Triglyceride glucose index is a useful marker for predicting subclinical coronary artery disease in the absence of traditional risk factors.
Atherosclerosis
Coronary computed tomographic angiography
Risk factor
Triglyceride glucose index
Journal
Lipids in health and disease
ISSN: 1476-511X
Titre abrégé: Lipids Health Dis
Pays: England
ID NLM: 101147696
Informations de publication
Date de publication:
14 Jan 2020
14 Jan 2020
Historique:
received:
02
11
2019
accepted:
05
01
2020
entrez:
16
1
2020
pubmed:
16
1
2020
medline:
8
10
2020
Statut:
epublish
Résumé
Atherosclerotic cardiovascular (CV) events commonly occur in individuals with a low CV risk burden. This study evaluated the ability of the triglyceride glucose (TyG) index to predict subclinical coronary artery disease (CAD) in asymptomatic subjects without traditional CV risk factors (CVRFs). This retrospective, cross-sectional, and observational study evaluated the association of TyG index with CAD in 1250 (52.8 ± 6.5 years, 46.9% male) asymptomatic individuals without traditional CVRFs (defined as systolic/diastolic blood pressure ≥ 140/90 mmHg; fasting glucose ≥126 mg/dL; total cholesterol ≥240 mg/dL; low-density lipoprotein cholesterol ≥160 mg/dL; high-density lipoprotein cholesterol < 40 mg/dL; body mass index ≥25.0 kg/m The prevalence of CAD increased with elevating TyG index tertiles (group I: 14.8% vs. group II: 19.3% vs. group III: 27.6%; P < 0.001). Multivariate logistic regression models showed that TyG index was associated with an increased risk of CAD (odds ratio [OR] 1.473, 95% confidence interval [CI] 1.026-2.166); especially non-calcified (OR 1.581, 95% CI 1.002-2.493) and mixed plaques (OR 2.419, 95% CI 1.051-5.569) (all P < 0.05). The optimal TyG index cut-off for predicting CAD was 8.44 (sensitivity 47.9%; specificity 68.5%; area under the curve 0.600; P < 0.001). The predictive value of this cut-off improved after considering the non-modifiable factors of old age and male sex. TyG index is an independent marker for predicting subclinical CAD in individuals conventionally considered healthy.
Sections du résumé
BACKGROUND
BACKGROUND
Atherosclerotic cardiovascular (CV) events commonly occur in individuals with a low CV risk burden. This study evaluated the ability of the triglyceride glucose (TyG) index to predict subclinical coronary artery disease (CAD) in asymptomatic subjects without traditional CV risk factors (CVRFs).
METHODS
METHODS
This retrospective, cross-sectional, and observational study evaluated the association of TyG index with CAD in 1250 (52.8 ± 6.5 years, 46.9% male) asymptomatic individuals without traditional CVRFs (defined as systolic/diastolic blood pressure ≥ 140/90 mmHg; fasting glucose ≥126 mg/dL; total cholesterol ≥240 mg/dL; low-density lipoprotein cholesterol ≥160 mg/dL; high-density lipoprotein cholesterol < 40 mg/dL; body mass index ≥25.0 kg/m
RESULTS
RESULTS
The prevalence of CAD increased with elevating TyG index tertiles (group I: 14.8% vs. group II: 19.3% vs. group III: 27.6%; P < 0.001). Multivariate logistic regression models showed that TyG index was associated with an increased risk of CAD (odds ratio [OR] 1.473, 95% confidence interval [CI] 1.026-2.166); especially non-calcified (OR 1.581, 95% CI 1.002-2.493) and mixed plaques (OR 2.419, 95% CI 1.051-5.569) (all P < 0.05). The optimal TyG index cut-off for predicting CAD was 8.44 (sensitivity 47.9%; specificity 68.5%; area under the curve 0.600; P < 0.001). The predictive value of this cut-off improved after considering the non-modifiable factors of old age and male sex.
CONCLUSIONS
CONCLUSIONS
TyG index is an independent marker for predicting subclinical CAD in individuals conventionally considered healthy.
Identifiants
pubmed: 31937313
doi: 10.1186/s12944-020-1187-0
pii: 10.1186/s12944-020-1187-0
pmc: PMC6961240
doi:
Substances chimiques
Biomarkers
0
Blood Glucose
0
Cholesterol, LDL
0
Triglycerides
0
Glucose
IY9XDZ35W2
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
7Subventions
Organisme : National Research Foundation (KR)
ID : 2018R1D1A3B07043344
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