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Participants were stratified by TyG tertiles. Spectral clustering with complexity\u2010invariant dynamic time warping identified distinct glycaemic variability glucotypes. Comprehensive CGM metrics spanning time\u2010domain, frequency\u2010domain, event\u2010based, and circadian rhythm domains were evaluated. Multivariable logistic regression assessed associations between TyG and glycaemic phenotypes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Across TyG tertiles, we observed progressive increases in HbA1c (6.8\u2009\u00b1\u20091.5%, 7.2\u2009\u00b1\u20091.2%, 7.3\u2009\u00b1\u20091.3%,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.011), fasting glucose (6.1\u2009\u00b1\u20091.1, 7.2\u2009\u00b1\u20091.6, 8.5\u2009\u00b1\u20092.8\u2009mmol\/L,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001), and triglycerides (0.9\u2009\u00b1\u20090.2, 1.4\u2009\u00b1\u20090.4, 2.7\u2009\u00b1\u20091.0\u2009mmol\/L,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001). Most notably, patients in the highest TyG tertile exhibited sustained hyperglycaemia with lower TIR (81.8% to 72.8 to 70.3%,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.001), elevated TAR (15.9% vs. 29.1%,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001), and paradoxically reduced TBR (2.3% to 1.4% to 0.6%,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.014) and CV (26.2% to 25.8% to 23.8%,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.021). Frequency domain analysis demonstrated that elevated TyG was associated with high\u2010level, low\u2010frequency glucose oscillations. Higher TyG tertiles demonstrated increased prevalence of severe variability glucotype (32.3% to 53.8% to 63.4%), with TyG emerging as the strongest independent predictor (OR\u2009=\u20091.87, 95% CI: 1.42\u20132.50,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Elevated TyG identifies a distinct glycaemic phenotype characterized by high\u2010level, low\u2010frequency oscillations, sustained hyperglycaemia, and minimal hypoglycaemic risk. T2DM patients with high TyG levels may be appropriate candidates for more intensified glucose\u2010lowering strategies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/dom.70558","type":"journal-article","created":{"date-parts":[[2026,2,18]],"date-time":"2026-02-18T11:48:24Z","timestamp":1771415304000},"page":"3752-3763","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Unveiling glycaemic variability patterns linked to the triglyceride\u2010glucose index in type 2 diabetes: Insights from continuous glucose monitoring"],"prefix":"10.1111","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6254-1409","authenticated-orcid":false,"given":"Yunxiao","family":"Wu","sequence":"first","affiliation":[{"name":"Department of Epidemiology and Biostatistics, School of Public Health Peking University  Beijing China"},{"name":"Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of 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