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A novel numerical model of combination levels of C-peptide and insulin in coronary artery disease risk prediction

Authors :
Hao Dai
Qi Fu
Heng Chen
Mei Zhang
Min Sun
Yong Gu
Ningtian Zhou
Tao Yang
Source :
Mathematical Biosciences and Engineering, Vol 18, Iss 3, Pp 2675-2687 (2021)
Publication Year :
2021
Publisher :
AIMS Press, 2021.

Abstract

Objective: Insulin resistance is a major risk factor for coronary artery disease (CAD). The C-peptide-to-insulin ratio (C/I) is associated with hepatic insulin clearance and insulin resistance. The current study was designed to establish a novel C/I index (CPIRI) model and provide early risk assessment of CAD. Methods: A total of 865 adults diagnosed with new-onset diabetes mellitus (DM) within one year and 54 healthy controls (HC) were recruited to develop a CPIRI model. The CPIRI model was established with fasting C/I as the independent variable and homeostasis model assessment of insulin resistance (HOMA-IR) as the dependent variable. Associations between the CPIRI model and the severity of CAD events were also assessed in 45 hyperglycemic patients with CAD documented via coronary arteriography (CAG) and whom underwent stress echocardiography (SE) and exercise electrocardiography test (EET). Results: Fasting C-peptide/insulin and HOMA-IR were hyperbolically correlated in DM patients and HC, and log(C/I) and log(HOMA-IR) were linearly and negatively correlated. The respective correlational coefficients were −0.83 (p < 0.001) and −0.76 (p < 0.001). The equations CPIRI(DM) = 670/(C/I)2.24 + 0.25 and CPIRI(HC) = 670/(C/I)2.24 − 1 (F = 1904.39, p < 0.001) were obtained. Patients with insulin resistance exhibited severe coronary artery impairment and myocardial ischemia. In CAD patients there was no significant correlation between insulin resistance and the number of vessels involved. Conclusions: CPIRI can be used to effectively evaluate insulin resistance, and the combination of CPIRI and non-invasive cardiovascular examination is of great clinical value in the assessment of CAD.

Details

Language :
English
ISSN :
15510018
Volume :
18
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Mathematical Biosciences and Engineering
Publication Type :
Academic Journal
Accession number :
edsdoj.8f4b7984429347479f36b20b2fe5db82
Document Type :
article
Full Text :
https://doi.org/10.3934/mbe.2021136?viewType=HTML