{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T22:37:05Z","timestamp":1787697425974,"version":"build-2784847793"},"reference-count":29,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T00:00:00Z","timestamp":1778112000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Endocrinol."],"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>Inflammation and insulin resistance synergistically contribute to the progression of coronary artery disease (CAD), yet the predictive performance of single biomarkers remains limited. This study aimed to evaluate the predictive value of a composite index derived from high-sensitivity C-reactive protein (hs-CRP) and the triglyceride\u2013glucose (TyG) index, termed the hs-CRP-TyG index, and to assess its potential incremental value compared with the TyG index alone.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A total of 1,372 patients who underwent coronary angiography were retrospectively enrolled, including 1,190 patients with CAD and 182 without CAD. The hs-CRP-TyG index was calculated for each participant. Multivariable logistic regression analysis was performed to evaluate associations with CAD risk and severity. Model performance was assessed using receiver operating characteristic (ROC) curves with DeLong test, calibration analysis, and bootstrap internal validation (1,000 resamples) to estimate optimism-corrected performance. Restricted cubic spline (RCS) analysis was used to explore nonlinear dose\u2013response relationships. Decision curve analysis (DCA) was conducted to evaluate clinical utility. Incremental predictive value over the TyG index was assessed using net reclassification improvement (NRI) and integrated discrimination improvement (IDI).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The hs-CRP-TyG level was significantly higher in the CAD group than in the non-CAD group [1.45 (1.02\u20131.90) vs. 1.23 (0.89\u20131.69),\n                      <jats:italic>P<\/jats:italic>\n                      &amp;lt;\u00a00.01]. In the fully adjusted model (Model 4), the hs-CRP-TyG index was independently associated with CAD risk (OR\u00a0=\u00a01.34, 95%\n                      <jats:italic>CI<\/jats:italic>\n                      : 1.03\u20131.78,\n                      <jats:italic>P<\/jats:italic>\n                      &amp;lt;\u00a00.05) and showed a graded positive association with severe coronary lesions. RCS analysis revealed a significant nonlinear dose\u2013response relationship, with an accelerated increase in CAD risk when hs-CRP-TyG exceeded 1.42. In direct comparison, the hs-CRP-TyG index demonstrated higher sensitivity than the TyG index alone (68% vs. 47%), whereas overall discriminative performance was comparable (AUC: 0.79 vs. 0.79; DeLong test\n                      <jats:italic>P<\/jats:italic>\n                      &amp;gt; 0.05). Reclassification analyses (NRI and IDI) suggested limited incremental predictive value after full adjustment. DCA indicated a potential net clinical benefit within certain threshold probabilities. Subgroup analyses confirmed the robustness of these associations, with a stronger effect observed among patients with impaired cardiac function.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The hs-CRP-TyG index is associated with both the presence and severity of CAD and reflects the combined effects of metabolic and inflammatory processes. Although it demonstrates higher sensitivity than the TyG index alone, its overall discriminative performance is comparable, and its incremental predictive value appears limited after full adjustment. This composite marker may have limited complementary value in high-risk settings, but further prospective validation is warranted.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fendo.2026.1836149","type":"journal-article","created":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T04:46:41Z","timestamp":1778129201000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Association of the hs-CRP-TyG index with coronary artery disease risk and angiographic severity: a retrospective comparative study with the TyG index"],"prefix":"10.3389","volume":"17","author":[{"given":"Min","family":"Yang","sequence":"first","affiliation":[{"name":"Department of General Practice, Chongqing University Fuling Hospital, Chongqing University","place":["Chongqing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ling-yun","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of General Practice, Chongqing University Fuling Hospital, Chongqing University","place":["Chongqing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Neurology, Fuling People's Hospital of Chongqing","place":["Chongqing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuan-yuan","family":"Yi","sequence":"additional","affiliation":[{"name":"Department of General Practice, Chongqing University Fuling Hospital, Chongqing University","place":["Chongqing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yun-hu","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of General Practice, Chongqing University Fuling Hospital, Chongqing University","place":["Chongqing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,5,7]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacc.2025.08.015","article-title":"Global, regional, and national burden of cardiovascular diseases and risk factors in 204 countries and territories, 1990-2023","volume":"86","year":"2025","journal-title":"J Am Coll Cardiol"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-021-03392-8","article-title":"The changing landscape of atherosclerosis","volume":"592","author":"Libby","year":"2021","journal-title":"Nature"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1093\/eurheartj\/ehz455","article-title":"2019 ESC\/EAS guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk","volume":"41","author":"Mach","year":"2020","journal-title":"Eur Heart J"},{"key":"B4","doi-asserted-by":"publisher","first-page":"589","DOI":"10.1038\/s41573-021-00198-1","article-title":"Targeting inflammation in atherosclerosis - 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