odds ratio Performance Ranking p-value

Journal

Computers in biology and medicine
ISSN: 1879-0534
Titre abrégé: Comput Biol Med
Pays: United States
ID NLM: 1250250

Informations de publication

Date de publication:
05 2019
Historique:
received: 23 01 2019
revised: 21 03 2019
accepted: 21 03 2019
pubmed: 21 4 2019
medline: 1 7 2020
entrez: 21 4 2019
Statut: ppublish

Résumé

Conventional cardiovascular risk factors (CCVRFs) and carotid ultrasound image-based phenotypes (CUSIP) are independently associated with long-term risk of cardiovascular (CV) disease. In this study, 26 cardiovascular risk (CVR) factors which consisted of a combination of CCVRFs and CUSIP together were ranked. Further, an optimal risk calculator using AtheroEdge composite risk score (AECRS1.0) was designed and benchmarked against seven conventional CV risk (CVR) calculators. Two types of ranking were performed: (i) ranking of 26 CVR factors and (ii) ranking of eight types of 10-year risk calculators. In the first case, multivariate logistic regression was used to compute the odds ratio (OR) and in the second, receiver operating characteristic curves were used to evaluate the performance of eight types of CVR calculators using SPSS23.0 and MEDCALC12.0 with validation against STATA15.0. The left and right common carotid arteries (CCA) of 202 Japanese patients were examined to obtain 404 ultrasound scans. CUSIP ranked in the top 50% of the 26 covariates. Intima-media thickness variability (IMTV) and IMTV AECRS1.0

Identifiants

pubmed: 31005010
pii: S0010-4825(19)30099-X
doi: 10.1016/j.compbiomed.2019.03.020
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

182-195

Informations de copyright

Copyright © 2019 Elsevier Ltd. All rights reserved.

Auteurs

Elisa Cuadrado-Godia (E)

Department of Neurology, IMIM - Hospital Del Mar, Barcelona, Spain.

Ankush D Jamthikar (AD)

Department of ECE, VNIT, Nagpur, Maharashtra, India.

Deep Gupta (D)

Department of ECE, VNIT, Nagpur, Maharashtra, India.

Narendra N Khanna (NN)

Department of Cardiology, Indraprastha APOLLO Hospitals, New Delhi, India.

Tadashi Araki (T)

Division of Cardiovascular Medicine, Toho University, Tokyo, Japan.

Md Maniruzzaman (M)

Statistics Discipline, Khulna University, Khulna, Bangladesh.

Luca Saba (L)

Department of Radiology, University of Cagliari, Italy.

Andrew Nicolaides (A)

Vascular Screening and Diagnostic Centre, University of Cyprus, Nicosia, Cyprus.

Aditya Sharma (A)

Cardiovascular Medicine, University of Virginia, VA, USA.

Tomaz Omerzu (T)

Department of Neurology, University Medical Centre Maribor, Slovenia.

Harman S Suri (HS)

Brown University, Rhode Island, USA.

Ajay Gupta (A)

Department of Radiology, Cornell Medical Center, NY, USA.

Sophie Mavrogeni (S)

Cardiology Clinic, Onassis Cardiac Surgery Center, Athens, Greece.

Monika Turk (M)

Department of Neurology, University Medical Centre Maribor, Maribor, Slovenia.

John R Laird (JR)

Heart and Vascular Institute, Adventist Health St. Helena, St Helena, CA, USA.

Athanasios Protogerou (A)

Department of Cardiovascular Prevention & Research Unit Clinic & Laboratory of Pathophysiology, National and Kapodistrian Univ. of Athens, Greece.

Petros Sfikakis (P)

Rheumatology Unit, National Kapodistrian University of Athens, Greece.

George D Kitas (GD)

Research & Development-Academic Affairs, Dudley Group NHS Foundation Trust, Dudley, United Kingdom.

Vijay Viswanathan (V)

MV Hospital for Diabetes and Professor M Viswanathan Diabetes Research Centre, Chennai, India.

Jasjit S Suri (JS)

Stroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA, USA. Electronic address: jasjit.suri@atheropoint.com.

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