{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T00:12:04Z","timestamp":1790035924122,"version":"4.0.1"},"reference-count":37,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T00:00:00Z","timestamp":1765497600000},"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>Background<\/jats:title>\n                    <jats:p>Insulin resistance and systemic inflammation jointly drive deterioration of cardiorenal-metabolic function; however, how composite indices reflect disease severity remains unclear. We compared the triglyceride\u2013glucose\u2013neutrophil-to-lymphocyte ratio (TyG-NLR) and a C-reactive protein\u2013TyG\u2013based index (CTI) to examine their associations with severity outcomes in hospitalized adults with type 2 diabetes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a retrospective study of hospitalized adults with type 2 diabetes at the Affiliated Hospital of Qingdao University, classifying cardiorenal disease into four severity levels. Using ordinal logistic regression, we evaluated the independent associations of the C-reactive protein\u2013TyG\u2013based index (CTI) and the triglyceride\u2013glucose neutrophil-to-lymphocyte ratio (TyG-NLR) with severity, performed trend testing (p-trend), and explored potential nonlinearity with restricted cubic splines (RCS). For robustness, we additionally fitted a partial proportional odds model (VGAM framework) and a multinomial logistic model. Relative to a base covariate model, we assessed the incremental value of these indices in terms of overall model performance (AIC, BIC, Nagelkerke R\u00b2, likelihood-ratio test), discrimination (AUC), calibration (calibration plot, slope, and calibration-in-the-large [CITL]), and clinical net benefit via decision-curve analysis (DCA).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A total of 2, 885 patients were included. In multivariable ordinal logistic regression analysis, both higher quartiles of CTI and TyG-NLR were significantly associated with increased disease severity (CTI_Q4 vs Q1: OR = 1.59, 95% CI 1.21\u20132.09; TyG-NLR_Q4 vs Q1: OR = 2.14, 95% CI 1.64\u20132.78; both P&amp;lt; 0.001). The Brant test indicated partial violation of the proportional odds assumption; sensitivity analysis using a VGAM-based partial proportional odds model yielded consistent results across thresholds. Trend tests revealed a significant linear increase in disease severity across quartiles for both indices (all P for trend &amp;lt; 0.001).Restricted cubic spline (RCS) analysis showed a nonlinear relationship between TyG-NLR and disease severity (LRT \u03c7\u00b2= 34.438, P &amp;lt; 0.001), with the risk plateauing beyond a TyG-NLR value of approximately 16.64; in contrast, CTI exhibited an approximately linear association (LRT \u03c7\u00b2 = 1.486, P = 0.476). Regarding model performance, the TyG-NLR model achieved the best overall fit (AIC = 4367, BIC = 4488, Nagelkerke R\u00b2 = 0.245, LR \u03c7\u00b2 = 50.8, P = 5.3 \u00d7 10\n                      <jats:sup>-<\/jats:sup>\n                      \u00b9\u00b9), while CTI yielded moderate improvement (LR \u03c7\u00b2 = 12.3, P = 0.006). In terms of discrimination, the TyG-NLR model attained the highest AUC of 0.680 (95% CI 0.668\u20130.693) and the lowest Brier score of 0.476. Calibration curves demonstrated good agreement at all thresholds (\u22651, \u22652, \u22653), with the TyG-NLR model showing the closest alignment with the ideal line.Decision curve analysis (DCA) indicated that TyG-NLR provided the greatest net clinical benefit across a wide range of threshold probabilities (0.05\u20130.35), followed by CTI, while the incremental value of TyG alone was minimal. Both VGAM and multinomial logistic models yielded consistent directions of association, supporting the robustness of these findings.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>In adults with type 2 diabetes, both CTI and TyG-NLR were independently associated with cardiorenal disease severity.Notably, TyG-NLR demonstrated a steeper risk gradient and modest improvements in discrimination and calibration, and it yielded slightly higher net clinical benefit across clinically relevant decision thresholds. These findings suggest potential clinical utility for risk stratification, although the overall predictive gain was moderate and requires further validation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fendo.2025.1735949","type":"journal-article","created":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T05:15:08Z","timestamp":1765516508000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Impact of the triglyceride\u2013glucose\u2013neutrophil-to-lymphocyte ratio and the C-reactive protein\u2013TyG index on cardio-renal disease in patients with type 2 diabetes"],"prefix":"10.3389","volume":"16","author":[{"given":"Ying","family":"Guo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongjian","family":"Jia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengyan","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tong","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhendong","family":"Diao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xicheng","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jietao","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,12,12]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1093\/qjmed\/hcaf022","article-title":"Global burden of cardiovascular diseases and its risk factors, 1990-2021: A systematic analysis for the global burden of disease study 2021","volume":"118","author":"Tan","year":"2025","journal-title":"QJM: Monthly J Assoc Phys"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacc.2019.10.009","article-title":"The global burden of cardiovascular diseases and risk factors: 2020 and beyond","volume":"74","author":"Mensah","year":"2019","journal-title":"J Am Coll Cardiol"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1016\/s0140-6736(20)30925-9","article-title":"Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: A systematic analysis for the global burden of disease study 2019","volume":"396","author":"Vos","year":"2020","journal-title":"Lancet (London England)"},{"key":"B4","doi-asserted-by":"publisher","first-page":"795","DOI":"10.1016\/s0140-6736(19)32008-2","article-title":"Modifiable risk factors, cardiovascular disease, and mortality in 155\u2008722 individuals from 21 high-income, middle-income, and low-income countries (Pure): A prospective cohort study","volume":"395","author":"Yusuf","year":"2020","journal-title":"Lancet (London England)"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1161\/circulationaha.106.674143","article-title":"Risk factors for the progression of coronary artery calcification in asymptomatic subjects: results from the multi-ethnic study of atherosclerosis (Mesa)","volume":"115","author":"Kronmal","year":"2007","journal-title":"Circulation"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCULATIONAHA.107.699579","article-title":"General cardiovascular risk profile for use in primary care","volume":"117","author":"D\u2019Agostino","year":"2008","journal-title":"Circulation"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1093\/eurheartj\/ehab309","article-title":"Score2 risk prediction algorithms: new models to estimate 10-year risk of cardiovascular disease in europe","volume":"42","year":"2021","journal-title":"Eur Heart J"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1038\/ki.2010.536","article-title":"Lower estimated glomerular filtration rate and higher albuminuria are associated with all-cause and cardiovascular mortality. 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