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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).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      This retrospective, cross-sectional, and observational study evaluated the association of TyG index with CAD in 1250 (52.8\u2009\u00b1\u20096.5\u2009years, 46.9% male) asymptomatic individuals without traditional CVRFs (defined as systolic\/diastolic blood pressure\u2009\u2265\u2009140\/90\u2009mmHg; fasting glucose \u2265126\u2009mg\/dL; total cholesterol \u2265240\u2009mg\/dL; low-density lipoprotein cholesterol \u2265160\u2009mg\/dL; high-density lipoprotein cholesterol &lt;\u200940\u2009mg\/dL; body mass index \u226525.0\u2009kg\/m\n                      <jats:sup>2<\/jats:sup>\n                      ; current smoking; and previous medical history of hypertension, diabetes, or dyslipidemia). CAD was defined as the presence of any coronary plaque on coronary computed tomographic angiography. The participants were divided into three groups based on TyG index tertiles.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The prevalence of CAD increased with elevating TyG index tertiles (group I: 14.8% vs. group II: 19.3% vs. group III: 27.6%;\n                      <jats:italic>P<\/jats:italic>\n                      \u2009&lt;\u20090.001). 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\u20132.166); especially non-calcified (OR 1.581, 95% CI 1.002\u20132.493) and mixed plaques (OR 2.419, 95% CI 1.051\u20135.569) (all\n                      <jats:italic>P<\/jats:italic>\n                      \u2009&lt;\u20090.05). The optimal TyG index cut-off for predicting CAD was 8.44 (sensitivity 47.9%; specificity 68.5%; area under the curve 0.600;\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0&lt;\u20090.001). The predictive value of this cut-off improved after considering the non-modifiable factors of old age and male sex.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>TyG index is an independent marker for predicting subclinical CAD in individuals conventionally considered healthy.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12944-020-1187-0","type":"journal-article","created":{"date-parts":[[2020,1,14]],"date-time":"2020-01-14T10:02:40Z","timestamp":1578996160000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":105,"title":["Triglyceride glucose index is a useful marker for predicting subclinical coronary artery disease in the absence of traditional risk factors"],"prefix":"10.1186","volume":"19","author":[{"given":"Gyung-Min","family":"Park","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Young-Rak","family":"Cho","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5502-9933","authenticated-orcid":false,"given":"Ki-Bum","family":"Won","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu Jin","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sangwoo","family":"Park","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Soe Hee","family":"Ann","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong-Giun","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eun Ji","family":"Park","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shin-Jae","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sang-Gon","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dong Hyun","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joon-Won","family":"Kang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tae-Hwan","family":"Lim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hong-Kyu","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jaewon","family":"Choe","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seung-Whan","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Young-Hak","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,1,14]]},"reference":[{"key":"1187_CR1","doi-asserted-by":"publisher","first-page":"898","DOI":"10.1001\/jama.290.7.898","volume":"290","author":"UN Khot","year":"2003","unstructured":"Khot UN, Khot MB, Bajzer CT, Sapp SK, Ohman EM, Brener SJ, Ellis SG, Lincoff AM, Topol EJ. 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