ArticleJournal of diabetes science and technology2026
Diversity of Daily Glycemic Phenotypes Is Independently Associated With HbA1c: A Time-Resolved CGM Clustering Analysis.
Article in Journal of diabetes science and technology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundAlthough continuous glucose monitoring (CGM)-derived summary metrics are widely used, they may obscure the intraday temporal organization and potentially overlook clinically relevant differences in daily glucose patterning across time. We aimed to identify distinct daily glycemic phenotypes using time-resolved clustering and to examine whether the diversity of these patterns is independently associated with glycated hemoglobin (HbA1c).
methodsWe analyzed 5902 days of CGM data from 103 participants with type 1 (n = 19) and type 2 (n = 84) diabetes. Daily waveforms were clustered using
resultsEight distinct daily glycemic phenotypes were identified. The Phenotype Diversity Score strongly correlated with HbA1c (
conclusionsTime-resolved CGM clustering reveals clinically meaningful daily glycemic phenotypes and demonstrates that phenotype diversity is independently associated with HbA1c. This pattern-based perspective complements conventional summary metrics and may help explain glycemic heterogeneity among individuals with similar average glucose levels.
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